NetApp Aktienkurs
Vergleich mit Peer Group
📊 Peer Group
📈 Was ist das?
Die Peer Group sind die Unternehmen mit dem ähnlichsten Geschäftsmodell. Sie dienen als Vergleichsmaßstab, um eine Aktie einzuordnen.
🧮 Wie wird sie ausgewählt?
Nach Ähnlichkeit des Geschäftsmodells, also Unternehmen aus derselben Branche, mit vergleichbaren Produkten und einer ähnlichen Kundengruppe. Nur so vergleichst du Äpfel mit Äpfeln.
🏛️ Wofür ist sie wichtig?
Ob eine Aktie günstig oder teuer ist, lässt sich am ehesten im Vergleich beurteilen. Ein KGV von 18 oder ein EV/FCF von 20 wirkt je nach Maßstab günstig oder teuer. Die Peer Group liefert dabei den treffsichersten Maßstab: Unternehmen mit ähnlichem Geschäftsmodell, die denselben Bedingungen unterliegen.
🎯 Was bedeutet das für Anleger?
Liegt eine Kennzahl unter dem Peer-Durchschnitt, ist die Aktie relativ günstiger bewertet, über dem Durchschnitt entsprechend teurer. Ein Abschlag zur Peer Group kann eine Chance sein, aber auch einen Grund haben (zum Beispiel geringeres Wachstum). Der Vergleich ist ein Startpunkt, kein Urteil.
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📘 Marktkapitalisierung
📈 Was ist das?
Die Marktkapitalisierung zeigt, wie viel ein Unternehmen laut Börse aktuell wert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft Unternehmen in Größenklassen (Large, Mid, Small Cap) einzuordnen und gibt Hinweise auf Marktmacht und Stabilität.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Große Unternehmen gelten als stabiler, zahlen oft Dividenden, wachsen aber langsamer.
- Kleine Firmen können stärker wachsen, sind aber schwankungsanfälliger.
- Die Marktkapitalisierung ist ein guter Indikator für Unternehmensgröße, aber kein Maß für Unter- oder Überbewertung.
📘 Enterprise Value (Unternehmenswert)
📈 Was ist das?
Der Enterprise Value (EV) zeigt, was ein Unternehmen tatsächlich kostet, wenn man es komplett übernehmen würde – inklusive Schulden und abzüglich Cash.
🧮 Wie wird es berechnet?
(= Marktkapitalisierung + Nettoverschuldung)
🏛️ Wofür ist es wichtig?
Der EV ist eine realistischere Bewertungsbasis als die Marktkapitalisierung, da er die Kapitalstruktur berücksichtigt. Er ist Grundlage für Kennzahlen wie EV/FCF oder EV/Sales.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Der Enterprise Value zeigt, was ein Unternehmen tatsächlich wert ist – unabhängig davon, wie es finanziert ist.
- Er ist besonders wichtig für professionelle Investoren, da er eine objektivere Grundlage für Bewertungsvergleiche bietet als die Marktkapitalisierung allein.
- Ein Unternehmen mit hoher Verschuldung erscheint im EV teurer, eines mit viel Cash günstiger – auch wenn sie an der Börse gleich viel wert sind.
📘 Nettoverschuldung
📈 Was ist das?
Die Nettoverschuldung zeigt, wie viele Schulden nach Abzug des verfügbaren Cashs tatsächlich verbleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie zeigt, wie stark ein Unternehmen von Fremdkapital abhängig ist – und wie gut es in der Lage ist, seine Schulden kurzfristig zu bedienen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine niedrige oder negative Nettoverschuldung bedeutet hohe finanzielle Stabilität.
- Unternehmen mit viel Cash und geringer Verschuldung sind besser gerüstet für Krisen.
- Eine hohe Nettoverschuldung erhöht das Risiko – besonders bei steigenden Zinsen oder konjunkturellen Schwächen.
📘 Cash
📈 Was ist das?
Der Cashbestand zeigt, wie viele liquide Mittel einem Unternehmen sofort zur Verfügung stehen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Er gibt Auskunft über die finanzielle Flexibilität: Ein hoher Cashbestand ermöglicht Investitionen, Rückkäufe oder Krisenresistenz.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Cashbestand zeigt finanzielle Stärke und Handlungsspielraum.
- Cash kann für Investitionen, Schuldentilgung oder Aktienrückkäufe genutzt werden.
- Allerdings: Zu viel ungenutztes Kapital kann auch auf mangelnde Investitionsideen hinweisen.
📘 Anzahl ausstehender Aktien
📈 Was ist das?
Die Anzahl ausstehender Aktien gibt an, wie viele Aktien eines Unternehmens aktuell im Umlauf sind und von Investoren gehalten werden.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie ist die Grundlage für viele Kennzahlen wie Gewinn je Aktie (EPS), Marktkapitalisierung oder KGV.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Je weniger Aktien im Umlauf sind, desto höher fällt z. B. der Gewinn je Aktie aus – wichtig für Bewertung und Dividendenrendite.
- Aktienrückkäufe verringern die Anzahl ausstehender Aktien – und steigern den Wert je Aktie.
- Kapitalerhöhungen haben den gegenteiligen Effekt: mehr Aktien → Verwässerung der bestehenden Anteile.
📘 Kurs-Gewinn-Verhältnis (KGV)
📈 Was ist das?
Das KGV zeigt, wie oft der Gewinn pro Aktie im aktuellen Aktienkurs enthalten ist – also wie „teuer“ eine Aktie im Verhältnis zum Gewinn ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KGV gehört zu den bekanntesten Bewertungskennzahlen. Es hilft Anlegern einzuschätzen, ob eine Aktie im Vergleich zu ihrem Gewinn eher günstig oder teuer erscheint.
🧮 Berechnung
📊 KGV (TTM) = bezogen auf den Gewinn der letzten 12 Monate (Trailing Twelve Months):🎯 Was bedeutet das für Anleger?
- Ein niedriges KGV kann auf eine günstige Bewertung hindeuten – oder auf Probleme im Geschäftsmodell.
- Ein hohes KGV kann Wachstumserwartungen widerspiegeln – oder eine überbewertete Aktie.
📘 Kurs-Umsatz-Verhältnis (KUV)
📈 Was ist das?
Das KUV zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen – unabhängig vom Gewinn.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KUV ist besonders bei wachstumsstarken oder noch nicht profitablen Unternehmen hilfreich. Es zeigt, wie hoch der Umsatz an der Börse bewertet wird.
🧮 Berechnung
Marktkapitalisierung = 42,24 Mrd. $ | Umsatz (TTM) = 7,39 Mrd. $
Marktkapitalisierung = 42,24 Mrd. $ | Umsatz erwartet = 8,34 Mrd. $
🎯 Was bedeutet das für Anleger?
- Ein niedriges KUV kann auf Unterbewertung hindeuten – oder auf schwache Margen.
- Ein hohes KUV kann hohe Erwartungen widerspiegeln – oder übermäßigen Optimismus.
- Besonders sinnvoll bei Wachstumsunternehmen, bei denen der Gewinn oder Free Cashflow (noch) keine Aussagekraft hat.
📘 Unternehmenswert zu Umsatz (EV/Sales)
📈 Was ist das?
EV/Sales zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen, wenn man auch Schulden und Cash berücksichtigt – es ist eine kapitalstrukturbereinigte Version des KUV.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Diese Kennzahl eignet sich besonders für den Vergleich von Unternehmen mit unterschiedlicher Verschuldung – sie zeigt, wie teuer ein Unternehmen tatsächlich im Verhältnis zum Umsatz ist.
🧮 Berechnung
Enterprise Value = 41,15 Mrd. $ | Umsatz (TTM) = 7,39 Mrd. $
Enterprise Value = 41,15 Mrd. $ | Umsatz erwartet = 8,34 Mrd. $
🎯 Was bedeutet das für Anleger?
- EV/Sales ist neutral gegenüber der Kapitalstruktur und eignet sich gut für Unternehmensvergleiche.
- Ein niedriges Verhältnis kann auf eine günstig bewertete Aktie hindeuten – ein hohes Verhältnis auf hohe Erwartungen oder Überbewertung.
- Besonders nützlich bei wachstumsstarken, noch nicht profitablen Firmen.
📘 Unternehmenswert zu Free Cashflow (EV/FCF) | ex SBC
📈 Was ist das?
EV/FCF setzt den Unternehmenswert eines Unternehmens ins Verhältnis zu seinem Free Cashflow. Die Kennzahl zeigt damit, mit welchem Vielfachen des aktuellen Free Cashflows ein Unternehmen bewertet wird. EV/FCF ex SBC berücksichtigt zusätzlich aktienbasierte Vergütungen (Stock-Based Compensation, SBC). SBC verursacht zwar keinen direkten Cash-Abfluss, kann bestehende Aktionäre jedoch durch die Ausgabe zusätzlicher Aktien verwässern. Deshalb wird SBC bei dieser Variante vom Free Cashflow abgezogen.
🧮 Wie wird es berechnet?
EV/FCF ex SBC = Enterprise Value ÷ (Free Cashflow (TTM) − SBC)
🏛️ Wofür ist es wichtig?
EV/FCF ermöglicht eine Bewertung auf Basis des Free Cashflows und ergänzt damit gewinnbasierte Bewertungskennzahlen wie das KGV. Die Variante ex SBC berücksichtigt zusätzlich die wirtschaftliche Belastung durch aktienbasierte Vergütungen und ermöglicht dadurch eine konservativere Betrachtung aus Sicht der Aktionäre.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriges EV/FCF bedeutet, dass der Unternehmenswert im Verhältnis zum aktuellen Free Cashflow niedrig ist. Die Ursachen dafür sollten jedoch immer im Unternehmens- und Branchenkontext betrachtet werden.
- Ein hohes EV/FCF bedeutet, dass der Unternehmenswert im Verhältnis zum aktuellen Free Cashflow hoch ist. Das kann beispielsweise auf hohe Wachstumserwartungen oder eine vorübergehend schwache Cash-Generierung zurückzuführen sein.
- Bei positiver SBC und positivem bereinigtem Free Cashflow fällt EV/FCF ex SBC in der Regel höher aus als das klassische EV/FCF.
- Besonders aussagekräftig ist die Kennzahl bei Unternehmen mit relativ stabilen und gut einschätzbaren Cashflows.
- Bei negativem oder sehr niedrigem Free Cashflow ist EV/FCF nur eingeschränkt aussagekräftig und sollte nicht wie ein gewöhnliches Bewertungsmultiple interpretiert werden.
📘 Kurs-Buchwert-Verhältnis (KBV)
📈 Was ist das?
Das KBV zeigt, wie hoch der Marktwert eines Unternehmens im Verhältnis zu seinem bilanziellen Eigenkapital ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KBV ist besonders bei Substanzwerten (z. B. Banken, Industrie) relevant. Es hilft Anlegern zu erkennen, ob ein Unternehmen unter oder über seinem buchhalterischen Vermögen bewertet ist.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein KBV unter 1 kann auf Unterbewertung oder schwache Rentabilität hindeuten.
- Ein KBV über 1 zeigt, dass der Markt dem Unternehmen Mehrwert über den Buchwert hinaus zuschreibt (z. B. Marken, Patente, Wachstum).
- Das KBV eignet sich besonders gut für Unternehmen mit stabilen, materiellen Vermögenswerten.
📘 Dividende je Aktie
📈 Was ist das?
Die Dividende je Aktie zeigt, wie viel Geld ein Unternehmen pro Aktie an seine Aktionäre ausschüttet – typischerweise jährlich oder quartalsweise.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie ist die absolute Größe der Auszahlung je Aktie – wichtig für alle, die regelmäßige Erträge suchen oder Dividendenstrategien verfolgen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine stabile oder wachsende Dividende je Aktie ist oft ein Zeichen für ein solides Geschäftsmodell.
- Die Dividende je Aktie allein sagt aber nichts über die Rendite – dafür ist auch der Aktienkurs relevant (→ Dividendenrendite).
- Langfristig steigende Dividenden sind oft ein sehr gutes Merkmal (z. B. Dividenden-Aristokraten).
📘 Dividendenrendite
📈 Was ist das?
Die Dividendenrendite zeigt, wie hoch die Dividende eines Unternehmens im Verhältnis zum Aktienkurs ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft dabei, Dividendenaktien vergleichbar zu machen – unabhängig vom absoluten Auszahlungsbetrag.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine stabile Dividendenrendite kann auf verlässliche Ausschüttungen hinweisen.
- Ein Vergleich der 1J- und 5J-Rendite hilft zu erkennen, ob das Dividendenwachstum mit dem Kurswachstum Schritt hält.
- Eine niedrige Rendite ist nicht zwingend negativ – sie kann auf starkes Kurswachstum hindeuten.
📘 Dividendenwachstum
📈 Was ist das?
Das Dividendenwachstum zeigt, wie stark ein Unternehmen seine Dividende je Aktie über die Zeit gesteigert hat.
🧮 Wie wird es berechnet?
5J: durchschnittliche jährliche Wachstumsrate (CAGR)
🏛️ Wofür ist es wichtig?
Stetig steigende Dividenden gelten als Zeichen für finanzielle Stärke und Aktionärsorientierung – besonders interessant für langfristige Investoren.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein stabiles Dividendenwachstum ist ein Zeichen nachhaltiger Ertragskraft.
- Ein hohes Dividendenwachstum kann ein erheblicher Hebel deiner Rendite sein:
- Wenn ein Unternehmen z. B. 1 € Dividende zahlt und diese über 5 Jahre jährlich um 15 % erhöht, bekommst du im 5. Jahr bereits 2 € je Aktie – doppelt so viel wie zu Beginn!
📘 Ausschüttungsquote (Payout)
📈 Was ist das?
Die Ausschüttungsquote zeigt, wie viel Prozent des Unternehmensgewinns (pro Aktie) als Dividende an die Aktionäre ausgeschüttet wird.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Quote hilft einzuschätzen, ob eine Dividende auf Dauer tragfähig ist – besonders im Verhältnis zum erzielten Gewinn.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine niedrige Ausschüttungsquote bedeutet: Das Unternehmen behält einen größeren Teil des Gewinns für Investitionen – typisch für Wachstumsunternehmen.
- Eine moderate Quote (z. B. 25–50 %) steht oft für ein gesundes Gleichgewicht zwischen Ausschüttung und Zukunftsinvestitionen.
- Hohe Ausschüttungsquoten können attraktiv wirken, sind aber riskanter, wenn die Gewinne schwanken oder sinken.
📘 Dividendensteigerungen in Folge (Erhöhungen)
📈 Was ist das?
Diese Kennzahl zeigt, wie viele Jahre in Folge ein Unternehmen seine Dividende pro Aktie erhöht hat – ohne Kürzung oder Aussetzung.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Ein langer Track Record kontinuierlicher Erhöhungen spricht für Verlässlichkeit, solide Finanzen und aktionärsfreundliche Unternehmenspolitik.
🎯 Was bedeutet das für Anleger?
- Ein langer Zeitraum mit Dividendensteigerungen stärkt das Vertrauen – besonders in Krisenzeiten.
- Solche Unternehmen gelten als verlässlich und planbar für Einkommensinvestoren.
- Je länger die Serie, desto stärker das Commitment gegenüber den Aktionären.
📘 Umsatz
📈 Was ist das?
Der Umsatz zeigt, wie viel ein Unternehmen insgesamt mit seinen Produkten und Dienstleistungen verdient – also den Bruttoerlös vor Abzug von Kosten.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Umsatz ist eine der zentralen Kennzahlen zur Einschätzung der Unternehmensgröße, Marktstellung und Wachstumskraft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein wachsender Umsatz zeigt eine steigende Nachfrage und kann ein guter Frühindikator für Gewinnsteigerungen sein.
- Vergleiche von aktuellem und erwartetem Umsatz geben Hinweise auf das Marktumfeld und Analystenerwartungen.
- Wichtig: Starker Umsatz allein genügt nicht – auch Margen und Profitabilität zählen.
📘 EBITDA
📈 Was ist das?
EBITDA steht für „Earnings Before Interest, Taxes, Depreciation and Amortization“ – also Gewinn vor Zinsen, Steuern und Abschreibungen. Es zeigt das operative Ergebnis eines Unternehmens, bereinigt um bilanztechnische und finanzierungsbedingte Effekte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBITDA ist eine verbreitete Kennzahl zur Beurteilung der operativen Leistungsfähigkeit – insbesondere bei kapitalintensiven Unternehmen oder im internationalen Vergleich.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes oder wachsendes EBITDA spricht für starke operative Erträge – unabhängig von Bilanzierung oder Steuerlast.
- EBITDA ist besonders nützlich, um Unternehmen branchenübergreifend zu vergleichen.
- Wichtig: EBITDA ist keine offizielle Gewinnkennzahl – Abschreibungen und Finanzierungskosten werden ausgeklammert.
📘 EBIT
📈 Was ist das?
EBIT steht für „Earnings Before Interest and Taxes“ – also Gewinn vor Zinsen und Steuern. Es zeigt das operative Ergebnis eines Unternehmens nach Abschreibungen, aber vor Finanzierungs- und Steueraufwand.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBIT ist eine zentrale Kennzahl zur Beurteilung der Profitabilität aus dem Kerngeschäft – unabhängig von Kapitalstruktur oder Steuersystem.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes EBIT deutet auf ein profitables Kerngeschäft hin – vor Zinslasten oder steuerlichen Effekten.
- Es erlaubt objektivere Vergleiche zwischen Unternehmen mit unterschiedlicher Finanzierung.
- Im Vergleich mit EBITDA zeigt EBIT bereits den Einfluss von Abschreibungen auf das operative Ergebnis.
📘 Nettogewinn
📈 Was ist das?
Der Nettogewinn ist der verbleibende Jahresüberschuss (oder -fehlbetrag) eines Unternehmens – nach Abzug aller Kosten, Steuern, Zinsen und Abschreibungen
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Nettogewinn ist die zentrale Erfolgskennzahl – er zeigt, wie profitabel ein Unternehmen nach allen Kosten tatsächlich arbeitet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein steigender Nettogewinn zeigt, dass das Unternehmen effizient wirtschaftet – trotz aller Kosten.
- Die Entwicklung des Gewinns beeinflusst z. B. direkt das KGV und weitere Kennzahlen.
- Im Zeitverlauf lässt sich ablesen, wie stabil und profitabel ein Geschäftsmodell wirklich ist.
📘 Free Cashflow (FCF) | ex SBC
📈 Was ist das?
Der Free Cashflow gibt an, wie viel Bargeld tatsächlich übrig bleibt, nachdem ein Unternehmen seine Betriebsausgaben und Investitionsausgaben gedeckt hat. Der FCF ex SBC zieht zusätzlich die aktienbasierte Vergütung ab, um den Cashflow um den Effekt der nicht zahlungswirksamen SBC zu bereinigen.
🧮 Wie wird es berechnet?
Free Cashflow ex SBC = Operativer Cashflow − SBC − Investitionen in Sachanlagen (CAPEX)
🏛️ Wofür ist es wichtig?
Der FCF spiegelt die tatsächliche Finanzkraft eines Unternehmens wider – unabhängig von den bilanziellen Gewinnen. Er zeigt, wie viel Spielraum ein Unternehmen für Dividenden, Aktienrückkäufe oder den Schuldenabbau hat. Der FCF ex SBC zieht zusätzlich die aktienbasierte Vergütung ab und zeigt, wie hoch die Cash-Generierung nach Abzug der SBC ausfällt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow bedeutet, dass ein Unternehmen echte Finanzkraft besitzt – unabhängig vom bilanzierten Gewinn.
- Er ist oft die solideste Grundlage für nachhaltige Dividenden und Aktienrückkäufe.
- Sinkender FCF kann ein Warnsignal sein – auch wenn der Gewinn stabil aussieht.
📘 Umsatzwachstum
📈 Was ist das?
Das Umsatzwachstum zeigt, wie stark sich die Erlöse eines Unternehmens im Vergleich zum Vorjahr verändert haben – tatsächlich (TTM) und auf Prognosebasis (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (Umsatz erwartet ÷ Umsatz Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein wachsender Umsatz ist ein zentrales Signal für steigende Nachfrage, Geschäftsausweitung und Marktanteilsgewinne – besonders bei Wachstumsunternehmen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachstum ist der Motor langfristiger Wertsteigerung – besonders bei Technologie- und Wachstumsaktien.
- Wichtig ist nicht nur das aktuelle Wachstum, sondern auch dessen Nachhaltigkeit.
- Prognosen zeigen, ob Analysten weiteres Potenzial erwarten – oder eine Verlangsamung.
📘 EBITDA-Wachstum
📈 Was ist das?
Das EBITDA-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens vor Zinsen, Steuern und Abschreibungen im Vergleich zum Vorjahr gestiegen oder gesunken ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBITDA ÷ EBITDA Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein steigendes EBITDA ist ein Zeichen für verbesserte operative Ertragskraft – unabhängig von Finanzierungsstruktur oder Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Starkes EBITDA-Wachstum signalisiert operative Effizienz und Skalierung – besonders relevant in Wachstumsphasen.
- EBITDA-Wachstum ist ein Frühindikator für Margen- und Gewinnentwicklung – sollte aber stets im Zusammenhang mit Umsatz und EBIT betrachtet werden.
📘 EBIT Wachstum
📈 Was ist das?
Das EBIT-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens (nach Abschreibungen, aber vor Zinsen und Steuern) im Vergleich zum Vorjahr gewachsen ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBIT ÷ EBIT Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Das EBIT-Wachstum ist ein direkter Indikator für die wirtschaftliche Entwicklung des operativen Geschäfts – unter Berücksichtigung der Kapitalintensität (Abschreibungen).
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Steigendes EBIT signalisiert wachsende operative Rentabilität – auch unter Berücksichtigung von Abschreibungen.
- Das EBIT-Wachstum ist ein wichtiges Maß zur Beurteilung von Geschäftsmodellen mit hohen Investitionskosten.
- Im Zusammenspiel mit Umsatz- und EBITDA-Wachstum ergibt sich ein umfassendes Bild zur operativen Entwicklung.
📘 Nettogewinn-Wachstum
📈 Was ist das?
Das Nettogewinn-Wachstum zeigt, wie stark der Jahresüberschuss eines Unternehmens gegenüber dem Vorjahr gestiegen oder gesunken ist – sowohl tatsächlich (TTM) als auch auf Basis von Prognosen (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (erwarteter Nettogewinn ÷ Nettogewinn Vorjahr − 1) × 100
Der erwartete Wert basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Der Gewinn ist die entscheidende Ergebnisgröße für ein Unternehmen. Ein wachsender Nettogewinn deutet auf steigende Effizienz, stabile Kostenkontrolle und nachhaltige Ertragskraft hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachsender Nettogewinn stärkt die Bewertung, Dividendenfähigkeit und Kursfantasie.
- Stagnierender oder rückläufiger Gewinn trotz Umsatzwachstum kann auf Margendruck hinweisen.
📘 Free Cashflow-Wachstum
📈 Was ist das?
Das Free-Cashflow-Wachstum zeigt, wie sich der freie Mittelzufluss eines Unternehmens im Vergleich zum Vorjahr verändert hat – also der Betrag, der nach allen operativen Ausgaben und Investitionen übrig bleibt.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Free Cashflow ist der echte, verfügbare Geldzufluss. Wachstum in diesem Bereich ist ein Zeichen für finanzielle Stärke und steigende Flexibilität bei Dividenden, Rückkäufen oder Investitionen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Sinkender Free Cashflow kann auf steigende Investitionen, höhere Kosten oder stagnierende operative Erträge hindeuten.
- Besonders bei Dividendenwerten ist das FCF-Wachstum wichtig – denn Dividenden werden letztlich aus dem verfügbaren Cash gezahlt.
- Ein negativer Trend sollte genauer analysiert werden – er ist nicht zwangsläufig schlecht, aber potenziell ein Warnsignal.
📘 Bruttomarge
📈 Was ist das?
Die Bruttomarge zeigt, wie viel vom Umsatz nach Abzug der direkten Herstellungskosten (Material, Produktion) als Bruttogewinn übrig bleibt – also der „Rohgewinn“ eines Unternehmens.
🧮 Wie wird es berechnet?
Auch: Bruttomarge = Bruttogewinn ÷ Umsatz × 100
🏛️ Wofür ist es wichtig?
Die Bruttomarge gibt Aufschluss über die Profitabilität eines Produkts oder Geschäftsmodells vor Fixkosten, Steuern und Zinsen. Sie zeigt, wie effizient ein Unternehmen produzieren oder einkaufen kann.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Bruttomarge deutet auf starke Preissetzungsmacht und effiziente Herstellung hin.
- Sinkende Bruttomargen können auf Kostensteigerungen oder Preisdruck hindeuten.
- Besonders im Vergleich zu Wettbewerbern liefert die Bruttomarge wertvolle Einblicke in die Geschäftsqualität.
📘 EBITDA-Marge
📈 Was ist das?
Die EBITDA-Marge zeigt, wie viel vom Umsatz als operativer Gewinn vor Zinsen, Steuern und Abschreibungen (EBITDA) übrig bleibt. Sie misst die operative Effizienz – ohne Verzerrungen durch Finanzierung oder Buchwerte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBITDA-Marge hilft zu verstehen, wie viel operativer Gewinn ein Unternehmen aus jedem Euro Umsatz erzielt – unabhängig von Kapitalstruktur oder steuerlichem Umfeld.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBITDA-Marge zeigt starke operative Ertragskraft – unabhängig von Bilanzierungseffekten.
- Die Marge ermöglicht gute Vergleiche zwischen Unternehmen und Branchen.
- Ein stabiler oder wachsender Wert kann auf effiziente Kostenkontrolle und Skalierbarkeit hindeuten.
📘 EBIT-Marge
📈 Was ist das?
Die EBIT-Marge zeigt, wie viel Prozent des Umsatzes als operativer Gewinn nach Abschreibungen, aber vor Zinsen und Steuern übrig bleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBIT-Marge misst die operative Ertragskraft eines Unternehmens unter Berücksichtigung der Kapitalintensität (z. B. Maschinen, Anlagen). Sie eignet sich gut zum Vergleich von Geschäftsmodellen mit unterschiedlich hohen Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBIT-Marge zeigt, dass ein Unternehmen auch nach Abschreibungen effizient arbeitet.
- Sie ist besonders relevant in kapitalintensiven Branchen.
- Langfristig stabile oder steigende Margen sind ein Zeichen wirtschaftlicher Stärke und Preissetzungsmacht.
📘 Nettomarge
📈 Was ist das?
Die Nettomarge zeigt, wie viel vom Umsatz am Ende als „Reingewinn“ übrig bleibt – also nach Abzug aller Kosten, Zinsen, Steuern und Abschreibungen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Nettomarge gibt an, wie effizient ein Unternehmen über alle Stufen hinweg wirtschaftet. Sie zeigt, wie viel Gewinn tatsächlich je Euro Umsatz übrig bleibt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Nettomarge zeigt, dass ein Unternehmen nicht nur operativ stark ist, sondern auch seine Finanzierung und Steuerbelastung im Griff hat.
- Vergleiche mit Wettbewerbern geben Einblicke in die wirtschaftliche Qualität.
- Sinkende Nettomargen trotz Umsatzwachstum können ein Warnsignal sein – etwa für steigende Kosten oder sinkende Effizienz.
📘 Free-Cashflow-Marge | ex SBC
📈 Was ist das?
Die Free-Cashflow-Marge zeigt, wie viel Free Cashflow ein Unternehmen im Verhältnis zu seinem Umsatz erwirtschaftet. Der Free Cashflow entspricht vereinfacht dem operativen Cashflow abzüglich der Investitionsausgaben. Die Free-Cashflow-Marge ex SBC berücksichtigt zusätzlich aktienbasierte Vergütungen (Stock-Based Compensation, SBC). SBC verursacht zwar keinen direkten Cash-Abfluss, kann bestehende Aktionäre jedoch durch die Ausgabe zusätzlicher Aktien verwässern. Daher wird SBC bei dieser Kennzahl vom Free Cashflow abgezogen.
🧮 Wie wird es berechnet?
Free-Cashflow-Marge ex SBC = (Free Cashflow − SBC) ÷ Umsatz × 100
🏛️ Wofür ist es wichtig?
Die Free-Cashflow-Marge zeigt, wie effizient ein Unternehmen seinen Umsatz in Free Cashflow umwandelt. Ein hoher Free Cashflow kann dem Unternehmen finanziellen Spielraum für Dividenden, Aktienrückkäufe, Schuldentilgung oder weitere Investitionen geben. Die Variante ex SBC berücksichtigt zusätzlich die wirtschaftliche Belastung durch aktienbasierte Vergütungen und ermöglicht dadurch eine konservativere Betrachtung der Cash-Generierung aus Sicht der Aktionäre.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Free-Cashflow-Marge zeigt, dass ein Unternehmen einen hohen Anteil seines Umsatzes in Free Cashflow umwandelt.
- Das kann dem Unternehmen mehr finanziellen Spielraum für Dividenden, Aktienrückkäufe, Schuldentilgung oder Investitionen geben.
- Die Free-Cashflow-Marge ex SBC berücksichtigt zusätzlich die mögliche Verwässerung durch aktienbasierte Vergütungen.
- Besonders aussagekräftig ist die Entwicklung über mehrere Jahre. Sinkende Werte können beispielsweise auf höhere Investitionen, Veränderungen im Working Capital oder eine schwächere operative Entwicklung zurückzuführen sein.
📘 Eigenkapitalquote
📈 Was ist das?
Die Eigenkapitalquote zeigt, wie hoch der Anteil des Eigenkapitals an der Bilanzsumme eines Unternehmens ist – also wie stark es sich aus eigenen Mitteln finanziert.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Eine hohe Eigenkapitalquote steht für finanzielle Stabilität, Krisenfestigkeit und gute Bonität. Sie ist besonders relevant bei der Beurteilung der Verschuldung.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalquote signalisiert finanzielle Stabilität – besonders in Krisenzeiten.
- Ein niedriger Wert kann auf ein höheres Risiko oder eine aggressive Verschuldung hinweisen.
- Wichtig: Die Eigenkapitalquote sollte immer gemeinsam mit der Eigenkapitalrendite betrachtet werden. Nur so lässt sich beurteilen, ob ein Unternehmen nicht nur solide, sondern auch effizient wirtschaftet.
📘 Eigenkapitalrendite (ROE)
📈 Was ist das?
Die Eigenkapitalrendite zeigt, wie effizient ein Unternehmen mit dem Kapital seiner Aktionäre arbeitet – also wie viel Gewinn es pro Euro Eigenkapital erwirtschaftet.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Eigenkapitalrendite ist eine zentrale Rentabilitätskennzahl. Sie hilft Anlegern zu erkennen, ob das Unternehmen eine attraktive Verzinsung auf das eingesetzte Eigenkapital erwirtschaftet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalrendite spricht für ein starkes, effizientes Geschäftsmodell.
- Besonders interessant ist sie bei kapitalintensiven Firmen oder solchen mit hoher Eigenkapitalquote.
- Wichtig: Ein sehr hoher ROE kann auch auf hohe Schulden hinweisen – daher sollte sie immer im Kontext mit der Eigenkapitalquote betrachtet werden.
📘 Return on Capital Employed (ROCE)
📈 Was ist das?
ROCE misst die Gesamtrentabilität eines Unternehmens – also wie effizient es das eingesetzte Kapital (Eigen- und Fremdkapital) zur Gewinnerzielung nutzt.
🧮 Wie wird es berechnet?
Das eingesetzte Kapital ist das gesamte betriebsnotwendige Kapital, unabhängig von der Finanzierungsquelle.
🏛️ Wofür ist es wichtig?
ROCE eignet sich besonders gut für den Vergleich unterschiedlich finanzierter Unternehmen. Es zeigt, wie effektiv ein Unternehmen Kapital investiert – unabhängig von der Kapitalstruktur.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROCE zeigt, dass ein Unternehmen sein Kapital effizient einsetzt – unabhängig davon, ob es durch Eigen- oder Fremdkapital finanziert ist.
- Je höher der ROCE im Vergleich zu ähnlichen Unternehmen, desto mehr Wert schafft das Unternehmen mit seinem investierten Kapital.
- Besonders wichtig ist der ROCE bei Firmen mit hohen Investitionen – z. B. in Industrie, Energie oder Infrastruktur.
📘 Return on Invested Capital (ROIC)
📈 Was ist das?
ROIC zeigt, wie effizient ein Unternehmen das Kapital investiert, das langfristig im operativen Geschäft gebunden ist – unabhängig davon, ob es aus Eigen- oder Fremdkapital stammt.
🧮 Wie wird es berechnet?
- NOPAT = „Net Operating Profit After Taxes“
- Investiertes Kapital = operatives Vermögen abzüglich nicht-verzinster Schulden
🏛️ Wofür ist es wichtig?
ROIC ist eine der präzisesten Kennzahlen zur Bewertung der Kapitalrendite – besonders im Vergleich zur Eigenkapitalrendite, weil es Verzerrungen durch Schulden vermeidet. Er zeigt, ob ein Unternehmen Mehrwert für alle Kapitalgeber schafft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROIC zeigt, wie gut ein Unternehmen mit dem tatsächlich investierten (betriebsnotwendigen) Kapital wirtschaftet.
- Im Unterschied zu ROCE wird nur Kapital betrachtet, das wirklich zur Finanzierung operativer Aktivitäten dient – und verzinst werden muss.
- Besonders hilfreich, um die Kapitalrendite von Unternehmen mit viel „überschüssigem“ Kapital oder zinsfreien Verbindlichkeiten realistisch zu vergleichen.
📘 Verschuldungsgrad (Leverage Ratio)
📈 Was ist das?
Der Verschuldungsgrad zeigt, wie stark ein Unternehmen durch verzinsliche Schulden (z. B. Kredite und Anleihen) im Verhältnis zum Eigenkapital finanziert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Kennzahl hilft, das finanzielle Risiko und die Abhängigkeit von Fremdkapital zu beurteilen. Ein hoher Verschuldungsgrad kann die Eigenkapitalrendite steigern – birgt aber auch erhöhte Risiken bei Zinsanstiegen oder Liquiditätsengpässen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Verschuldungsgrad steht für finanzielle Stabilität und Unabhängigkeit.
- Ein hoher Wert kann auf erhöhte Risiken hinweisen – insbesondere bei schwankenden Zinsen oder konjunkturellen Schwächen.
- Wichtig: Immer im Kontext zur Branche und Kapitalintensität bewerten.
📘 SBC | in % Umsatz
📈 Was ist das?
SBC (Stock-Based Compensation) bezeichnet die aktienbasierte Vergütung, die ein Unternehmen seinen Mitarbeitern und Führungskräften gewährt. Der Prozentanteil zeigt, wie hoch die SBC im Verhältnis zum Umsatz ist.
🧮 Wie wird es berechnet?
SBC in % Umsatz = (SBC ÷ Umsatz) × 100
🏛️ Wofür ist es wichtig?
Aktienbasierte Vergütung ist für Aktionäre ein realer Kostenfaktor. Sie erhöht die Aktienanzahl und verwässert damit die bestehenden Anteile. Der Anteil am Umsatz zeigt, wie stark ein Unternehmen auf dieses Mittel setzt und wie viel der Wertschöpfung an Mitarbeiter statt an Aktionäre fließt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Wert ist grundsätzlich positiv: Die aktienbasierte Vergütung fällt im Verhältnis zum Umsatz gering aus.
- Ein hoher Wert kann dagegen auf eine stärkere Abhängigkeit von aktienbasierter Vergütung und ein höheres potenzielles Verwässerungsrisiko hindeuten. Entscheidend ist dabei auch, ob das Unternehmen die Verwässerung durch Aktienrückkäufe ausgleicht.
📘 SBC in % FCF
📈 Was ist das?
SBC (Stock-Based Compensation) bezeichnet die aktienbasierte Vergütung, die ein Unternehmen seinen Mitarbeitern und Führungskräften gewährt. Der Prozentanteil zeigt, wie hoch die SBC im Verhältnis zum Free Cashflow (FCF) ist.
🧮 Wie wird es berechnet?
SBC in % FCF = (SBC ÷ Free Cashflow) × 100
🏛️ Wofür ist es wichtig?
Aktienbasierte Vergütung ist für Aktionäre ein realer Kostenfaktor. Sie erhöht die Aktienanzahl und verwässert damit die bestehenden Anteile. Der Anteil am freien Cashflow zeigt, wie groß die SBC im Verhältnis zur vom Unternehmen erwirtschafteten Cash-Generierung ist. Da SBC nicht zahlungswirksam ist, wird sie bei der Berechnung des FCF typischerweise nicht als Cash-Abfluss berücksichtigt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Wert ist hier meist günstig. Die aktienbasierte Vergütung fällt im Verhältnis zur Cash-Erzeugung gering aus.
- Ein hoher Wert bedeutet, dass ein großer Teil des ausgewiesenen freien Cashflows durch nicht zahlungswirksame SBC gestützt wird.
- Je höher der Wert, desto stärker kann die SBC die tatsächliche wirtschaftliche Belastung für Aktionäre widerspiegeln.
📘 SBC-Wachstum 1J
📈 Was ist das?
Das SBC-Wachstum 1J zeigt, wie stark sich die aktienbasierte Vergütung (Stock-Based Compensation) eines Unternehmens im Vergleich zum Vorjahr verändert hat.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das SBC-Wachstum zeigt, ob die aktienbasierte Vergütung für Aktionäre zunehmend oder abnehmend relevant wird. Steigt die SBC deutlich, kann dadurch langfristig auch die Verwässerung der Aktionäre zunehmen. Gleichzeitig handelt es sich um einen nicht zahlungswirksamen Aufwand, der in der Gewinn- und Verlustrechnung das Ergebnis mindert, in der Kapitalflussrechnung jedoch wieder hinzugerechnet wird.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher positiver Wert ist meistens negativ, denn steigende SBC kann die Belastung für Aktionäre erhöhen, insbesondere durch mögliche Verwässerung.
- Entscheidend ist, ob die Entwicklung der SBC langfristig nachhaltig bleibt. Ein gewisses Maß an SBC ist bei vielen Wachstums- und Technologieunternehmen üblich.
📘 Aktienanzahl-Wachstum 1J
📈 Was ist das?
Das Wachstum der Aktienanzahl zeigt, wie stark sich die Zahl der ausstehenden Aktien innerhalb eines Jahres verändert hat.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Aktienanzahl bestimmt, auf wie viele Anteile sich Gewinn und Vermögen des Unternehmens verteilen. Sinkt die Anzahl der Aktien, steigt der relative Anteil bestehender Aktionäre. Steigt sie, werden bestehende Aktionäre verwässert. Die Kennzahl macht damit Verwässerung und Aktienrückkäufe direkt sichtbar.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein negativer Wert ist meist positiv, da die Zahl der ausstehenden Aktien zurückgeht.
- Ein positiver Wert deutet auf eine Verwässerung bestehender Aktionäre hin.
- Ein sinkender Wert ist nicht automatisch positiv: Entscheidend ist auch, zu welchem Preis und wie die Rückkäufe finanziert werden.
📘 Shareholder Yield
📈 Was ist das?
Der Shareholder Yield zeigt, wie viel Wert ein Unternehmen im Verhältnis zu seiner Marktkapitalisierung durch Dividenden, Aktienrückkäufe und Schuldenabbau für seine Aktionäre schafft. Damit geht die Kennzahl über die klassische Dividendenrendite hinaus.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Dividendenrendite allein zeigt nur einen Teil davon, wie ein Unternehmen sein Kapital zugunsten der Aktionäre einsetzt. Neben Dividenden können auch Aktienrückkäufe den Anteil bestehender Aktionäre am Unternehmen erhöhen. Ein Abbau der Verschuldung stärkt zusätzlich die finanzielle Position des Unternehmens. Der Shareholder Yield fasst diese drei Komponenten in einer Kennzahl zusammen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein höherer Wert bedeutet mehr Kapitalrückgabe bzw. einen stärkeren Schuldenabbau zugunsten der Aktionäre.
- Die Zusammensetzung ist wichtig: Dividenden, Rückkäufe und Schuldenabbau haben unterschiedliche Auswirkungen.
- Rückkäufe schaffen nur dann Wert, wenn die Aktien zu attraktiven Preisen zurückgekauft werden.
- Entscheidend ist auch, ob die Kapitalrückgaben und der Schuldenabbau nachhaltig finanziert werden.
📘 Ergebnis je Aktie (EPS)
📈 Was ist das?
Das Ergebnis je Aktie (EPS) zeigt, wie viel Gewinn auf eine einzelne Aktie entfällt – und ist eine der wichtigsten Kennzahlen zur Bewertung von Unternehmen.
🧮 Wie wird es berechnet?
Die verwässerte Aktienanzahl berücksichtigt auch potenzielle neue Aktien, etwa durch Optionen, Wandelanleihen oder andere Umtauschrechte.
🏛️ Wofür ist es wichtig?
EPS bildet die Basis für viele Bewertungskennzahlen wie KGV, PEG oder Payout Ratio. Es macht den Gewinn für Aktionäre vergleichbar – unabhängig von der Unternehmensgröße.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- EPS hilft, die Profitabilität pro Aktie zu erfassen – und ist besonders wichtig im Zeitvergleich oder im Vergleich mit Analystenschätzungen.
- Steigendes EPS kann ein Zeichen für stabiles Wachstum oder Aktienrückkäufe sein.
- Wichtig: Verwende verwässertes EPS für realistische Bewertungen – besonders bei stark aktienbasierten Vergütungssystemen.
📘 Free Cashflow je Aktie (FCF je Aktie)
📈 Was ist das?
Der Free Cashflow je Aktie zeigt, wie viel freier Mittelzufluss einem Unternehmen pro Aktie zur Verfügung steht – nach Investitionen, aber vor Dividenden oder Schuldentilgung.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der FCF je Aktie zeigt, wie viel liquide Mittel pro Aktie tatsächlich im Unternehmen verbleiben – wichtig für Dividenden, Aktienrückkäufe oder Schuldentilgung. Im Gegensatz zum Gewinn ist er schwerer manipulierbar und daher besonders aussagekräftig.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow je Aktie ist ein Zeichen für hohe finanzielle Flexibilität.
- Er zeigt, wie viel Kapital ein Unternehmen effektiv einsetzen oder ausschütten kann.
- Besonders relevant für dividendenstarke Unternehmen oder solche mit starker Kapitalrendite.
📘 Short Interest
📈 Was ist das?
Short Interest zeigt, wie viele Aktien eines Unternehmens aktuell leerverkauft wurden – also von Investoren geliehen und verkauft, in der Erwartung fallender Kurse.
🧮 Wie wird es berechnet?
Der Wert zeigt den Anteil der Aktien, der aktuell auf fallende Kurse spekuliert wird.
🏛️ Wofür ist es wichtig?
Short Interest dient als Stimmungsindikator: Ein hoher Wert deutet auf Skepsis oder negative Erwartungen gegenüber dem Unternehmen hin – kann aber auch zu einem „Short Squeeze“ führen, wenn der Kurs plötzlich steigt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Short Interest deutet auf Vertrauen in das Unternehmen hin.
- Ein hoher Wert kann ein Warnsignal sein – oder eine Chance, wenn sich die Stimmung dreht.
- Besonders spannend in volatilen Märkten oder vor wichtigen Quartalszahlen.
📘 Employees
📈 Was ist das?
Die Mitarbeiteranzahl zeigt, wie viele Personen ein Unternehmen weltweit beschäftigt – ein Indikator für Größe, Struktur und Geschäftsmodell.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft bei der Einschätzung von Skaleneffekten, Effizienz und Personalkosten. Zusammen mit Umsatz und Gewinn lassen sich Kennzahlen wie Produktivität je Mitarbeiter ableiten.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Viele Mitarbeiter bedeuten große operative Komplexität – aber auch hohes Umsatzpotenzial.
- Produktivität je Mitarbeiter ist ein wichtiger Indikator für Effizienz.
- Besonders spannend bei stark wachsenden Tech- oder Industrieunternehmen.
📘 Umsatz je Mitarbeiter
📈 Was ist das?
Der Umsatz je Mitarbeiter zeigt, wie viel Erlös ein Unternehmen durchschnittlich pro Beschäftigtem erwirtschaftet – eine Kennzahl für Effizienz und Produktivität.
🧮 Wie wird es berechnet?
Die Mitarbeiterzahl stammt in der Regel aus dem letzten verfügbaren Jahresbericht.
🏛️ Wofür ist es wichtig?
Diese Kennzahl hilft, Geschäftsmodelle zu vergleichen – insbesondere zwischen arbeitsintensiven und technologiegetriebenen Unternehmen. Ein hoher Wert deutet auf Automatisierung, Effizienz oder hohen Wertschöpfungsanteil hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Umsatz je Mitarbeiter spricht für ein skalierbares und margenstarkes Geschäftsmodell.
- Ein niedriger Wert kann auf arbeitsintensive Prozesse oder geringere Wertschöpfung hinweisen.
- Besonders hilfreich beim Vergleich von Tech- vs. Industrieunternehmen.
NetApp Aktie Analyse
Analystenmeinungen
28 Analysten haben eine NetApp Prognose abgegeben:
Analystenmeinungen
28 Analysten haben eine NetApp Prognose abgegeben:
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NetApp — Citi’s 2026 Global TMT Conference
1. Question Answer
Good afternoon, everyone. Asiya Merchant. Day 1 of Citi's conference, just after lunch, midafternoon. Actually, there's been a couple of sessions after lunch. But the afternoon of day 1 Citi's tech conference. Asiya Merchant here. I lead the tech sector on the hardware and tech supply chain. Really happy here to have NetApp's CFO, with Wissam Jabre as well as IR, VP of IR, Kris Newton here. We have a bunch of questions. We're going to be doing this fireside. If you have any questions at the end, we're going to leave a few minutes here for investors to ask questions, please do raise your hand so we can bring the mic to you. All right. Well, thank you for coming. I'm going to first give it over to Kris. She has a few comments.
All right. Thanks for having us. Today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in our most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. We disclaim any obligation to update information in any forward-looking statement for any reason.
All right. Well, Wissam, Kris, you guys just reported earnings. It was not even a week ago, right? And you took your -- you had very strong results for fiscal 1Q coming out and then you did raise your whole fiscal year outlook as well, almost 2x, right? I think one of the questions that investors here were asking and have been asking is something I've been asking all my companies, especially on the enterprise OEM side of things, like what gives you confidence that this is not -- this is durable, right? I mean you still have three quarters to go, and it's not just customers double ordering, you guys have backlog demand outlooks, like it's not just customers double ordering and trying to get a secure spot in place given the constraints that are out there.
Thanks, Asiya. First, happy to be here. Thank you for having us. Look, we had a stellar start to the year, as you mentioned, we reported last week. And when it comes to Q1, we saw some really good broad-based strength in demand driven by AI adoption and infrastructure modernization. There's also many ways that we typically monitor our business. We look at pipeline, we look at orders, we look at backlog and we monitor it that way. And so far, we haven't seen anything out of the ordinary. And so we do think that -- we do see an underlying strength in demand that basically also gave us enough confidence to increase the guidance for the fiscal year.
As you noted, we basically increased the guidance for fiscal year '27, doubling roughly the growth rate year-on-year relative to where the guidance was 90 days ago, and that also goes to EPS more than doubling that. And so there's other -- the last point I would say in terms of our business, we don't have -- our business goes directly to sort of -- it's linked to end customer demand. And so we don't -- there is no stocking the channel for this type of dynamics that works in it.
Okay. And then while we're on the topic of demand, maybe just because you're pretty well exposed, you have exposure to commercial, of course, enterprise, also government. Maybe if you can talk a little bit about demand? Was it a pretty broad-based that was underpinning your revenue outlook, was it pretty broad-based? And then you also have first-party services on cloud as well.
Yes. So we -- in Q1, we experienced broad-based demand. We saw growth across various geographic regions, and we saw growth across the various types of customers and across types -- various types of industries. And when it comes to our public cloud business, which is where really the three top hyperscalers are our customers, and they offer our software as a native storage software solution. We've also experienced some really nice growth. We had -- we reported around 28%. But then when we adjust to -- for the extra week that we had in Q1, it was around 19%. And so the growth was fairly broad-based.
Okay. And then given that supply -- you guys have to have supply in order to underpin your demand outlook. I think at the start of the year, a lot of questions were around supply, do the OEMs have the supply in order to underpin the demand outlook here, you guys are doubling your demand outlook. So what's changed on the supply side? Have you signed LTAs that gives you access to supply? Just help us on the supply side.
Yes, we've always worked very closely with our suppliers on not only understanding what the supply situation is, but also sharing with them what our outlook looks like. And so that sort of has been our mode of operation for quite some time. Where we are now, we basically have -- I mean, at this time, we have -- we feel comfortable about the supply we have to be able to deliver the outlook we guided. We have different types of arrangements with different types of suppliers. In some cases, we have LTAs, in others, we basically have agreed upon sort of commitments and so on, but we feel comfortable from a supply perspective at this time to be able to deliver our outlook.
Okay. And outside of supply, Wissam, are there things? I mean you have a range, right, when you provide the outlook as well, both for the quarter and for the year. Like what would it take for -- what are -- outside of supply, are there other gating factors that we should think or other factors that could cause you to upside on that side? And maybe we can also talk about the risks maybe towards the lower end of your guide then?
Yes. I mean when you look at the guide, we basically take into account all the information we have at the time when we build our outlook on which the guidance is based. And so we're one quarter in the year, and so we'll wait until the end of this quarter, and we'll be able to provide a better update for the rest of the year.
Okay. And what about pricing? Because I know people often do the P times Q. I know I bugged Kris during the quarter to talk about this, P times Q, when people look at the bids that you're shipping, but of course, pricing has gone up quite meaningfully for -- not just for yourself, for your entire OEM space. So how much is pricing factored into that outlook? I mean how -- and if we do continue to see uptick in pricing, is that upside to your guide? Is that how we should think about it?
So it's pretty normal and understandable and inflationary environment for pricing to be a factor. But what's most important is that what's underlying the growth and the outlook is more of a strength in the business driven by what I mentioned earlier with respect to AI adoption in the enterprise as well as infrastructure modernization.
Okay. And then your growth rate, though, obviously, you had a pretty meaningful growth in fiscal 1Q. You're guiding for strength in fiscal 2Q. And then there was the extra week in 1Q, I get that. But then your -- the implied guide at least was a little bit of deceleration here as we get into the back half of your fiscal year. What's underpinning that? Is it just you're just being very prudent, given you're just one quarter into the fiscal year? Are there other factors that we should think about, maybe supply, et cetera, that's kind of baked into a deceleration in growth rates in the back half?
Yes. So when you look at the guidance, it is important to note that the guidance for the full year relative to 90 days ago is higher and the guidance for the second half also is higher than what we had 90 days ago. So when we looked at the full year guidance, we basically updated the guidance in total and both the first and the second half year sort of are incrementally better than what we thought they would be 90 days ago. Now when you look at the seasonality of the business and you factor in the extra week in Q1, it looks like roughly the revenue -- at the midpoint, roughly the revenue is split almost 50-50, 50% first half, 50% second half. Now it's slightly -- in fact, it's slightly less than 50%, if you sort of want to go to the first decimal point, but it is, let's call it 50-50, which is not necessarily far from the area -- sort of the split that we've had for multiple years.
Okay. All right. Okay. And then a little bit on margins because, obviously, product gross margins, you talked about component inflation here. They are expected to moderate in 2Q, and I think you said about towards the low 50s, if I'm not mistaken, for the product gross margins. I mean can you talk a little bit about what's -- well, how should investors think about that? I mean components typically are pass-through for you guys. At what point do you see component inflation sort of moderating here maybe even reversing?
So look, we are operating in a tight supply chain environment. So it's too early to sort of make a call on the component pricing. But when it comes to product gross margin, it is the -- what we guided for Q2 and for the rest of the year, so think of Q2 to Q4, it's slightly better product gross margin than we had expected 90 days ago. Now when it comes to the full year gross margin, the number is -- the guide is slightly lower, but that's solely driven by the richer product revenue mix. All the margin lines are either similar to what we thought they would be 90 days ago or better.
Right. Okay. But on the product gross margin side, you are seeing more mix towards flash, right? In general, the product is mixing more towards flash. Your flash revenues are very strong year-on-year. Typically, those associated with higher-margin product margins because there's more software component in there. So just walk us through sort of what -- that puts and takes to product gross margins as you continue to maybe see more demand mixing towards flash, which carry typically higher software components.
Yes. I think your comment is accurate for Q1, Asiya. We did see a higher flash mix in the overall revenue relative to the hybrid flash side. For the forward-looking numbers, we typically don't break it out as such. I mean to the extent it happens, maybe, but it's too early to tell.
We did call out strength in the hybrid flash business, so as we look forward, that could come through. And I wouldn't necessarily assume that the historical kind of relative margin performance of different product classes stand in this current environment.
And then to mitigate the cost headwinds, right? I mean we've talked -- what are additional tools? Some of it just pass-through of pricing. What other tools would you have to mitigate some of the costs?
Yes. So the first one is, as you mentioned, we tend to focus on -- and it's very customary in our space to pass through the component cost inflation, which we've done for now a couple of quarters. We've sort of built also certain agility in the business to enable us to do that in a faster way, meaning sort of the -- whether it's the duration of our quotes, et cetera, to enable us to be -- to react faster in the event we have to -- we are encountering component cost increases, and we have to increase our prices. We also have many other ways to -- where we work with our suppliers. So for most of the commodities we purchase, we have more than one supplier and so that helps us work on securing the supply but in some cases, also it helps a little bit on the cost side.
But in -- from the business itself, when you look at our portfolio, we have a very broad portfolio, so we don't only necessarily carry only all-flash. We have all-flash, we have hybrid flash, we have Keystone and we have the public cloud business. And so we're happy to help our customers solve their problem regardless which service we offer. And so for customers that tend to really want to focus on very high performance, for instance, they may want to choose an all-flash array solution where capacity is probably more important or maybe they're much more cost sensitive and capacity is more important then we're happy to offer a hybrid flash, which is hard disk type based.
For customers who want to sort of -- who have limited budgets and prefer to split their spending over multi-years, we could offer Keystone, which is our Storage-as-a-Service solution. And for customers who are comfortable doing a consumption approach, we're happy to offer our public cloud business. So there are some ways we address it through the supply side, through the cost side. There's other ways we address it also by offering different solutions. And as Kris mentioned, now from a hybrid flash versus all-flash, we don't have much of a differential on the margin side as well.
Okay. All right. Good to know. And then AI wins, I know NetApp often talks about the AI wins per quarter, and people track, that's a KPI that you shared on the call. Fiscal 1Q number showed a little bit of deceleration, but I think the size of these deals are getting larger. Just help investors understand like are you seeing as these AI wins are coming through and we talk about it, even that's one of the focus at this conference as well about enterprise adoption. Are you seeing much more storage being attached to all these AI wins as you're talking to your customers, what kind of storage? Just help us understand what you're seeing as your customers are talking about these AI wins that you're then communicating to the investor base.
Yes. I mean what we disclosed for Q1 was much higher than what Q1 '26 was in terms of the number of AI wins, that's what we disclosed. What we've noticed in Q1 also is that the average size of the deal is now bigger than before, and so for some of the proof-of-concept type of deals that we had, let's say, a year ago, we're starting to see more of a production type of deals now. And that sort of helps explain that larger average size deal. This just basically demonstrates that our customers, once they put -- once they test the product, they're happy. In terms of the AI workloads, they're happy with it and they come back for larger deployments.
Okay. And then when you think about some of your compute vendors or competitors, for example, in the ecosystem, they're talking about very, very strong, a lot of strength in the traditional servers versus CPU-based servers, AI workloads. As you're thinking about storage attach, like you said, it's being reflected in the size of these deals, like are you seeing that inflection where compute and storage may be more closely aligned versus compute, which is obviously, first, we had a lot of GPU spend, now we're seeing a lot of CPU spend. Are you starting to see storage being more and more attached to these agentic AI workloads? How meaningful could it be in the next couple of years?
I mean there is, as I mentioned earlier, certain broad-based strength in demand. And so some of it, I would imagine has to do with some of the CPU server deployment because ultimately, after all these servers are deployed, they will need to have some form of storage attached to them. It's a bit too early to tell the magnitude, but it is -- I would imagine that typically, it would be a tailwind to our business.
Okay. I know you said it's difficult to size it right now, but any -- like when you talk about these deals that you're winning and tracking, like is there any way to carve out how big it could be over the next 2 or 3 years, like in terms of percentage of revenues that have come from just these AI wins?
I mean, look, we know that AI is giving us a tailwind on the top line, right? And the one thing to note is there's the AI sort of workloads, but there's also other types of infrastructure modernization that could be related to or associated with AI workloads that are also happening at the same time since AI could generate other types of applications and infrastructure needs. And so I think over time, the line between AI and non-AI could become blurry like if you think of -- you mentioned 2, 3, 4 years down the road, that could become a little bit of a blurry line.
Right. On the other hand, if you look at sort of the industry -- let's just talk about the broader industry TAM, right? As you think about the AI, whether it's data modernization, whether it's this incremental workloads, is there any way the way you guys think about the TAM? Like how big could enterprise storage become over the next 2 to 3 years as we're starting to see AI workloads now?
I mean it's clear that we're -- at least today, based on what we reported and what we're seeing in the market. It's clear that we're experiencing a certain TAM growth. And so -- it is too early for us to tell where this could be 2 to 3 years from now, but what's clear is that there's certain underlying demand that's driven from the AI adoption and from infrastructure modernization.
Okay. And then just your own competitive dynamics here, like how do you think like you could grow share within this expanding TAM? And where do you feel most comfortable? Is it on the flash side? Is it on the hybrid side? Is it on cloud storage, Keystone, which is Storage-as-a-Service? Where do you feel like you have the biggest opportunity to gain share in a growing TAM?
When we look at our numbers and how we're looking at sort of the next few quarters, they -- basically all parts of the business are doing well. In Q1, for instance, the all-flash array business grew by 47%. And in Q1 also, we saw a small uptick in the hybrid flash revenue year-on-year, which is the second quarter in a row we see that after several quarters of -- like many quarters of decline.
We also saw some nice uptick on the public cloud business, as I mentioned earlier. The business, excluding the extra week, was up 19%, if you sort of dissect that and look at the first party and marketplace within that revenue, it grew at a much faster pace than this. Just for reference, the first party and marketplace portion of the public cloud business last year grew at around 31%, so there's really high growth there. And when you look at the Keystone Storage-as-a-Service, in Q1, we experienced similar types of year-on-year growth as we've seen in Q4. It's still growing rapidly and expanding.
You guys made a couple of acquisitions during the quarter, I think, DataPelago and JetStream. I hope I'm pronouncing that correctly. Just -- I think they're tuck-in acquisitions more than transformational. So just help us understand like what's the reasoning for these acquisitions? How do you think it's going to change? What attracted you to these acquisitions, two in a quarter, is that -- could it be greater looking forward? Like where are you guys focused on in terms of technology acquisitions?
Yes. As you noted, both our tuck-in acquisitions, the technology acquisitions to complement our portfolio. So when you look at DataPelago, DataPelago is basically an extremely high-performance data processing software engine that's capable of processing compute and the CPU and GPU environments for -- while basically keeping the data where it resides. Meaning processing data at the storage layer at a very high speed and high performance, which provides typically lower cost and better performance for the customers.
And when you're able to process data where it resides, it also enhances security and data protection because you don't have to sort of move the data from one place to where the AI -- to sort of other AI systems, basically other compute clusters for AI systems. So that's the DataPelago which is pretty much, think of it as an enhancement to potentially AIDE.
On the JetStream side, JetStream is very much a disaster recovery type of solution for VMware environment. And so that combines well with our public cloud business where we could also be used for disaster recovery as a retention type of storage on the public cloud business. So it gives us basically additional capability for the public cloud business. So both of these are small tuck-ins that are more technology oriented to help us complement our portfolio and basically be more competitive.
Okay. And then on the AI side, I know at the INSIGHTS last year and you have an INSIGHT day coming up again. AFX, AIDE, you talked a lot about that. I mean, just help us understand how is that differentiating you from some of your other competitors, whether the compute and storage vendors who are selling full stack solutions or maybe just the only storage competitors that are out there and especially we also have the neocloud storage providers, whether it's Vast or WEKA. So how does -- where are you with your AFX, AIDE offerings? And how does that differentiate you relatively?
Yes. I mean we have some customers that are in certification phase on AFX. AFX is our disaggregated architecture solution where customers can choose either to focus on performance or on capacity. And when you think of AFX and AIDE, basically, they're part of the NetApp platform, which is really the key differentiator for us because we provide unified solution, which would include things like AI data services and so on for our customers. And so it helps us be more competitive in terms of our portfolio offering as well.
Okay. Let's see, I'm going to just ask if there's any questions here in the audience. If you do, please raise your hand. Public cloud -- sorry, did I miss any? Public cloud grew, you just talked about it, 19% ex the extra week, which is pretty -- and the first party obviously grew much faster than that. That's a pretty nice growth relative to what you guys were experiencing. How sustainable is that? And what should -- what could maybe drive further growth in that? Do you think this 19%, 20% growth is pretty sustainable? What should investors be looking for to see if that growth could accelerate here, especially as we are hearing about overall cloud growing pretty rapidly?
Yes. Look, the public cloud business is a very nice high-growth business for us, and the high teens growth rates are sustainable. This is a business that is very differentiated. We continue to make investments in it and adding capabilities and features to ensure that it stays differentiated and it stays in sort of leadership place where it is. Overall, the first party marketplace is growing at a much faster pace as you noted. And so over time, that will continue to sort of also drive a nice growth as you think of the sort of mix within the public cloud business. So the high-teens percentage is a sustainable number for us.
Okay. And I know you guys are exposed across various hyperscalers for their first party. Was the growth pretty unanimous across or I mean similar across all the other hypers? Or were there ones which were doing a little bit better?
They're all growing at a nice pace. Obviously, they're not all of equal size, but they're all growing at a very nice pace, contributing to that high growth in the business.
Okay. And is there any way to carve out how much AI is contributing to that growth in the public cloud that you're experiencing?
Well, the way to think of our public cloud segment is that really our customers are really the three hyperscalers, so Microsoft, Google and AWS. And then obviously, we serve end customers. We know that there are AI workloads that happen within our public cloud environment. But we don't necessarily -- the visibility isn't as great since obviously, they're our customers' customer. We get quite a bit of visibility, but it's not necessarily as good. But what we know is that there are AI workloads that are basically taking place on that or run on those in that environment.
And have you had to like make investments or change some of those product offerings? And is that how you kind of, I guess, get to some understanding that, okay, this could be AI-driven?
We continue to evolve the product offering. We continue to add capabilities to it and we continue to enable sort of -- and be able to sort of plug into the various AI capabilities that are offered by our partners.
Okay. Public cloud margins, I mean, they have continued to go higher. The past, I think, a target range that was shared at your last investor event. At what point do you consider revisiting that margin framework for your public cloud?
So public cloud margins, to be precise in Q1 were at 86-plus percent. The long-term range for us is 80% to 85%. We've been operating at that level for, I think, three -- actually slightly higher than this for the last three quarters. We're comfortable with the range where it is now. We think there's potentially some upward bias, but we're comfortable with the range that it is now because we want to allow to continue to invest in the business and drive growth. And so that's really why I think at this point, we'll keep the range where it is.
Okay. And the upside for this quarter, is it just a scaling thing as you start to see more growth? Obviously, you're scaling and so you should drive better margins.
Well, the one thing to keep in mind, Asiya, is that in Q1 we had an extra week, so that helped a little bit the margin, but it still would have rounded to 86 anyway.
Okay. Keystone again, grew significantly last year. Where do you think Keystone could be for your business, like over the long term?
So Keystone is another offering from our portfolio where we -- this is our Storage-as-a-Service. It's been growing at a really nice pace. In Q1 it grew at the same pace as we saw more or less in Q4. So really high growth. It has really nice margins. It's accretive to our overall gross margin and operating margins. It is one of those elements of the business that we offer to our customers who are interested in basically doing Storage-as-a-Service. It is by itself, what we focus on with respect to working with our customers is to provide the best solution for them.
And so we don't necessarily push Storage-as-a-Service solution versus an on-prem. We work with the customer to determine what is best for them in terms of what they're trying -- the problem they're trying to solve and what the infrastructure they're putting in place. I expect the business to continue to grow at a nice pace, continue to be as profitable and drive good profit growth for the company.
Is it a totally different set of customers that choose one, like public cloud versus Keystone? Or do you see some customers may be having both, but just different workloads or...
I mean it could be -- yes, we see customers who could have the on-prem, for instance, solution and Keystone is not necessarily a specific type of customer. Sometimes it depends on their workloads. Sometimes it depends on if they have any migration projects. It varies on their requirements. And so this is why what I mentioned earlier, we work with the customer to try to figure out what solution or what the problem they're trying to solve, and we address it in the best way possible for them.
Okay. And Keystone margins, public cloud margins, given -- I mean, obviously, your our public cloud business is bigger. The margin is fairly similar?
I think the public cloud margin has really phenomenal margins. I mean when you get to that sort of 86%.
Okay. All right. Operating income guidance. You guys continue to manage OpEx extremely well. I think now the last few years, you guys have shown that you can manage OpEx at, is it what, half the growth rates versus the revenue? And so how we should think about that going forward given complexity of offerings, AI, obviously, you're making some technology acquisition, how does that kind of overall play into kind of your OpEx guide?
Yes. I mean when you look at our operating margin guide, the latest we shared for the year with the increased guidance on the top line, we also increased the operating margin guidance at the midpoint by around 120 basis points, and so this shows the operating leverage that exists in the business and sort of demonstrates the earnings power there. Our focus is to balance between growth and margin. And so we grow the top line, we grow the gross profit, but also we want to continue to see that operating margin leverage to some extent.
And so when we -- so having said that, we also want to invest in the business. We want to invest in growth. And so our approach is typically not to invest or not to have OpEx grow faster than half of the growth rate of the revenue. And if you sort of look at what -- where we are for the fiscal '27 guide, it sort of gives you a good idea that we're pretty much still living within that framework. But we still want to invest in the growth of the business. We think there's a lot of opportunities for us ahead, especially in AI data solutions. And so that's something we continue to focus on as well as, of course, driving their revenue growth and operating margin.
And so Wissam, as you think about -- I mean, obviously, you guys generate quite a lot of cash. When you're thinking about deploying cash, you have these technology tuck-in acquisitions, you have capital returns, you obviously have to lock in supply to some -- like you're sitting back here, how are you thinking about as -- have my objectives for deploying cash change?
Our capital allocation approach has not changed. We still intend to return up to 100% of our free cash flow to our shareholders, either through dividends and buybacks, that hasn't changed. On the M&A side, you saw us do a couple of tuck-in acquisitions. We're a technology business. We want to make sure that we have a competitive portfolio that's second to none and so we will continue to complement our portfolio as needed with these types of investments.
All right. Any questions here from the audience? With the rising component prices and obviously, it's reflecting through, as you guys are passing through that, what are your customers saying? I know you talked a little bit about you have a full stack offering. You can do anything, you can do it as a service, you can do public cloud, you can do hybrids. But at the end of the day, how are customers sort of adjusting their budgets? And where are they getting the incremental -- given that storage is growing, where are they getting the incremental budgets to support compute spending going up, PC spending going up, storage spending going up? What are you hearing from your customers as they're adjusting their budgets to allow for the higher pricing that's flowing through?
I mean look, customers budget based on their business priorities. And so -- and they also spend based on their budgets. And so in many cases, if they need to reprioritize what they buy, they would adjust it based on what the prices are and what they need to buy. But what's most important is they do budget based on their business priorities. And if we fit within those priorities, obviously, that's great for us. And obviously, we're seeing some of that probably happening over the last quarter for this year, so that's a positive.
All right. As my -- one of my last questions always is what do you think investors are missing about the NetApp story?
Well, look, we've had a stellar start of the year. We had many records in Q1. We did exceed our guidance on all metrics. We did increase the outlook for the fiscal year for both -- actually, for all the revenue as well as operating margin and EPS. We continue to invest in the innovation and maintain that sort of innovative approach to the technology and driving this very strong portfolio.
And later this month, we have INSIGHT, which is our customer conference where we also showcase some of the great innovations that the team at NetApp has developed and is developing, so I encourage you to listen to that. We think we are in a nice period of growth that would help us to continue to drive sustainable growth, sustainable profitability and cash flow and drive value for our shareholders.
Thank you, Kris. Thank you, Wissam. I appreciate it, and I'll see you at INSIGHT.
Thank you for having us.
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NetApp — Citi’s 2026 Global TMT Conference
NetApp signalisiert breite, KI-getriebene Nachfrage, sichert Lieferketten und hebt die Jahresprognose deutlich an.
🎯 Kernbotschaft
- Nachfrage: Breite Nachfrage über Regionen und Branchen, angetrieben von Künstlicher Intelligenz (KI) und Infrastrukturmodernisierung.
- Guidance: Management hat die Prognose für das Geschäftsjahr 2027 (FY27) deutlich erhöht und begründet das mit anhaltender Endkundennachfrage.
- Lieferketten: NetApp meldet ausreichende Versorgung dank langfristiger Absprachen und unterschiedlicher Lieferantenmodelle.
📌 Strategische Highlights
- Produktmix: Starkes Wachstum beim All‑Flash‑Geschäft; Hybrid‑Flash zeigt eine erste Stabilisierung.
- Cloud & SaaS: Public‑Cloud‑Geschäft wuchs exklusive einer zusätzlichen Woche rund 19%; Keystone (Storage‑as‑a‑Service) wächst weiter kräftig.
- Zukäufe: Zwei Tuck‑ins (DataPelago für datennahe Verarbeitung, JetStream für Disaster‑Recovery in VMware) ergänzen KI‑ und Cloud‑Fähigkeiten.
🔍 Neue Informationen
- Versorgungsstatus: NetApp fühlt sich derzeit komfortabel, die erhöhte Jahresprognose zu beliefern; Verträge reichen von LTAs (Langfristige Liefervereinbarungen) bis zu Liefercommitments.
- Margenrahmen: Public‑Cloud‑Bruttomargen lagen in Q1 bei ~86%, Langfristbereich bleibt 80–85%; Produktbruttomarge für Q2 wird um die niedrigen 50er‑Prozent erwartet.
- AI‑Deals: Mehr KI‑Wins; durchschnittliche Dealgrößen steigen, PoCs wandeln sich häufiger in Produktionsprojekte.
❓ Fragen der Analysten
- Nachhaltigkeit: Analysten fragten nach Double‑ordering vs. nachhaltiger Nachfrage; Management betont Endkunden‑getriebene Buchungen, liefert aber keine absolute Quantifizierung.
- Supply‑Risiken: Nachfrage hängt von Komponentenversorgung ab; NetApp nennt LTAs/Commitments, vermeidet aber detaillierte Lieferantenangaben.
- KI‑Grösse: Wie viel Umsatz KI wirklich beiträgt bleibt unklar; Management sieht Tailwind, kann Anteil am TAM (Total Addressable Market) nicht exakt beziffern.
⚡ Bottom Line
- Implikation: Erhöhte Guidance und breite Nachfrage sind positiv für Wachstum und zeigen operativen Hebel; Risiken bleiben bei Komponentenpreisen und bei der genauen Sichtbarkeit, wie stark KI‑Workloads langfristig Umsatz und Margen treiben.
NetApp — Goldman Sachs Communacopia + Technology Conference 2026
1. Question Answer
Hi, everybody. Welcome to the NetApp fireside chat at the Goldman Sachs Communacopia and Technology Conference. I have the privilege of having CEO, George Kurian, here with us today. My name is Kat Murphy. I cover NetApp and IT hardware here at Goldman Sachs. We have about 35 minutes for today's discussion, inclusive of audience Q&A.
Before I begin, I'll read a quick safe harbor. NetApp asked you to read their safe harbor disclosure. Today's discussion may include forward-looking statements regarding NetApp's future performance, which is subject to the risks and uncertainties. Actual results may materially differ from the statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q filed with the SEC and available on their website at netapp.com. NetApp disclaims any obligation to update information in the forward-looking statements for any reason.
So with that, thank you, everyone, for being here. George, thank you for your time. It's a privilege to have you here on stage.
To kick it off, NetApp reported earnings last week where you raised your fiscal 2027 guidance for 17% revenue growth and 22% EPS growth at the midpoint. Before we dig into some more strategic questions here today, can you talk us through a brief recap of the quarter and what gave you confidence this early in the year to raise your full year fiscal '27 guidance? And highlight anything that you think is important for this audience.
Thank you for having me. Thank you for joining us. It was a super strong start to the quarter, to the year. Pretty much every product line, every district, every industry, every country was well ahead of plan. We had record revenue, earnings per share. Billings was in record territory. All-flash array revenue was a record, up 47% year-on-year. Cloud continues to grow in the high teens, adjusted for the extra week. And so we feel really, really positive about the momentum in the business.
Great. One of the central questions investors are looking to understand is how agentic AI adoption may create a TAM uplift for the enterprise storage opportunity, much in the same way we've seen in traditional compute and in networking.
What we are seeing is the broad-based pattern of demand that we're seeing, which gave us confidence to raise the full year, and the outlook provides real confidence in the durability, is this idea that to use AI models effectively, you need robust data infrastructure because the output that these models and agents generate are only as valuable as well-curated, high-quality data.
So we saw wins in our AI-specific configurations that were up materially year-on-year. But we also saw a broad-based kind of upgrade of databases and lakehouses and streaming engines and all of the other associated applications that go alongside AI. And so, broad-based demand from a customer standpoint. And this is driven by the fact that as we have seen customers deploy these AI use cases, they need better and better storage and data infrastructure.
And as a part of that, you've talked in the past about a significant share of AI projects being abandoned because of a lack of AI-ready data or data readiness issues. Can you talk about why a unified platform like ONTAP, in particular, helps address some of those data readiness challenges and how you're assisting your customers in preparing for that broader adoption trend?
Yes. To get -- AI models are essentially probabilistic engines. And to get accurate results from those models, you need to apply them and use your enterprise data against those models. That enterprise data is typically smeared across cloud, across a variety of applications and across a variety of different storage environments and customers. Our view has always been that it's important to unify all of these landscapes so that you can bring different data types, different data applications under one common rubric so that the model gets the best output. And so our long-term thesis that hybrid multi-cloud needs to be unified across site, media, and applications is coming through.
Thank you. You recorded more than 1,100 AI deals in fiscal '26. You talked about 350 more last quarter, at increasing deal sizes as well. As this infrastructure spend evolves from pilots into more full-scale production, how should we think about measuring or quantifying the impact on NetApp's results specifically? And if you could talk to how some of these AI-specific configurations may look from a margin contribution perspective relative to the rest of your product portfolio?
I think, first of all, the size of the AI deals, which are really specifically tied to unique AI configurations that we can track, has -- the number of deals has grown materially, as you noted, year-on-year, and the size of those deals has also grown. We have seen customers who deployed proof of concepts with us a year ago or 6 months ago come back and say, "Yes, the proof of concept worked. I want to expand the footprint."
That being said, the impact of AI in our business is much broader. I think people are upgrading a lot of other storage and applications to work alongside the AI-specific configurations. And so we see the demand picture being really strong across a broad book of business. I think with regard to the margin profile, there's no material difference between our sort of broad-based enterprise business and the AI-specific environments.
To maybe dial into that AI-specific environment and the configurations there, I want to ask about the AFX platform, which you launched last fall. How should we think about the opportunity that the AFX platform goes after and how those types of customers, that you've talked about this being more of a neocloud-based product, have different needs from your core enterprise customer?
Yes. I think we introduced the AFX platform for customers who want the flexibility to gang up different sizes of compute instances with storage in really, really flexible ways. Those are typically large enterprises and some of the neoclouds. We have seen good uptake. They go through a certification process, but we've disclosed on the calls momentum and progress with the AFX platform, which is good. We are going to be announcing even more advancements for the really high end of the neocloud for training and sort of this frontier models use cases coming up at INSIGHT. Super excited about that announcement.
Can you talk about what NetApp's right to win is with this neocloud opportunity? Obviously, have strength and leadership on the enterprise, but what about that translates to the neocloud as well?
Yes. I think 2 or 3 things. I think one is we have proven to have been able to deploy hyperscale-level data management, data infrastructure because we are embedded in all of the big hyperscale providers. So we know how to -- the technology from a scalability, from a provisioning -- ease of provisioning from a cloud-native operating paradigm is super proven. We also have go-to-market models that allows the neoclouds and our sales teams to work together on opportunities where we are more partner than vendor.
And then, of course, as the neoclouds have gone or want to move from just sort of training or what you call stateless, meaning workloads that are very temporal, to more enduring workloads, data management, security, sovereignty, all of the controls we provide as well as hybrid use cases become more important. So our opportunity there is growing, and we see broader engagements from all of them.
Great. More on the sovereignty point. You've talked about your expanded relationship with Google Distributed Cloud to extend the company's reach into sovereign and some of these highly secure environments. As governments and enterprises increasingly prioritize this concept of data sovereignty, what is NetApp's right to win there? Is it different than the neocloud story? Or how can you frame NetApp's opportunity in that customer set?
We have been strong in sovereign for a long time. I think that, for example, 6 of the 8 largest cloud providers in France have NetApp as their infrastructure, right? This is domestic cloud providers. We see the push on sovereign growing around the world because AI is seen as a national security priority in most countries. And so we have been working with both the national cloud providers as well as the hyperscalers to build sovereign environments.
Those sovereign environments have -- our differentiation is that you can take advantage of all of the innovations, for example, in the hyperscalers, all of their advanced AI platforms, but use private data storage and private data management with our solutions. For example, in the Google Distributed Cloud architecture, they're bringing the Google AI stack with NetApp storage to a private disconnected environment in customers. And so we see more and more of those use cases as opportunities for us, not only with Google, but in other cloud providers as well.
Shifting gears here, I want to touch on how NetApp is helping its customers navigate input cost increase. Specifically, how does the breadth of NetApp portfolio across all-flash, hybrid, spinning disk, how does that help your customers navigate these input costs? And how should we think about the demand in this environment of increasing ASPs for some of the non-mission-critical storage projects that your customers are looking to undertake?
Yes. We've always believed that you want to bring your data estate under one management framework and orchestration framework, whether that is media type or whether that's location, your data center, cloud providers' data center, hyperscaler data center, so that it gives you flexibility to navigate these landscapes. We are working with our customers on 2 fronts around the commodity situation. On one front is to give them the tools to optimize the use of high-cost flash for only the part of the data that really requires high-cost flash and to automate movement of colder data out of those flash-based systems into cheaper disk-based configurations. We hinted at the fact that our disk-based systems have started to show growth, and we see strong uptake through the rest of the year as the cost of flash becomes 15 to 20x the cost of disk, right? And so that's one.
And I would tell you what's interesting is that data in an all-flash system, a large part of that data is actually cold. It started out hot, but like a Hollywood movie star, faded over the life of the use of data. And so you want to move it off of that hot system. And so that's giving us competitive position. The second is for compute access, we are working with several clients on hybrid compute landscapes where they want to provision compute in the cloud as a risk mitigation strategy for not having access to supply chain components for their own data centers. And so we're seeing more and more pickup of that as well. Both of those are parts of our solutions.
Can you talk about how consumption models change as well, whether it's the capital purchase or consumption-based models like Keystone, how that has changed in the last 9 months as prices on memory and hard disk has risen significantly?
Keystone has done well. Our performance for Keystone, which is our Storage-as-a-Service business, in Q1 was roughly similar to our results in Q4 and were above our internal targets. I think that we want to give customers the broadest range of procurement choices so that they can use the right tools for the right use case. And for several examples, like, "Hey, I want to stand up a pilot environment. I'm not sure it's going to be a long-standing commitment, but I want to experiment." We suggest Keystone or cloud as a better alternative than paying an upfront CapEx purchase.
I'll have one explicit memory question. But in terms of fiscal 2027 guidance, how should we think about how much of that outlook is supported by NAND and hard disk that NetApp already has under contracts through LTAs versus volumes that might need to be procured at more floating prices in the future? And anything you could share just on pricing assumptions on these components embedded into your full year outlook?
Yes. I think, obviously, when we provide guidance, especially the guidance that had a significant uplift, you want to make sure you have good visibility into demand, which we do, as well as to work with suppliers a priori to ensure that you have access to supply. And we feel good about both sides of that equation.
With regard to the work we do with suppliers, we work with them on a broad range of commercial vehicles, including buying in the open market as well as through long-term agreements to assure access to available supply at competitive cost structures, and they prefer a range of tools that we work with. I think if you look at our balance sheet for the quarter, inventory was up because we want to make sure we have adequate inventory on hand to be able to meet demand. And so -- yes.
Product gross margins performed better than investors were expecting and better than guidance in the most recent quarter. And as we think about the broadening demand that you've talked about across flash, across hybrid, across disk, how should investors think about this balance of mix, pricing actions, and then some of your cost recovery efforts and the impact on the margin profile for your product margins going forward?
Yes. I think ultimately, product gross margins are a balance of kind of having raised prices to meet the increases in costs. We don't always -- we can't match them always one for one and the ability to recover those price increases through discipline and the value that we offer customers. We feel good about our execution in Q1. Obviously, every quarter, you got to go execute and match price with cost. I think if you look at the full year outlook on product gross margins, it's incrementally up every quarter relative to what we had laid out when we guided the full year at the start of the year, which is a reflection both of better visibility into cost as well as more confidence in our ability to recover pricing in the market.
I think with regard to kind of our view of the full year, product gross margins are a component of overall company gross margin. Company gross margin is really determined by the mix of product and service. And I think if you look at the outlook for the year, product is growing much faster than service, which affects the corporate gross margin rate, even though the underlying rates for all of the components are the same as what we thought. And then in the case of product gross margins, better than we thought 90 days ago.
I want to shift gears to the Public Cloud segment. You posted 28% growth in the quarter, 19% when you exclude the extra week, operating at very attractive gross margins, as you mentioned. What is driving that momentum? And why are you confident that the public cloud business can continue to grow at this elevated rate as we look into the back half of fiscal '27?
Yes. I think public cloud has grown in the high teens, low 20s for a long period of time as we have scaled that business. And so we feel good about it. Would I like it to grow a little bit faster? Sure. I think our sales teams know that I'm pushing for faster growth.
I think the picture is driven by 3 trends. I think first is sort of secular growth in the hyperscalers. They're growing at very high rates, and we are a small part of the overall storage market, so we can grow more without any real encumbrance. The second is broader product offerings that allow us to deliver more value to customers as well as the confidence driven by strong net customer retention and expansion numbers. We see really good numbers there.
And then the third is better kind of execution, kind of distribution. We see good returns from investments we're making around go-to-market to expand the range of account types we can penetrate, the range of channel partners we can engage. So super bullish about our cloud business. We are extraordinarily well positioned not only in public cloud, but as they build private environments, right? So in sovereign, we are part of several of the build-outs in Europe in distributed and kind of disconnected cloud. You saw the work that we did with Google, and we are working on others like that. So really been a good strategic bet for the company that gives us a really strong competitive position and growth engine going forward.
On the more offerings point that you mentioned is part of those 3 drivers of public cloud. Can you talk about how AI scaling or enterprises adopting -- increasing their adoption of AI could drive incremental demand in this category in particular? And how do you envision an enterprise using the public cloud and NetApp services through the public cloud to kind of go after this opportunity?
Yes. I think we see that we have made investments and continue to do more innovation work to connect our offerings in the public cloud with the hyperscalers' AI platforms like Bedrock from Amazon or Vertex from Google or Azure Studio from Microsoft. And what we are seeing is AI is truly a hybrid use case, right? Most clients have data in one place and want to use tools in another place. And because we make it so frictionless for them to use those tools, they kind of are putting more and more use cases on NetApp storage.
We saw, for example, in the quarter, innovations that we introduced a couple of quarters ago with Amazon see super strong uptake, life sciences companies using some of the tool chains in the cloud for molecular analysis or for diagnostics, use cases that we would not have won on-prem. We are seeing them use serverless functions, LLM tools with the data infrastructure solutions we have. And then just as I walked in this morning, we actually moved a large competitive customer to the public cloud for their AI data lake, right? It's just one of many. We've been working on it for a while, and they just kind of went live with us. So gives us more wallet, more value, the ability to not only compete in cloud, but also on-prem for the full estate.
Maybe sticking on that point of competitive wins. How is NetApp seeing the competitive environment or some market share dynamics evolve as you compete with vendors who might be taking a more full solution approach where they're bundling storage with the sale of compute or networking? And how does NetApp's kind of best-in-breed independent storage vendor status compete against some of those more bundled offerings?
Yes. We've always had to compete with people who have tried to build full stack solutions, bundling all of the offerings together. And I think we've held our own. We've gained share over many years against those providers. I think 2 or 3 things there. I think one is we have innovation advantages over full stack vendors. And today, when we talk about full stack to clients, we say, "Hey, your stack is not just on-prem compute, network, storage. You want to think about hyperscale compute, network, storage. You want to think about neocloud compute, network, storage. And the real kind of full stack is an integrated hybrid cloud stack." And so we feel good about our position.
No fundamental changes from 6 months ago. I think if you look at the overall share metrics, there are several players in the market who are losing share. And it's probably us, Pure and Dell that are the kind of focused players, either gaining share or holding share.
Very helpful. I want to return to a comment you made earlier around ONTAP and talk about how the positioning of ONTAP as a software layer across on-prem, cloud and AI environments is a competitive advantage or a competitive moat for NetApp. Can you talk about how that's helping your competitive positioning in the increasingly complex configurations of your clients? And maybe for the purposes of this audience, why is this something that NetApp is able to do and your peers aren't or your enterprise customers aren't able to build in-house?
Yes. I think the core value proposition, ONTAP is our operating system. And we have been the pioneer in the industry that said it's better to unify your data estate under one operating framework rather than to have custom siloed environments for every use case. The benefits of that accrue over time. And now you can see that becoming even more apparent to clients, right?
I think the benefits accrue from, hey, much simpler operations. I don't have to patch 1,000 different environments. I don't have a huge amount of technical training that I need to have for my staff. I can learn one thing, I can use it in a much broader set of things. The second benefit has been, hey, we have taken our clients to places that no other vendor has taken their clients. We've taken them into public cloud environments. We've taken them into national cloud environments that gives them strategic flexibility and return on that investment in a way that nobody else has.
I think with regard to kind of the benefit to NetApp is we make one operating system investment, and we can recover that across a much wider range of customer types and use cases than anybody else in the industry. So there's benefits to customers that accrue at an advancing rate over time, and there's benefits to NetApp from having one platform investment that we accrue across a huge amount of use cases.
Maybe I'll ask a few more, and then I'll turn it over to the audience to see if they have any questions.
Sure.
But I do want to ask about the U.S. public sector. It has -- there's been a lot of disruption and budget uncertainty in the U.S. public sector, but we saw some nice growth in the most recent quarter. What are you seeing in the federal demand environment today? And how should we think about AI factoring into growth and recovery in that part of your business?
Yes. I think, first and most importantly, the disruption from a procurement side has mitigated. The government was operating under a continuing resolution. There was a lot of uncertainty from DoD and other disruptions in the public sector in the federal government a year ago. I think those have largely abated. There's been a funding bill that's been passed, the One Big Beautiful Bill. So we are optimistic. I think with regard to our position in the public sector market, listen, it's a 2-horse race between us and Dell. We feel strong about our position.
And I think with regard to AI, certainly, there's national security use cases, there's broad-based public interest use cases in public health or weather forecasting or resource management use cases and of course, in sort of warfighter and national defense. And so we feel excited about the opportunity to serve our government in ways that would protect American and advance American interests.
We've talked a lot about how you're helping your enterprise customers deploy AI, but you are a large enterprise yourself. Are there any examples you can share about how internally you're adopting agentic AI for operating efficiencies or other ways in which it's added value within NetApp today?
Yes. I think, first of all, we believe that whenever there's a disruption, you've got to lean into it so that you can learn it and you can really get the texture of is it really disruptive and valuable in X use cases or Y use case. So we've been sort of using AI in our business aggressively. I think from a broad basis, we had about, say, 400 sort of bottoms-up projects, we sort of narrowed that down to 140, sort of real proof of concepts to 40 projects, that have been pipelined to 13, that are contributing to positive returns in the P&L. In those, the big ones are really in product development and in customer life cycle and customer support.
In product development, it's classic, "Hey, can you deliver more innovation to market faster? Can you improve the security of your products? Can you make your products more self-healing?" In customer support, it's "Hey, can you make your knowledge bases, which our customers love, searchable using conversational AI?" It's reducing the number of inbound customer calls, which nobody likes to make, right? They want to self-service themselves and to make the user experience much, much richer. We have also been able to look at forecasting, for example, on demand or supply at a much more granular level using AI tools in ways that humans just could not do, right? You can forecast now at a subcomponent level, you can run really complex simulations across the scenarios.
And I think the 3 or 4 things I would say is, one is you want a center of excellence and control of your AI platform. We are using more open source and open-weight models to manage costs. We are building our own infrastructure to manage token costs. That AI center of excellence gives you reusable patterns, and we match that with business unit sponsorship because the business units have to fund and to make -- take responsibility for the AI use cases. And then ultimately, it's the people process change as well. You can't get AI adopted widely if you don't embrace the human change element of it.
Very helpful. Let's see if there's any questions in the audience. If we could get a microphone over here.
Can you just explain to us, if you look between cloud adoption, the public cloud and enterprise adoption and training and inference, what is sort of the sweet spot for you in terms of where these vectors are headed towards? In other words, is there a point in which you might see sort of a greater inflection point in your business as we have a greater mix of inference or as enterprises adopt more AI? Just sort of give us a sense of how that plays out.
Yes. I think from our exposure and for the longer term, inference really is the important element. I think it's true not only for our business but for the industry at large, right? Inference has to deliver value for continued investments in AI technology. For data storage and data infrastructure, inference is the much bigger part of the overall business than training.
I think we have seen more projects becoming successful in inference. You can see that from the engagements we have with customers where a year ago, they were in pilot mode in a lot of them. Now they're putting it into production. I think with regard to the growth in our public cloud business, these are production use cases. They're not training, or they're not proof of concepts. They've run the proof of concept a year ago, and now they are really doing scale production.
So as inference grows, who's likely to be your biggest customers? Is it the enterprise themselves, the cloud customers, content aggregators? Who's likely to emerge as sort of the largest incremental buyer for your solutions?
I think we do not sell to the hyperscalers. We sell through them to the enterprise. That has always been our business model, right? And so we think that the -- there's a set of digital natives and AI-native companies that are not the hyperscalers, but people that are actually building applications using AI on behalf of others, maybe, or Software-as-a-Service companies as well as enterprises. We are making some product announcements at INSIGHT for super, super high-scale frontier lab kind of training environments. And so from -- if those innovations are successful, which we expect them to be, they will also bring us a new class of customers.
And as the price of components and memory has increased, storage as a percentage of the overall solution, as the cost has also increased, are you seeing some kind of a pushback from end users? What is sort of the conversations as you have to raise your prices to maintain margins?
I think we have had to be responsible about making sure that you optimize the customers' estate. So on the things that we can control, we make sure that they're using high-priced flash, for example, only for the data that deserves to need that level of performance. We are actively engaged in helping customers reduce or reuse equipment in more sort of to help them reduce the impact of the price increases.
I think with regard to what we have seen, which is countercyclical, is usually when prices go up, the amount of new equipment purchases are constrained because customers budget in dollars. So we went into the year, we said, "Hey, typical pattern says X amount of new use cases, Y decrease in the amount of refresh of infrastructure upgrades." We are seeing infrastructure upgrades way above normal pattern. We are seeing new use cases also way above normal pattern, which says that there is a secular spending shift towards our category. And that is why we are so far ahead.
I do think we're out of time, unfortunately. I want to keep everyone on schedule this early in the day. But George, it's been a privilege to have you here. Everyone, I hope you have a successful and fruitful conference. Thank you.
Thank you for having me. Thank you.
Thank you.
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NetApp — Goldman Sachs Communacopia + Technology Conference 2026
Fireside‑Chat: NetApp betont AI‑getriebene Nachfrage, hybride Cloud‑Moat (ONTAP), AFX‑Momentum und solide Public‑Cloud‑Dynamik.
🎯 Kernbotschaft
- AI‑Treibstoff: Agentische und inferenzorientierte KI‑Projekte treiben breite Nachfrage nach leistungsfähiger, einheitlicher Dateninfrastruktur.
- Plattformvorteil: ONTAP als einheitliche Daten‑OS soll NetApps Wettbewerbsmoat bei Hybrid‑Multi‑Cloud‑Einsätzen sichern.
- Wachstumstreiber: AFX (neocloud/Training), Public‑Cloud‑Geschäft und Sovereign‑Partnerschaften sind die klar benannten Hebel.
🚀 Strategische Highlights
- AFX‑Opportunity: AFX adressiert flexible Kombinationen aus Compute und Storage für Neoclouds und Trainings‑Workloads; weitere High‑End‑Ankündigungen geplant.
- Sovereignty: Partnerschaften (z.B. Google Distributed Cloud) erlauben private, nationale AI‑Umgebungen mit Hyperscaler‑AI‑Stacks und NetApp‑Storage.
- Produktmix: Starkes All‑Flash‑Wachstum, aber auch wachsende Nachfrage nach disk‑basierten Systemen als Reaktion auf hohe Flash‑Kosten; Keystone (Storage‑as‑a‑Service) bleibt relevant.
🔍 Neue Informationen
- Guidance‑Status: Keine neue Guidance im Chat; Management referenziert die letzte Anhebung für FY27, bietet aber zusätzliche Farbgebung.
- Konkretes: AFX‑Momentum, mehr Engagements in Sovereign‑Clouds, Inventory‑Aufbau und aktive Long‑Term‑Agreements mit Lieferanten wurden betont.
- Internes AI‑Learning: Pipeline: ~400 Ideen → 140 PoCs → 40 Projekte → 13 mit positivem P&L‑Beitrag; Fokus auf Produktentwicklung und Kundensupport.
❓ Fragen der Analysten
- Inference vs Training: Management sieht Inferenz als langfristig größeren Markttreiber; Kunden verschieben viele Projekte von Pilot zu Produktion.
- Kundensegmente: Käufer reichen von traditionellen Enterprises über SaaS/AI‑Native Firmen bis zu Neocloud‑Betreibern; Hyperscaler werden indirekt adressiert.
- Kosten/Preise: Diskussion zu Komponentenpreisen und Kundenreaktionen; Management nennt LTAs und Inventar als Absicherung, liefert aber keine detaillierten Preisannahmen oder AI‑Umsatzquantifizierung.
⚡ Bottom Line
- Auswirkung: NetApp positioniert sich als Profiteur der KI‑Welle durch Plattform‑Vorteile (ONTAP), Cloud‑ und Sovereign‑Partnerschaften sowie AFX‑Innovationen; Margen und Wachstum hängen von Lieferkettensicherung, Preisrecovery und der Konversion von Piloten in Produktionsprojekte ab.
NetApp — Q1 2027 Earnings Call
1. Management Discussion
Good day, and welcome to the NetApp First Quarter of Fiscal Year 2027 Earnings Call. [Operator Instructions] Please note, this event is being recorded.
I would now like to turn the conference over to Kris Newton, Vice President, Investor Relations. Please go ahead.
Hi, everyone. Thanks for joining our Q1 FY '27 earnings call. With me today are our CEO, George Kurian; and CFO, was Wissam Jabre. This call is being webcast live and will be available for replay on our website at netapp.com.
During today's call, we will make forward-looking statements and projections with respect to our financial outlook and future prospects, including, without limitation, our guidance for the second quarter and fiscal year 2027, our expectations regarding future revenue, profitability and shareholder returns, the expected benefits from our acquisitions and partnerships, and other growth initiatives and strategies. These statements are subject to various risks and uncertainties, which may cause our actual results to differ materially. For more information, please refer to the documents we file from time to time with the SEC and on our website, including our most recent Form 10-K and Form 10-Q. We disclaim any obligation to update our forward-looking statements and projections.
During the call, all financial measures presented will be non-GAAP unless otherwise indicated. Reconciliations of GAAP to non-GAAP measures are available on our website.
I'll now turn the call over to George.
Thanks, Kris. Good afternoon, everyone. Thank you for joining us today. We delivered a stellar start to the year, exceeding our Q1 guidance on every metric and delivering a record-setting first quarter. Revenue increased 30% year-over-year to $2.03 billion. Our disciplined approach converted robust top line growth into significant profitability even in a challenging component cost environment with gross profit growing 29% to a record $1.43 billion, operating margin reaching 31.9% and EPS up 66% from Q1 a year ago. Adjusting for the additional week in Q1, our performance still stands as 1 of the best in the company's history.
This quarter's achievements reflect more than just strong execution. They underscore NetApp's growing leadership in a rapidly evolving environment. Our broad-based success expand industries and geographies with multiyear agreements, expansion into new workloads and deeper customer engagement, all strong leading indicators of durable growth.
While we're seeing some accelerated purchase decisions and pricing benefits, we are also seeing a clear structural improvement in the underlying demand environment all of which contributed to Q1 strong results and are fueling our momentum. This exceptional quarter is both a testament to our execution and a clear signal of the expanding opportunities ahead.
Given our strong start and the success we're seeing across our business, we are materially raising our outlook for the year.
AI is no longer a future aspiration. It's a business imperative. As organizations move to operationalize AI, the challenge is not just compute but data readiness. NetApp is a key partner for companies making this shift, eliminating complexity and accelerating time to value at scale. The NetApp platform enables customers to make all data AI-ready in place, providing unified storage, robust security and a single control plane across hybrid multi-cloud environments, delivering capabilities that redefine expectations in the industry.
By removing the need for data movement, we empower enterprises to accelerate AI and analytics while maintaining governance and control, enabling them to transition from AI experimentation to production with confidence.
The strength of our platform is fueling both deeper relationships with existing customers and new customer acquisition. A recent win highlights this momentum in a highly competitive evaluation, a major U.S. utility chose NetApp over both legacy and flash-only competitors, displacing the incumbent and standardizing on our unified AI-ready data infrastructure. Wins like this where a customer and trust their most demanding workloads to NetApp are leading indicators of our expanding role in the market and set the stage for long-term growth.
Our record Q1 was fueled by robust growth in public cloud, all flash and keystone revenues, reflecting the momentum in our business and validating our strategy as we deliver meaningful results for customers.
Driven by strong adoption of our first-party and marketplace storage services, Q1 public cloud revenue grew to $206 million, up 28% year-over-year and up 19% adjusting for the extra week.
Customers choose NetApp for our secure, scalable, cloud-native storage services as they migrate workloads to the cloud. VMware workloads in particular, are among those increasingly being moved to the cloud, opening significant opportunities for NetApp. In Q1, a U.S. hospitality company adopted NetApp technology for the first time through Amazon FSX for NetApp on Tap, supporting its large-scale VMware migration to AWS. FSXN delivered superior performance lower cost and versatile workload support. Similarly, a U.S. public sector organization selected Azure NetApp Files as a part of its data modernization efforts. A&F overcame technical barriers found in other cloud services and enabled substantial cost savings. These wins highlight how NetApp's differentiated cloud storage solutions facilitate seamless, efficient VMware migrations, reinforcing our ability to drive sustained growth as organizations accelerate their cloud adoption. All-flash array revenue reached $1.31 billion in Q1, up 47% year-over-year. Customers are standardizing our NetApp for their most mission-critical workloads, including GPU-intensive AI pipelines that demand high performance, low latency and built-in cyber resilience. Our innovation and go-to-market execution continue to drive share gains in this part of the market.
In today's challenging cost environment, the breadth and flexibility of the NetApp platform stand as strategic advantages. We empower customers to optimize performance, capacity and budget requirements without compromising cyber resilience or operational simplicity. This value proposition is driving strong customer demand across our portfolio. And notably, we are seeing accelerating interest in our hybrid flash solutions.
Let me share recent examples of how the breadth of our portfolio has enabled us to displace competitors and win new customers. In its first engagement with NetApp, a European IT service provider for pension insurance, selected our unified storage to meet stringent security and resilience requirements for critical infrastructure. Our flexible architecture not only supports the availability and integrity of highly sensitive data today, but also provides a secure, efficient and sustainable foundation for future AI workloads. NetApp recently displaced a competitor at a leading transportation agency. Our solution combined all-flash arrays for high-performance processing of massive video files with hybrid flash arrays for reliable, cost-effective long-term retention. Our ability to deliver the scalability reliability and performance required for advanced analytics and ongoing infrastructure maintenance was key to the win.
AI is powering a new wave of growth for NetApp, momentum that has been building and continues to accelerate. In Q1, we won approximately 350 AI and data lake modernization deals, up significantly from a year ago. Importantly, deal sizes are increasing as customers move from proof of concept to production. Initial wins in prior years are expanding into production-level workloads, reflecting confidence in NetApp's ability to support large-scale AI environments. Our solutions are enabling customers to activate data in place for AI, accelerate time to insight and achieve real business outcomes, putting NetApp at the center of their journeys.
Here are a few examples from Q1. We signed a significant agreement with Samsung Electronics to support its EDA environment and AI Center of Excellence. A public sector organization awarded NetApp a strategic deal to modernize and expand its intelligence capabilities and deliver real-time analytics, leveraging NetApp AFX integrated with NVIDIA Superpod. AFX's disaggregated architecture provides the flexibility and performance required for advanced AI workloads and provides a future-ready foundation, delivering the power and scalability needed to meet evolving requirements as data demands grow. NetApp secured a significant win with an Asian neo cloud provider, supplying high availability, secure and scalable storage for new customer-facing AI services. Our robust multi-tenancy and deep expertise in large-scale Kubernetes and OpenStack environments set us apart, helping the provider to modernize its infrastructure and support demanding AI inference workloads. This win displaced existing vendors and established a strong foundation for NetApp in 1 of the providers' most strategic AI initiatives.
We are strengthening our leadership through strategic acquisitions that expand the capabilities of the NetApp platform and broaden our addressable market. These investments position us to stay ahead as customer needs evolve, deepening our differentiation in cloud and AI.
In Q1, we acquired DataPelago, a recognized innovator in AI data infrastructure. Their nucleus software engine enables high-performance in-place data processing, eliminating costly data movement and streamlining AI readiness. With this technology, we believe we can unlock additional value from the vast unstructured data already managed on our platform, giving customers fresh opportunities to accelerate their AI initiatives and maximize the potential of their existing data assets. This positions NetApp as the company that makes zero-copy activation of enterprise data for AI real, helping customers drive AI initiatives improve efficiency and unlock more value from their data.
At the start of Q2, we acquired JetStream, a leader in cloud native disaster recovery for VMware environments. JetStream enables continuous protection and recovery of VMware workloads across diverse storage environments with seamless replication to NetApp cloud offerings like Azure NetApp Files. This acquisition will allow us to offer a simpler, more flexible path to cloud modernization and positions NetApp as the recovery destination of choice for VMware deployments, even when production data originates from competitors' infrastructure.
NetApp's strong Q1 results underscore our leadership in a transformative era shaped by accelerating AI and cloud adoption. The strength and flexibility of the NetApp platform allow us to support a diverse and growing customer base. By winning new business, deepening partnerships and investing in innovation, we are building a durable foundation for continued leadership and long-term growth. We are executing with discipline and vision and building on our leadership to deliver sustained value for our customers and shareholders.
We are excited to host our annual customer conference, NetApp Insight in September. We will showcase substantial innovation throughout the NetApp platform, delivering new value for AI and addressing the unique needs of high-growth markets like neo and sovereign clouds. We also will host an investor session to provide more detail on our strategy and solutions, and we hope you will join us.
In closing, I want to thank our employees for their dedication and focus. Our record start to the year is a testament to our team's commitment to our customers and to driving NetApp's continued success.
I'll now turn it over to Wissam.
Thanks, George, and good afternoon, everyone. In the fiscal first quarter, we delivered exceptional results exceeding the high end of all our guidance ranges. Revenue for the quarter was $2.03 billion, up 30% year-over-year and 4% sequentially. Non-GAAP earnings per share was $2.58, up 66% year-over-year. Revenue growth was driven by broad-based momentum across the business, highlighting the strength of our portfolio. This quarter's results reflect a healthier demand environment as customers invest in AI and modernization as well as some accelerated purchases and pricing benefits. As a reminder, Q1 included an additional week. Revenue was up 26% year-over-year, excluding the effect of the extra week, which contributed approximately $65 million to revenue, primarily in support and public cloud.
Looking at revenue by segment. Hybrid cloud revenue of $1.82 billion was up 30% year-over-year and 27% adjusting for the additional week. Product revenue of $987 million was up 51% year-over-year. Support revenue of $720 million was up 11% year-over-year and up 4%, excluding the extra week, which contributed approximately $50 million. Professional Services revenue of $112 million was up 15% year-over-year, mainly driven by continued robust growth in Keystone, our Storage-as-a-Service offering. Q1 public cloud revenue of $206 million was up 28% year-over-year and up 19% adjusting for the extra week, reflecting strong demand for first-party and marketplace storage services. The additional week contributed approximately $15 million to public cloud. We exited Q1 with $4.85 billion in deferred revenue, an increase of 7% year-over-year. Remaining performance obligations were $5.65 billion, up 14% year-over-year.
Moving to the rest of the income statement. Please note, my comments will be related to non-GAAP results unless stated otherwise. Q1 gross margin was 70.6%, exceeding the high end of our guidance and down 50 basis points year-over-year driven by greater product revenue mix compared to a year ago. Product revenue in the quarter was 49% of total revenue compared to 42% in the same period last year. The headwind from revenue mix was partially offset by year-over-year gross margin expansion across product, support, professional services and public cloud. Gross profit was $1.43 billion, up 29% compared to Q1 2026. Hybrid Cloud gross margin was 68.8%, down 20 basis points sequentially and reflecting lower product gross margin and partially offset by improvement in support and professional services gross margin. Product gross margin was 54.6%, down 150 basis points sequentially, mainly driven by higher component costs and partially offset by better pricing. Our recurring support business continues to be highly profitable with gross margin of 93.2%. Professional Services gross margin was 36.6%, improving 4.5 percentage points sequentially. Public cloud gross margin was 86.4%, up 70 basis points sequentially and over 6 percentage points year-over-year benefiting slightly from the additional week. The public cloud business has operated above the high end of the 80% to 85% long-term target range in the past 3 quarters. Operating expenses of $784 million were up 11% year-over-year and 5% sequentially, driven primarily by variable compensation and the impact of the additional week, which added approximately $22 million. Operating income was $645 million, up 61% compared to Q1 2026, and operating margin was 31.9%, up 6.1 percentage points year-over-year.
Earnings per share exceeded the high end of the guidance range at $2.58, up 66% year-over-year, more than double the growth rate of revenue, highlighting the operating leverage and our ability to translate that into earnings power.
In Q1, cash flow from operations was $503 million and free cash flow was $401 million. During the first quarter, we returned $302 million of capital to our shareholders with $200 million in share repurchases and $102 million paid in dividends of $0.52 per share. Q1 diluted share count of 200 million decreased by 3 million shares or 1.5% year-over-year.
Our balance sheet remains very healthy. We closed the quarter with $3.6 billion in cash and short-term investments and $2.5 billion in gross debt outstanding, resulting in a net cash position of $1.1 billion. Inventory expanded both year-over-year and quarter-over-quarter as we manage supply and inventory levels to support growing demand. Inventory turns were 6 down sequentially.
Overall, Q1 was an excellent start to the fiscal year, highlighted by strong revenue growth amid heightened AI and cloud-driven storage solutions demand. Combined with our disciplined execution, our revenue growth drove meaningful operating margin and EPS outperformance and robust cash flow generation.
Now turning to non-GAAP guidance, starting with Q2. We expect revenue to be $2.1 billion, plus or minus $75 million. At the midpoint, this implies 23% year-over-year growth. We expect gross margin to be in the range of 67% to 68%, sequentially lower, primarily driven by higher product revenue mix as a percentage of total revenue. We expect operating margin to be in the range of 30.9% to 31.9%. We expect earnings per share to be in the range of $2.54 and $2.64 with a midpoint of $2.59.
Turning now to full year fiscal 2027. We remain confident in the strength of our portfolio and our ability to execute in the current environment. Strong demand and continued business momentum reinforce that confidence and support our increased outlook for the year. We are raising our fiscal year revenue and EPS guidance. We now expect fiscal year 2027 revenue to be in the range of $7.975 billion to $8.225 billion. At the $8.1 billion midpoint, this represents 17% year-over-year growth and an increase of $650 million compared to our prior guidance. We expect gross margin to be in the range of 68.1% to 69.1%. The revised range primarily reflects a higher expected mix of product revenue compared with our prior guidance. At the same time, our fiscal year 2027 product gross margin expectations have improved slightly, while the underlying gross margin outlook for the rest of the business remains largely unchanged. We are raising operating margin to be in the range of 30.3% to 31.3%. We are raising earnings per share to be in the range of $9.73 to $10.03. At the $9.88 midpoint, this represents 22% year-over-year growth.
In closing, as we look ahead to the rest of fiscal year 2027, we remain confident in our strategy and disciplined execution. Our focus stays firmly on delivering strong revenue growth and profitability strengthening free cash flow and building long-term value for our customers and shareholders.
With that, I'll now turn the call over to Kris for Q&A.
Thanks, Wissam. Operator, let's begin the Q&A.
[Operator Instructions] Your first question comes from the line of Joseph Cardoso with JPMorgan.
2. Question Answer
Maybe for my first, if I could. George, you called out accelerating purchase decision and pricing benefits as well as structural improvement in underlying demand at the same time. Can you maybe just help us through the key drivers that is helping to distinguish between those dynamics? And what drives your confidence around maybe the more durable demand part of that? And just particularly in the context of the outlook, which implies at the time heading into the second half of fiscal year? And then I have a follow-up.
Thank you for the question. We had an exceptional start to the year. The demand profile was broad-based and we saw strength across every customer type, by size, medium, small public sector. We saw it across all the geographies, and we saw it across industry verticals, workload solutions, on-prem, Keystone, cloud. So super strong broad-based portfolio strength. I think when we distinguish the 3 buckets, clearly, what we saw in the quarter was counter to what we see typically when prices of silicon and commodity costs go up dramatically, customers generally lean into tech refresh. We saw into maintenance and non-refresh. We saw the opposite. We saw much higher than the anticipated strength across all classes of customers. Within the largest customers we saw some pockets of accelerated purchasing. But in many of those customers, we also saw them for less priority workloads and use cases be more moderated in their buying behavior as is typical. And then we saw clearly as commodity prices have gone up, we have adjusted our pricing, and you could see that in the outperformance in our product gross margin relative to our guidance, which is reflected in our ability to capture higher pricing.
No. Got it. George, I appreciate the color there. And maybe just a quick follow-up on the last comments you made. I just wanted to get a update or a clarification on how you're thinking about. I think you believe -- I believe you guys called out product gross margins troughing in the first quarter itself. Is that playing out? And then maybe more specifically, are you realizing the full benefits of the flow-through of the pricing actions you've taken and whether that's already played now in 2Q? Or should we expect that to there will be a tailwind going out into the 3Q or 1 of the subsequent quarters?
Yes, great question. And so in Q1, we did outperform our expectations with respect to the product gross margin, as George mentioned. We did have a bit of a favorable product mix associated with the various customer types and the geos that we serve. And so it did help us a little bit.
As we think and we look forward to Q2 and the rest of the year, the outlook very much on product margin has improved slightly relative to our prior guidance that we've provided 90 days ago. And so that's sort of an incremental positive, which basically says we have a bit more confidence in our ability to recoup the incremental costs that we're paying albeit probably won't be at the same levels we saw in Q1, but I would stress that it would be -- we're anticipating or -- and projecting it to be better than we thought it would be 90 days ago for the rest of the year.
Your next question comes from the line of Mehdi Hosseini with Susquehanna Financial Group.
Yes. I also have a question with 2 parts. Georgia, help me understand how would you break up your customers' investment and splitting modernization, upgrade of existing installed base of storage from incremental capacity added due to AI inferencing?
And my second question is for Wissam. I'm a little bit confused with the product gross margin trajectory. I think expectation was for gross margin -- private gross margin to be ramping in the mid-50% and improve from there. But your Q2 guide implies that we actually may see a Q-over-Q decline. If you could clarify, it would be appreciated.
With regard to your first question, Mehdi, we have seen super strong growth in our product portfolio as well as offerings like our all-flash array, Keystone and our cloud storage. Pretty much across the board, we were well ahead of our expectations. And we continue to see that strength durable for multiple quarters, which is why 1 quarter into the year, we have raised the full year materially, including the second half, right? So really, really strong momentum in the business.
With regard to what we saw, there are AI-specific build-outs, which are, for example, GPU as a service cloud, GPU environment within enterprises and data lakes and modern data lake type environment being built, particularly for GPU usage and for AI analytics. There is, however, also as other people have noted, including the hyperscalers, a broad-based modernization of a variety of adjacent workloads and infrastructures, right? So when you use AI, you also want to modernize your databases, you also want to modernize your unstructured data environment to get them ready, and we saw that happening pretty much across all the industries and all the customer segments. So really strong momentum. We're excited for the year, super confident about our position in the market and the alignment to where customers are prioritizing spending.
And to the second part of the question, Mehdi. Look, we did anticipate -- so maybe I'll explain how we anticipated the product gross margin to be shaped throughout the year, 90 days ago. We said that we would see a trough in Q1, and we anticipate a slight improvement for the rest of the year or gradual improvement for the rest of the year.
Now fast forward to today, we did manage Q1 product gross margin in a really great way. I think we did a great job in execution and we outperformed our expectations for Q1. So that's sort of the first point I want to make.
The second point is when we compare now Q2 to Q4 for the rest of the year to where it was 90 days ago, we're now expecting it to be slightly better. So if you think of the prior guidance had product gross margin in sort of the low 50% range if you sort of -- even though we don't guide every number, but that's why I was implied in the guidance, what's implied now in the updated guidance for the rest of the year in product gross margin is slightly better than that. That's really the -- hopefully, that clarifies and answer to your question.
Your next question comes from the line of Amit Daryanani with Evercore.
I guess just 2 questions from my side as well. I think 1 of the big things that investors are trying to figure out is just the durability of growth that you and everyone also seeing. And if I think about your fiscal year guide, you're also going to do a 26% growth in Q1, ex extra week, you're going to 23% in Q2. And I think it's like 9% or 10% in the back half of the year. Can you just talk like what is driving that sort of deceleration? And is that exit rate in the back half of 9%, 10%, sort of a wide way to think about what the long-term growth should be for the company?
And then George, you sort of talked about you're seeing clear structural improvement in the underlying demand environment. Can you maybe just help us appreciate like what metrics are you looking at or tracking to give you confidence that this is a structural shift versus perhaps prebuying given all the price increases?
I think, first of all, we are 1 quarter into our fiscal year and our approach has been to provide guidance that we feel confident about. We have raised the year materially to reflect the strength of our position and have raised the second half of the year right at the start of the year, right? And so I would not say that we are being cautious about the year. We feel really strongly about the performance. I think as I noted, with regard to what gives us confidence, it is the fact that all of our product lines, all of our customer segments by size, all of the types of commercial vehicles we use multiyear agreements, storage as a service, traditional CapEx transactions as well as the performance through all of our routes to market have outperformed materially and the outlook for the year is very strong. So we feel really, really good about our position both in terms of alignment to customer spend, the overall customer discussions we're having and the expanding opportunities we see across all kinds of customers.
Your next question comes from the line of Krish Sankar with TD Cowen.
Congrats with good results. George, my first question is that you kind of closed like 350 AI and data lake deals this quarter. Last quarter is more like 500. I understand the deal sizes are getting bigger. Is there a way you can quantify how much was the deal size of revenue dollars in the July versus April quarter? And from a bigger picture perspective, how much of your revenues is driven by AI? And then I had a quick follow-up for Wissam after that.
I think it's hard to quantify specifically what percentage of the revenue is driven by AI for 2 reasons. One is there are customer specific AI-specific environment, right, which is what the 350 deals that we said count toward, these are typically GPU connected AI stack connected deals.
That being said, as we and others have noted, AI is now driving a broad-based modernization and replatforming of the data infrastructure stack, so that you can support the needs of high-performance, inferencing use cases, the ability to build cross-application kind of data infrastructure and that is reflected across the strength of our business. So 350 were AI stack specific use cases, but the overall performance of the business reflects the influence of to modernize the entire data infrastructure. And we had since many years ago that we had started to see that momentum acceleration. We saw that in Q4. We are off to a super start in Q1. Our outlook for the year is very positive, and we see really good momentum across our entire portfolio.
Got it. And then Wissam, a quick question. Your component costs are going up. So is your inventory levels. I'm just wondering, when you look at your products, you kind of spoke about the product gross margin, what is the equation you're solving for? Is it managing product mix or price capture to generate more gross profit dollars? And where are most of the inventory dollars spent on?
Yes. So Krish, we did exit Q1 with a slightly higher inventory, but that's because, obviously, we continue to manage our supply and secure supply to be able to secure product for the demand growth that we're seeing. What we're basically focused on is the total gross profit for the company. We managed the total gross margin, but also the total gross profit dollars. And as you can see, as the top line grows, we're seeing gross profit dollars growing almost a similar pace. That's because this is what drives really the earnings power of the business. The -- I think this is best demonstrated when you also sort of take it down to the operating margin line. And you can see how basically any time where we upsided gross profit and gross margin, we tend to generate quite a bit of operating margin leverage. So I hope, this answers your question.
I think 1 of the things we have also -- one of the things we worked on to provide customers with the right solution for their use cases, I think we have started to see again the resurgence of hybrid flash in our portfolio and we anticipate a much stronger contribution from hybrid flash. So we're, as Wissam said, we're trying to solve as many customer problems with the right mix of portfolio and manage the overall business for gross profit dollar growth.
Your next question comes from the line of Asiya Merchant with Citigroup.
It's Mike Cadiz for Asiya Merchant at Citi. So my first question is regarding pricing. So as pricing actions begin to flow through and materialize in the quarter -- in quarters, how much of the expected pricing benefit do you think has been realized? And are you seeing any change in demand elasticity albeit early on?
I think with -- I'll take the demand question and Wissam can address the pricing capture. I think with regard to demand, listen, we have always believed and continue to believe that customers budget in dollars. What we are seeing reflected in the market is that the overall budget priority for data infrastructure and storage has gone up significantly in our customers. Within customers, for example, there are use cases where even at a higher price, they will be prioritizing spending on that. But within the same customer, they may defer until a future quarter a less priority use case. And we have seen that in our customer base. In some of those customers, they have also decided to go from a flash-based solution to a hybrid flash-based solution for the lower value use case, right? And so I would say that the most important thing that we have seen is unlike in prior cycles with the significant increase in pricing, we are actually seeing broad-based infrastructure spending, and we believe that it is correlated with and the modernization requirements of AI.
Yes. And with respect to the delay between the pricing actions and when we start seeing it. Look, we've taken actions to be more agile in this environment. So the impact of price increases should materialize sooner than in the past. In the past, for instance, it would take probably 2 to 3 quarters to start seeing it. But now we're seeing it much earlier.
Your next question comes from the line of Erik Woodring with Morgan Stanley.
George, I just want to maybe press you as a follow-up to Amit's question earlier, which is I realize we're just 1 quarter into the year, it's early, but your second half revenue is usually like high single digits versus your first half. And you're guiding it down. And so I understand the desire to remain conservative and provide a guide that you can hit. But given your qualitative commentary about demand, like why couldn't you beat those expectations by 10%, 20%? I just want to make sure we're not missing anything, just as we think about seasonality from the first half to the second half and anything that could be maybe an offset to way that -- to a way that we're thinking about normal seasonality? And then a quick follow-up, please.
Yes. So Erik, this is Visa. When we think of the seasonality, if you adjust for the extra week in Q1, we are now roughly seeing -- looking at 50-50, maybe a little bit -- when we're talking around in here, a little bit more than 50% in the second half, a little bit less than 50% in the first half. I mean you can do the math. But that's just basically based on our visibility at this time. We do, however, see as George mentioned in his prepared remarks, a really strong structural improvements in the demand. It's broad-based. It's driven by AI workloads. It's driven by modernization, and we basically are looking at that being the driver of revenue for the rest of the year.
We have 1 quarter in, Erik. We feel really good on our business. We've raised Q2 guidance. We've raised the full year guide. We'll tell you more as we play through the year. We are super confident about our position in the market, and we'll get more as we play through the year.
Awesome. Thank you, George. I can hear it in your voice. So I appreciate that, guys. And then Wissam, just 1 clarification point. The comments that you make about product gross margins and your ability to maybe get a little bit better capture here in the first quarter, is that purely a function of pricing and pricing confidence and kind of confidence in the demand in elasticity response there? I just want to make sure that we think about your ability to maybe capture slightly better product gross margins, it's because it's a function of price and not necessarily the other side, obviously being the [ bomb ] inflation.
Yes. Look, I mean, my comment is based on everything we see. As we look at -- as we form our outlook and we look and we project the business, we put everything that we know in our numbers. And that's really what my comment is about. It has to do with pricing. It has to do with [ banks ]. It has to do with multiple factors that basically go -- and of course, the cost side of the equation, that basically goes into forming the funnel, basically product margin.
Your next question comes from the line of Param Singh with Oppenheimer Inc.
So you've done a couple of acquisitions -- niche acquisitions recently. And I wanted to understand where do you see gaps in your technology portfolio today? And where does this make sense to buy versus build? And then I had a follow-up.
I think we are disciplined in our approach to acquisitions. The 2 that we have talked about are tied to cloud and AI. And they provide us with differentiated offerings to accelerate our position in each of those use cases.
With regard to DataPelago it is really about AI-driven analytics and the inferencing where we can accelerate the application processing adjacent to storage providing customers a better inferencing solution top to bottom.
With regard to JetStream, which we acquired at the start of Q2, it really strengthens our already strong position in VMware migrations to the cloud. We have really good solutions for customers that want to use NetApp to migrate. But for customers that are non-NetApp on-prem, we have a really good starting point with a DR in the cloud solution. So those are the 2 areas, AI and cloud that we're focused on, and we feel good about the technology portfolio that we have and we are doing tough ins to enhance the overall solution value to customers.
Understood, George. And then as my follow-up, your guidance implies that OpEx would go up as a percentage of revenue from the Q2 level in the back half. So I want to understand why there is an increase in investment in the back half? And then where would that actually go with it, is it R&D or sales and marketing? So if you could give some color on the investments that you're thinking about for the rest of the year, that would be great.
Yes, Param, this is Wissam. So the increase is driven really by a couple of areas. One, as we outperform, we're getting -- we have a slightly higher variable compensation accruals. And then the second is really continuing to invest in our AI solutions. But when you look at the overall OpEx for the year and you sort of look what is implied in the guidance, year-over-year is still a -- year-over-year increase for the full year, it still shows basically that the increase is less -- much less than the half of the revenue -- projected revenue growth. So we continue to be very disciplined in how we invest and how we look at our OpEx. That's, of course, because operating leverage and driving operating margin is a key element of our business model.
Your next question comes from the line of Wamsi Mohan with BofA.
I have a couple of clarifying questions. I think as you sort of think about the full year, a, would you say that your expectation of hybrid versus all-flash is similar versus your prior expectations? Would you say that given what you're seeing with supply that the upside that you're guiding to would be more driven by 1 versus other? And I have a quick follow-up, too.
Listen, I think that if you look at the overall business, all-flash performed exceptionally strongly in Q1, right? It was up 47% year-on-year. So when we look at the overall year, all-flash still blows out our prior expectations. Hybrid flash, when we had planned the year, we were cautious about customers' spending on non-mission-critical workloads. That is typically what they do, right? When you see price increases, customers pull back on capital equipment spending, we are seeing broad-based acceleration in capital spending across the board. And we are -- which is a sign of the AI super cycle, but then we are also seeing customers buying more hybrid flash. I would say if you look at the relative comparison. Listen, all-flash is super strong and will still be the predominant part of the acceleration in our business.
Okay. And as my follow-up, just is there any way you could give us some sense of this magnitude of these accelerated purchases. Going back to Erik's question on half over half seasonality, you guys obviously sound very confident on the outlook over here. But could you just help us through -- think through mathematically, how large was the accelerated purchases or the contribution there, which we should factor in as pull forward? Or is that just acceleration of demand that is coming not necessarily from the second half?
I think first of all, we're not going to break it out, right? I think what I would tell you is the number of customers and the percentage of our customer base that have the financial flexibility to do accelerated spending is very small, right? These are very large private companies usually, not even public sector organizations have the flexibility to do accelerated purchasing. So it is a much smaller percentage of customers than you would imagine, right? Very small percentage. What we saw in the results in Q1 was certain transactions that we expected to be built out over multiple quarters happening within a quarter. That doesn't mean that those same customers didn't defer other projects to accommodate these projects, right? And so I would tell you that it's a percentage of our business, we did not see it in Q4, but we saw it in Q1, and we felt like it was appropriate for us to acknowledge it. But it is not a material part of the overall business. In certain clients, as we talk about they are kitting out multiple data centers. They wanted to kit out -- they said, let's do 2 of the 4 that we want to do faster this calendar year and we'll come back for the other 2. We had expected kind of a more gradual build out of those. That is not common and widespread across the customer base.
Your next question comes from the line of Steven Fox with Fox Advisors.
I was curious if you could talk a little bit more about new customer wins. You mentioned that, that was also contributed to growth this quarter. I was curious from the standpoint of what maybe you're leading with and whether it's what kind of products, et cetera, and whether you're having success in certain verticals that we should be aware of?
Thank you for your question. We saw strength, as we said in our prepared remarks, in new customer acquisition, a new workload expansion within existing customers and stronger-than-expected tech refresh in our business. With new customers, we typically attack from 2 different vectors. Ones are kind of cloud-based solutions or our purpose-built block optimized solutions for the corporate and mid-market customers and with our unified sort of simplify your infrastructure, unify it on 1 platform solution for the enterprise. And we feel really good about our position with both new customer counts, new customer dollars as well as expansion within existing customers we're all as well ahead of our internal forecast.
Your next question comes from the line of Katherine Murphy with Goldman Sachs.
In lines with the following question regarding new customer acquisition through new workloads and new product categories, can you talk more about the success you're seeing in the AFX platform? I know you highlighted a public sector win in the quarter, but anything to share just on the momentum there and how that may be contributing to outlook for the full year?
AFX is built for the very high end of the performance and scale environment. So the number of transactions are not as many but the size of the transactions are material. We have really focused it on the AI GPU as a service category, and we're seeing good progress. We talked about neo clouds. We talked about the government agency that's building a private AI cloud. And so good progress. It is being certified across a large number of customers, and we're excited to continue to make progress on the solution.
Your next question comes from the line of Tim Long with Barclays.
Yes, maybe a follow-on, and then the second one. On the public cloud business, 19% growth ex the extra week is still very good growth rate. We've seen it kind of around that number for the last 1.5 years or so. So just curious, is there anything in the pipeline or new solutions or customer bases or anything that could maybe accelerate that number?
And then second, on Keystone, I did want to touch on that, you talked about growth and strength there. Looking at the professional services line and backing out an extra week, it doesn't look like it grew that much and we're kind of seeing or hearing about more as-a-service purchases in that area instead of paying up for more expensive hardware-based solutions because of the NAND price increases. So just talk about what you're seeing with those as-a-service solutions surprised we're not seeing a little bit more acceleration in that.
I think with regard to the public cloud business, listen, it stayed in the high teens as we have scaled the business. So I'm encouraged by the sustained momentum of the business. Obviously, the cloud storage business performs at a much higher level than that. And so we continue to see strengthen the [ 1P ] or the first-party end marketplace storage services.
With regard to the things that we're bringing out, please come to Insight. We have more AI solutions with the hyperscalers. We have more use cases combining data on-prem with hyperscale cloud and we have brought block storage and lower cost price points in multiple clouds, including Google and Amazon. So really good progress across the portfolio in cloud.
With regard to Keystone, without giving you a specific number, I will just say our Keystone business grew roughly in the same ballpark as prior quarters and in the same ballpark as our overall flash business, which is a really strong number. So we're excited about the progress of the business. We are seeing more new customers that we are targeting with Keystone, and we are bringing more capabilities to that part of our portfolio.
And Tim, just to add to what George said on Keystone, keep in mind, Keystone didn't really benefit much from the extra week, it benefited a very, very minimal amount.
Your next question comes from the line of Victor Chiu with Raymond James.
So inventory nearly doubled sequentially. Just kind of wondering, is that a function of trying to secure NAND and other components against expected demand? And maybe how much you have the inventory increases earmarked to specific customer orders and backlog. And a follow-up there, does the inventory buildup kind of give you better visibility into the remaining year and into next year?
Yes. I didn't get the second part of the question. But on the first part of the question, most of the inventory [ with that ] some strategic purchases and basically us managing inventory to be able to ship to our customers based on the strength of demand. So I wouldn't say -- in my mind, this is a positive. We're really making sure that we have the supply to continue to drive the growth in the business. I'm sorry, could you please repeat the second part of the question?
Yes. Does the inventory buildup kind of give you better supply and cost visibility, I guess, throughout this year and into next year?
Yes, typically...
You know, pricing is going to be less of a function in healthy growth, I guess.
You're correct. Typically done.
Your final question today comes from the line of David Vogt with UBS.
Great. So I'm going to keep it brief words. You've answered a lot of questions. But just a question on demand as we think about the next couple of quarters, is there any sort of seasonality that you saw in the most recent quarter, particularly as we go into subsequent quarters from industry verticals? I know if we go into the October quarter, obviously, there are customers that have different fiscal year-end. Did you see any sort of demand maybe slightly different seasonal demand patterns in the quarter? Because I know I think Wissam mentioned that there was a little bit of a pull in. I'm just trying to get a sense for how do we think about sort of the normal seasonality? Maybe this isn't normal, but how do we think about the seasonality of demand as we move through the back half of this year? .
Listen, I think our outlook, if you adjust for the extra week in Q1 is roughly in line with typical seasonality. And as Wissam mentioned, second half and first half are within spitting distance of our typical seasonality, right? I think we have a really broad book of business, David. And so the movement of any 1 customer is not going to affect the broad book of business. I think the 1 exception to that is typical U.S. public sector seasonality, right? And that you are quite aware of. So we feel really good about the momentum in the business. Listen, as we said, exceptional start to the year, we had strength across pretty much every part of our portfolio across every customer type, on-prem and cloud, every geography, we've raised the full year guide. We've raised Q2 guide. We feel really good about the momentum of the business, and we'll tell you more as we get through the year. So super excited.
Thank you, David. I'll pass it over to George for closing comments.
Thanks, Kris. With broad-based momentum, we delivered an exceptional start to fiscal year '27, exceeding our guidance on every metric, strengthening our conviction in the durability of demand and underpinning our confidence in our materially higher expectations for the year. The NetApp platform addresses a wide range of customer requirements, helping to operationalize AI workflow and accelerating cloud journey, driving new customer wins and deepening existing relationships. Our ongoing innovation continues to strengthen the value of the NetApp platform and at our upcoming Insight conference we'll showcase new solutions that unlock value for AI and in high-growth markets. We're building a durable foundation for long-term success, delivering sustained value for our customers and shareholders.
This concludes today's call. Thank you for attending. You may now disconnect.
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NetApp — Q1 2027 Earnings Call
NetApp — Q1 2027 Earnings Call
NetApp lieferte ein Rekord-Q1, hob die Jahresprognose deutlich an und sieht AI-getriebene, breit getragene Nachfrage als Treiber für nachhaltiges Wachstum.
📊 Quartal auf einen Blick
- Umsatz: $2,03 Mrd. (+30% YoY; +26% YoY ex. zusätzlicher Woche ~+$65M)
- EPS: $2,58 (Non-GAAP, +66% YoY)
- Operative Marge: 31,9% (+610 Basispunkte YoY)
- Bruttogewinn: $1,43 Mrd. (+29% YoY), Bruttomarge 70,6% (−50 bps YoY)
- Segment: All‑flash $1,31 Mrd. (+47% YoY); Public‑Cloud $206M (+28% YoY; +19% ex. Woche)
🎯 Was das Management sagt
- AI‑Plattform: NetApp positioniert sich als „AI‑ready“ Datenplattform, die Daten in place für AI bereitstellt (kein kostspieliges Verschieben von Daten).
- Marktwachstum: Breite Nachfrage über Regionen, Branchen und Kunden‑größen; starke Win‑Rate bei großen AI/VMware‑Migrationsprojekten.
- Akquisitionen: DataPelago (In‑place AI‑Processing) und JetStream (Cloud‑DR für VMware) ergänzen AI‑ und Cloud‑Funktionalität.
🔭 Ausblick & Guidance
- Q2: Umsatz $2,1 Mrd. ±$75M (Midpoint ≈ +23% YoY), Bruttomarge 67–68%, Operative Marge 30,9–31,9%, EPS $2,54–2,64 (Mid $2,59).
- FY27: Umsatz $7,975–8,225 Mrd. (Mid $8,1 Mrd. = +17% YoY), Bruttomarge 68,1–69,1%, Operative Marge 30,3–31,3%, EPS $9,73–10,03 (Mid $9,88 = +22% YoY).
- Risiken: Volatilität bei Komponentenpreisen, Produktmix (mehr Produktanteil drückt Margen) und Unsicherheit, ob beschleunigte Käufe nachhaltig sind.
❓ Fragen der Analysten
- Nachhaltigkeit der Nachfrage: Analysten fragten nach Pull‑forward vs. strukturellem Nachfrageanstieg; Management bestätigt breit getragene Stärke, nennt Pull‑forward jedoch als kleinen Anteil und gibt keine quantifizierte Aufschlüsselung.
- Produkt‑Bruttomarge: Diskussion über Timing der Pricing‑Maßnahmen; Q1 besser als erwartet, Management erwartet moderate weitere Verbesserung gegenüber vorheriger Guidance, aber Quartals‑Schwankungen möglich.
- Inventar & Supply: Inventaranstieg zur Sicherstellung von Komponenten (NAND etc.); Management sieht das als vorsorgliche Maßnahme zur Absicherung von Wachstum, gibt aber keine detaillierte Allokation zu Kundenaufträgen.
⚡ Bottom Line
- Fazit: Starke operative Hebelwirkung und deutlich angehobene Jahresprognose bestätigen, dass NetApp momentan vom AI‑ und Cloud‑Tailwind profitiert. Für Aktionäre ist das positiv, allerdings bleiben Margen‑ und Nachfrage‑Risiken (Komponentenpreise, Mixeffekte, möglicher Pull‑forward) zu beobachten.
NetApp — 2026 Evercore Global TMT Conference
1. Question Answer
All right. Good afternoon, everyone. Really it had with us with Sam Jabra, CFO of NetApp. Sam, thanks a lot for your time. Before I get into all the questions that I have, I'm just going to read the Safe statements for NetApp. .
Today's discussions may include forward-looking statements regarding Net's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in our most recent 10-K and 10-Q filed with the SEC and available on our investors website at www.netapp.com. We disclaim any obligation to of information in any forward-looking statement for any reason. That out of the way. Sam, thank you very much. Always appreciate your time.
Maybe before I kick into all the questions that I have and there's a lot going on, you folks reported earnings a week ago or so. Maybe just spend a couple of time to use a quick recap on the saw in April quarter, you obviously gave a full year -- just spend a couple of minutes on just recapping the audience and we'll take some questions from there.
Let's -- first, thank you so much for having me. Happy to be here. So yes, we did report last week. We basically reported revenue uptick relative to last year as well as sequential. We did see some nice broad-based strength in demand throughout the quarter. granted. We have also seen some commodity price increases. And so when you look at it, there's -- there were some accelerated demand as well.
However, our Q4 numbers did not reflect the -- who had minimal impact in them from those. We are seeing some good momentum in the business with the enterprise IT spending improving as well as enterprise AI activity as well improving. And so this is what we -- when we looked at the trends going into fiscal '27, we basically put all of this information together so that we can provide the best outlook, and that's what our guidance reflects. .
Got it. And before I get into all the questions around your guide, maybe the 1 thing that did come up a bit is just the Google relationship. I know you folks obviously had a press release on this on April 16. You called it out a couple of times around the ELA.
Can you just talk about what is this relationship with the Google Distributor cloud really entail? How long is the ELA and kind of what goes into it?
Yes, of course. And so -- this -- the nice thing about the Google agreement, it's in the -- it is in the hybrid cloud segment. This is the way to think of it. It's -- we had -- so we started with enterprise agreement with Google back in October 2024. And so what we announced in Q4 is an expansion in price agreement. It is for Google distributed cloud environments that are more secure environments addressing sovereign and highly secured type of use cases, think of things like more of a public sector type applications or more highly secure as well as potentially in national security type of applications.
The nice thing about this agreement is it pretty much gave us a couple of things, some TAM expansion because this is an area that we haven't necessarily basically expanded where we -- our footprint there. In addition, in that show our capabilities in terms of security and the ability to sort of provide data infrastructure for very highly secure environment. We did call it out in the quarter, it had a nice impact to our product revenue as well as our product across a -- as we think through it going forward, it is a 4.5-year type of agreement. And so going forward, it will have the typical type of hybrid cloud agreement where we have hardware, software and support. And so there will be some support revenue attached to it.
There will be some product revenue in the future as when we sort of put more deployment. But we -- but those would be part of the normal course of business. And as we think of the economics over the duration of the agreement, it's a typical hybrid cloud type of agreement economics.
Got it. Perfect. One of the topics that's been coming up a fair amount, especially after your earnings call, but also a bunch of other earnings call has been this consumer how much is the contribution that you're focusing is down by pole lines versus truly good end demand, right?
And I think you folks had like 12% growth in Q4. I think Q1 was guided for 17%. There's an extra week over there. But demand is much better that I think folks thought. How do you kind of think about end demand trends versus potential pull-ins that could be helping you? Just talk about how do you segregate those a bit?
So when we think of the business dynamics, we did we're seeing broad-based strength in demand. And now any time price increases, there could be different behaviors in the market by customers. some customers could accelerate their demand, but others may not have the same flexibility could put some of the purchases on hold.
So it's a mixed bag in terms of impact to the business. But when we look at really what's the underlying drivers, we think it's -- we think we're seeing some improvement in enterprise IT spending partly driven by enterprise AI spend as well. Now when you put it all together and they look at Q1 and the fiscal guide. Obviously, we are also aware of potential accelerated demand pull forward. And all of this is reflected in how we guided our business.
Got it. Memory is other topic that obviously has been kind of front and center for you and I'm sure for everyone else. Just talk about what are you seeing from a memory environment right now? Do you sort of expect this to be a multiyear issue? Or how do you kind of think about navigating this, and if it is a long-term issue, how is NetApp preparing in terms of supply commitments and agreements and maybe a drive on the you obviously gave a fiscal '27 guide. Do you have the bids, the LTs in place to ensure you get the capacity you need.
So when you look at sort of what happened over the last couple of quarters, we saw commodity prices increase at a very fast pace. In parallel, obviously, we had -- we implemented price increases last quarter to protect our profitability. And really, the way it works is we pass the commodities to our customers as is customary in the business we operate in or the industry we operate in.
As we think through fiscal year 2027, we look at this basically impacting mostly our product gross margin. And we think Q1 could be the trough, and we may see some we should see some gradual improvements from there for the rest of the year. And by gradual improvement, I don't mean step function improvement. I mean, sort of a bit of improvement as the year progresses. If we continue to see commodity price increases, we will be taking additional pricing actions to protect the profitability of our business.
The way we look at it is, obviously, we look at the over portfolio, and we adjust our crisis, depending on where we see cost increases. With respect to the supply environment. Look, we've -- we're operating -- we're clearly operating in a supply-constrained environment. There are certain shortages that show up every now and then, but we've been navigating it so far successfully. We -- when we look -- when we -- the way we operate with our partners and our suppliers is we work with them on our outlook, and we understand what their supply availability is, in some cases, we have commitments in terms of deliveries for quite some time. At this time, we believe we can secure the supply needed for us to drive our outlook for fiscal '27.
Got it. every company has their own kind of set of ways that they're going through memory mitigation efforts, I would say, pricing recently, 1 of the tools, but I think there's other tools that folks have talked about, you some beyond the price increase, which I'm sure everyone is saying. What are the other options or vectors you have in terms of managing the memory headwinds? And how are you mitigating it beyond the price increase? .
I mean, we're -- we -- of course, I mean, you mentioned price increases, and that's something we look at. But we also have a very broad portfolio, which offers us and gives us opportunities to serve our customers in many different ways. When you look where the increases happen, the most -- they happen mostly on the all-flash side portfolio simply because this is where the commodity prices increased the most. But we saw some increases on the hybrid hybrid flash side of the portfolio, but not to the same effect. And so where customers are -- or maybe cost sensitive depending on the workloads, we're happy to offer hybrid flash solutions for their data infrastructure. .
But we also are happy to work with them on a consumption model, if they so choose or subscription model. We have Keystone, our Storage as a Service there, it is sort of -- the spend is spread over a few years, and that basically provides a different model for customers who want to sort of not put up the cash outlay upfront. In addition, we have our public cloud segment, which is a great business that's on the hyperscaler side, where we're happy to also offer that. And for customers who use multi-cloud strategy, and they have -- they use NetApp on their hybrid cloud as well as on the public cloud. This is sort of -- it basically gives them a whole suite of options to choose from, and they can across the whole, basically, a gamut, they can use also ONTAP, which is our data management operating system.
Got it. From your perspective, how are customers contending with this memory issue, right? Are they looking at hybrid or HDD or in saying it's slower, but a better alternative for me, maybe given what's happened in the pricing right now there saying, we'll just buy storage or less bits in our box. I'm just talk customers dealing with this because it's a quite a bit of inflationary pressure for them as well.
It's -- I would say we're seeing various approaches. It depends on the type of customer, the size of their business, the workloads, what they're trying to really achieve and what their goals are. For some of the customers who have already a hybrid flash estate, and they don't necessarily need to go to all flash. That could be an option. It could still -- we could still upgrade or extend their data infrastructure using hybrid cloud for other customers who want to be sort of on the forefront of enterprise AI, they may want to go with more of a high-performance type of all-flash or high capacity type of all flash.
So I would say it all depends. Now in Q4, for instance, we didn't see much demand elasticity. We've always thought and we've always said that our customers budget in dollars, and this is how they basically deploy their budgets and to basically buy data infrastructure. Some of them may see the need to upsize depending on their business priorities because at the end of the day, they would reallocate their budgets based on business priorities. Others could choose to make different decisions, either sort of downsize or choose to delay their purchases. It all depends on their financial flexibility as well.
Fair enough. I think you folks disclosed this kind of AI demand number, which is like some of the AI deals you signed, I think, every quarter, and it was like 500-plus deals on the last call, which is pretty big step up from the prior quarter is like 300, I think, right?
So when you think of these AI deals that are going up dramatically, what is it that these enterprise customers is in the most enterprise -- what is the bottleneck they're trying to solve with storage when it comes to AI training because they do think storage is a pretty big bottleneck for them to deploy it in-house? And where does NetApp fit into that narrative?
So we do break out the various types of engagements when it comes to enterprise Half of the engagements that we saw in Q4 were on data preparation and data lake modernization. The other half was split in 2 categories. somewhat for inferencing and some on model fine tuning. The -- so when you think of data lake modernization or data preparation, it could be situations where some of the customers have their data siloed into various silos, and they want to sort of have a unified view of it and they basically are modernizing their infrastructure to enable them to have access to their overall data estate wherever it resides in the world and -- or in their sites.
So that's sort of 1 of the potential use cases. It could be that customers are utilizing AI much more from a day-to-day perspective in their activities or they're starting to do that, and that's sort of where inferencing comes in, they want to be able to utilize their proprietary data that sits on their own storage devices, and so they want to upgrade that to be able to utilize it more for AI use cases. There's multiple reasons why and how they could be using -- they could be needing higher performance or high capacity data infrastructure. that we offer.
Is the way to think about how big is the potential when it comes to these AI-related revenue opportunities? Or how big could AI revenues get for NetApp over time? .
Look, if the -- almost every -- I mean I went from experimentation to almost becoming a top priority across the board. And so we view it as incremental opportunity for us. It will be a nice tailwind as more and more enterprises sort of implement AI. It's, I would say, a bit early to quantify -- but it does feel like there's a certain momentum that we're feeling in the business. Yes, it's -- the way we think of it is -- it would present potentially a tailwind. How much of that is quantified today, it's probably too early to talk One of the products that you folks have, the AI data engine, which was, I think, GA recently as last quarter at fiscal Q4 for you folks.
How should we think about what does AI data engine really do for customers? Is it more for a brownfield way to get more of the wallet share? Just talk a little bit about what's the intent of this, what the monetization does this look like over time?
I mean the way we think of data is that it has certain gravity, and we would like to bring AI to the data as opposed to bring data to the -- and so this is the purpose of IDE. It's enabling our customers to understand much more about their data to provide more data about their data for them so that they can 1 improve the lit of the data that they have on their data states but also be able to utilize data more effectively for AI use cases. And so initial indications are very positive from AIDE.
We see really a couple of areas for us here and how this could work, at least based on the initial views -- on 1 side, we're -- when we engage with customers who are already on existing customers who are already on NetApp infrastructure they basically, that could potentially create some additional software or could be some software subscription model, where we could help them improve the quality of their data, their visibility into the data and potentially also attach that to storage. And there's also some nice uptick of interest from new customers who are wanting to have a better understanding of what AI does -- and that could present opportunities for us where we could basically not only delivery IDE, but also store storage solutions for that. So it's -- it's an exciting area of opportunity for us. .
Your public cloud business has been doing extremely well. I think it was up like high teens, 17%, 18%, excluding the divestiture dynamics, right? Just talk about like what's sort of driving the growth rates on the public cloud side? And then I think you always said that, hey, there's a healthy mix of new customers and existing customers. Where is that SKU going? And what's really driving the strength there? .
Yes. So as you noted, public cloud for us grew around 17%, 18% in fiscal '26 when we exclude spot from the previous year numbers. At the core of that first party and marketplace, which is really the drive -- the growing -- the growth engine of the public cloud business grew at around 30% year-on-year. As we go forward, we anticipate to see similar type of dynamics. And now that the first party and marketplace is it's become even a bigger portion of the business that should drive really a nice growth profile going forward. It is also a very highly profitable business for us. I mean, we -- our target -- gross margin target range is 80% to 85%, and we've been operating at the high end of that range for a few quarters now. When you think of the customer mix, yes, it is a mix of existing and new customers. .
It does also offer us the opportunity to attract customers that typically aren't necessarily serviced through the on-prem business. customers who are cloud native or basically started on the cloud that typically wouldn't have -- I wouldn't want to sort of -- wouldn't have NetApp on their on-premises are exposed to NetApp and to ONTAP. And so it does sort of track a new set of customers. It's a wide range of sizes, wide range of type of customers, I would say. But -- the nice thing is it's growing at a nice pace, and it is a highly profitable business for us.
And just on the margin side, right, I mean, I think it was like north of 85%, I'm not receiving last quarter. It was better than what you folks had thought. But is that the right -- I mean, is that the right margin framework to think about? Or what are the puts and things that drive the margins, like first body versus not, it appears like what drives the puts and takes around it. .
The long-term range we published is 80% to 85%. And as you correctly noted, we've operated slightly higher than that. We were like 85.7% in the last quarter. It's too early for us to really revisit our range. We think that the range is still valid for the next -- for some time. because the way to think of it is there's a mix of things. Obviously, it's a highly -- it's growing at a nice pace. And so -- and if we need to, for example, the -- in a portion of it, we do have some some assets associated with the capacity.
And so if we do need to refresh some of those assets, we have enough -- we think within the range where it is appropriate for us to refresh as well as continue that growth going forward? Could it be -- could it move in a different direction? Potentially, I'm not going to say no, but it's a bit too early for me to update the range. .
Got it. Keystone is something you talked about a little bit earlier, too, but it's certainly a part of the toolkit customers have to navigate with these memory challenges. From your perspective, are you seeing customers willing to say, in, I don't want to do a CapEx model. I'll do an OpEx model and go with Keystone or are they sort of different tracks that it's harder to get them to convert to Keystone versus CapEx? .
Keystone has been growing at a D&I space. I mean fiscal Keystone revenue was up around 65%. So it is a nice -- a smaller portion of our business, but it's growing at a nice pace. I mean, yes, our Keystone Storage as a Service has done really well. It continues to build momentum. And it is an alternative or a potential alternative for customers who don't want to put the cash outlay or put in place a bigger CapEx upfront.
I don't think we've seen so far a real trend in that month, but we obviously are ready for it. If our customers really want to sort of opt for storage as a service type of model as opposed to a CapEx model. And this is -- in some ways, this is the nice advantage, the breadth of our portfolio offers. We're able to do all flash, HDD Keystone, public computing, many options. As long as we're able to sort of serve our customers and maintain that sort of customer life cycle revenue.
Fair. Is there a way to think about on Keystone, like what's sort of the unit economic profile for a Keystone engagement versus a kind of a traditional engagement on a product base over 3 years of how long you want to think about like what are the unit economics of that in Keystone versus on a traditional sale?
I mean the way to think of it, I would say probably over a 3-year period, the economics are more or less equivalent. Longer than that, probably Keystone has a nice advantage because obviously, you extend that sort of revenue stream. But the -- but for us, what matters really is what solutions are we solving for our customers and how we solve is the best way possible, right? .
That's fair. Your fiscal '27 guide, right? Obviously, you got for revenue growth to be in the higher single-digit range on a top line basis. EPS, I think closer to $9 number, right, essentially. But to me was notable as it was like, hey, you folks talked about gross margins being down 220, 230 basis points year-over-year. But operating margins, I think we got it down like 50 basis points. So clearly, you're doing a lot on the OpEx side.
So let me just spend a little bit of time on what are the OpEx controls you're executing on to shield your bottom line so your free cash flow? And then are these durable savings? Are these transient savings? How do we think about that?
I think it's -- the outcome of that. I mean when you look at the transition year-on-year and how sort of the top line at the midpoint is guided versus where the operating margin is guided. The outcome is a combination of both some nice uptick on the revenue as well as basically disciplined management of OpEx or at least how we think of we project our OpEx and execute our business, generally speaking, when we look at our OpEx in the future, we plan OpEx growing at less than half of the growth of the revenue growth. .
And that's sort of done in a way to allow us to maintain certain operating leverage in the business. And so fiscal '27 is pretty much following the same type of approach. When we look at the OpEx itself, we're looking at it obviously as an investment. We continue to invest in our sales capacity and our go-to-market capabilities. Would it make some nice investment in fiscal '26 where we did say at the beginning of the year, we were adding some sales capacity. We did some of that.
We continue to think that the opportunity for us is there to drive top line growth, and so we'll continue to do some of that in fiscal '27. And on the R&D side, we want to continue to invest in the technological capabilities that we have, the differentiation, the AI data solutions. But we do that based on going after the highest ROI type of projects. And in parallel to look at the rest of our investments and we deemphasize areas that we think are not -- are either not driving the growth we want to see or they're not necessarily expected to deliver on the return. And so we do that on a regular basis.
When you sort of then combine the top line growth with really driving OpEx at a much lower growth relative to the revenue growth, that gives us some operating leverage, and that's how we plan the business.
Got it. beyond the whole AI investments that all the hyperscalers is doing in more, a recent thing has been like you're seeing a lot of uptick in spend for x86 servers for general purpose service right now. For inferencing deployment, the general there's a lot of demand for x86. I think a lot of enterprise comments are to like Dell, HP and so on.
I guess, maybe the question for you is that historically, when you see this big uptick in compute spend, especially as enterprises storage tends to follow at some point soon after that. Do you expect that kind of historical correlation to hold up? Or think there's something different in inferencing that maybe the lag is longer? Or how do you kind of look at all the server spend and say, we'll get it on the store side at some point.
I think we should -- I mean, when you deploy such an amount of compute. Do you want to make sure that it's run in the most efficient way possible for whatever purpose we're trying to use it for. And so to me, it feels rational that it is rational to see storage capacity follow, because you want to -- not only are you sort of wanting to make sure that they're operating very efficiently. There's going to be some data generated when you start thinking of agenting AI or inferencing.
There will be data generated as part of, obviously, all this process and the data has to reside somewhere. And so naturally speaking, I would expect to see some storage follow-through there. I think it's a bit too early for me to quantify or to even sort of define the time lag. But we're rationally speaking, we should see some of that happening.
Got it. What are your worriers that's been a bit more challenging as being the public federal government, the public vertical, if you may. It's been weak for several quarters for a lot of companies, not just in fairness. Can you just maybe just talk about how big is the federal business for you today? And then what are you sort of expecting from that business in the construct of your fiscal '27 guide that's out there? .
So for us, the U.S. public sector business, which includes the federal business is approximately 10% to 11% of our revenue. This is where it sort of has run for quite some time. Would it see subseasonal sort of movements throughout fiscal '26, except for the fourth quarter where we started to see some really nice uptick. In Q4, U.S. public sector was up almost 20% year-on-year. So there was some nice recovery that we experienced there.
Now that we think there's already sort of the budget passed and there's a little bit more clarity. We think this business should more or less return to a normal type of seasonality for the U.S. public sector. So that's what we should end -- at least that's what we're anticipating going forward.
Got it. you touched a little bit on capital allocation. You folks exited with a very strong balance sheet in Q4, $1.4 billion, if I'm not missing on net cash. Just talk about how do you think about the free cash flow generation for the business and then extend that a bit? And how do we think about our capital allocation as well over time? .
Yes. So when we started talking about the Q4 execution in fiscal '26. We should have actually mentioned how well we did on the cash flow generation. We did really phenomenally well in 2026. The business generated quite a bit of cash and we also obviously continue to do our typical capital return through dividends and through buybacks.
And so going forward, we expect to maintain a similar type of capital allocation where we want to return up to 100% of our free cash flow to our shareholders through dividends as well as buybacks.
The way to think of our cash flow, I would probably -- it should be -- it should follow similar type of dynamics that we've seen in the last couple of years. Our operating cash flow typically tracks our non-GAAP net income and that this coming year should be no different. And so we anticipate to still be highly cash generative.
M&A? Where does that sort of fit into the top process so it's more bolt-on.
Yes. I mean we're a technology business, right? We want to make sure we maintain our technological [indiscernible] advantages. And so if there's a need for us to do anything on it from a tuck-in perspective, we won't hesitate to M&A. That's -- I mean just -- you'd expect that from a technology business like ours. .
Fair enough. And those are all the questions I have some. So maybe I'll turn it back to you any closing comments, anything I did not touch on that we should be aware about as we think about NetApp going forward?
I think we've covered a lot of ground.
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NetApp — 2026 Evercore Global TMT Conference
NetApp sieht breite Nachfrage (Enterprise IT und AI), navigiert Speicherpreis- und Lieferdruck mit Preismaßnahmen, Portfolio-Mix und OpEx-Disziplin.
🎯 Kernbotschaft
- Kernaussage: Management signalisiert anhaltende Nachfrageausweitung durch Enterprise‑IT und Enterprise‑AI, zugleich kurzfristiger Druck auf Produkt-Großmargen durch gestiegene Speicher‑Commoditykosten; Gegenmaßnamen sind Preispass‑through, Portfolio‑Verschiebungen und Kostendisziplin.
🚀 Strategische Highlights
- Google‑ELA: Ausbau eines 4,5‑jährigen Hybrid‑Cloud‑Deals für stark abgesicherte/sovereign Umgebungen, inklusive Hardware, Software und Support; erweitert adressierbaren Markt.
- AI‑Offensive: AI Data Engine (GA) soll „AI to the data“ liefern, Datenqualität/Visibility verbessern und als Software‑Subscription plus Storage‑Attachment monetarisiert werden.
- Cloud & Keystone: Public‑Cloud (1st‑party/Marketplace) stark wachsend und sehr margenstark; Keystone (Storage as a Service) wächst schnell (~65% YoY) als alternatives OpEx‑Modell.
🆕 Neue Informationen
- Deal‑Details: Google‑Vertrag konkret: 4,5 Jahre, Fokus auf verteilte, besonders sichere Cloud‑Instanzen; erzeugt Produkt‑ und Support‑Umsatz über Laufzeit.
- AI‑Usecases: Aktuelle AI‑Deals splitten sich ~50% Data‑Preparation/Data‑Lake, Rest auf Inferencing und Model‑Fine‑Tuning — konkretere Deal‑Mix‑Färbung als bisher.
- Memory‑Ausblick: Commodity‑Preisanstieg trifft Produktmargen; Q1 als potentieller Margen‑Tiefpunkt, danach graduelle Erholung, weitere Preisanpassungen möglich.
❓ Fragen der Analysten
- Pull‑ins vs. Endnachfrage: Analysten hinterfragten, wie viel Wachstum „vorgezogen“ ist; Management sieht breiten Nachfrageanstieg, berücksichtigt Pull‑forward in der Guidance.
- Memory & Supply: Kernfragen zu Dauer des Speicher‑Inflationsdrucks, Lieferzusagen und Kapazitäts‑Commitments; NetApp sagt, Lieferzusagen bestehen und sie können Outlook bedienen.
- Margen & OpEx: Wie dauerhaft sind OpEx‑Einsparungen? Antwort: Disziplinierte Investitionspriorisierung, OpEx‑Wachstum soll <50% des Umsatzwachstums sein; teilweise strukturell, teilweise taktisch.
⚡ Bottom Line
- Implikation: Für Aktionäre bedeutet das: solides Nachfrage‑Momentum und klare Wachstumshebel (AI, Cloud, Google‑Deal), aber kurzfristiger Margendruck durch Speicherpreise. Management adressiert das mit Preisanpassungen, Portfolio‑Steuerung und Kostendisziplin; das Risiko bleibt commoditärer Speicher‑Trend, Upside durch Cloud/AI‑Monetarisierung.
NetApp — Bank of America 2026 Global Technology Conference
1. Question Answer
Hi, everyone. Thank you for joining us here on day 1 of BofA's Global Tech Conference. Delighted you could all join us here today. I'm Wamsi Mohan. I cover the IT hardware and supply chain space here for Bank of America. Thank you all for coming.
I'm delighted to welcome Wissam Jabre, who is the CFO of NetApp. And I have to be careful because I've known him in other roles prior to that. So well, welcome Wissam, a pleasure to have you over here and excited to hear for the next 30 minutes that we've got with a short amount of time about your outlook on NetApp story.
Thanks so much, Wamsi, and happy to be here and excited to share more.
Yes. And we have Jeriel from IR as well. Oh yes, sure. We'll make sure that we have -- you want to go ahead and cover the disclosure or I can do it, too, if you'd like me to.
That's fine. I'll go ahead and do it. So hey, today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. NetApp disclaims any obligation to update information in any forward-looking statement for any reason.
Excellent. Okay. With that out of the way, maybe I just want to point out Jeriel from IR is here, too, if you have any follow-up questions afterwards.
So what an exciting time to be in hardware, right? And I know you spent a lot of time on software resources within NetApp, and that's a differentiating viewpoint. But for infrastructure, maybe is the right word to use as opposed to hardware, but it is an exciting time to be in infrastructure. So maybe you can talk to our audience here a little bit about how is NetApp participating in this growth in infrastructure that is driven by AI?
So look, we've been sort of looking at and tracking our AI wins for quite some time. And as we disclosed most recently for Q4, we had around 500 of them. And what matters here is really the trend that this has followed. It's more than doubled year-on-year and continues to grow on a sequential basis. So it is a sign that there's more and more activity that is increasing in the enterprise AI space. And for us, this is very exciting because, obviously, it does, in some ways, lead to some of the improvement in IT or enterprise IT spending.
As we look at the infrastructure or the offerings that we have, we do have basically high-performance all-flash solutions that -- where we could participate on the AI side. And we also have our new offering, AFX, which is our disaggregated architecture in combination with AIDE that could also be a good offering for the AI space.
So maybe to step back for a second, right, like you're involved in the domain of data storage, data protection, making sure that the infrastructure runs seamlessly based off all this data growth that's happening around -- we were talking earlier with some companies where we're talking about data growth that's maybe 25% to 30% off of very large numbers. So now we're talking about like some big deployments.
So as you think about the market and your opportunity for growth, what should investors sort of think about in terms of the incremental maybe growth from baseline, growth that's provided by AI? And then where are we within sort of a more general replacement cycle for storage assets? It feels like a lot of the hardware assets are -- have been sweated for some time, and now it feels like they are ripe for a refresh. So I would love to get your thoughts on that.
I mean, look, we've been on that journey of moving towards the all-flash upgrades, if you like, from the 10K hard disk drive for quite some time. And we've seen our installed base basically as of almost churning approximately around 1% a quarter. We're now at around 48%. And so that sort of gave us a nice growth vector over the last few years.
Now when you look at where AI comes in is I think we should expect to see that all-flash transition continue, even though now with the current prices on all-flash and the dynamics that could have a little bit of an impact given the increase in prices. But we have a very broad portfolio that -- where we could offer our customers many alternatives as well. But in addition to sort of that transition, we think that all-flash -- sorry, AI or adoption of AI in the enterprise, especially in the inferencing space and the data preparation, data lake modernization space could provide some nice tailwind in addition to what the industry has been experiencing so far.
Okay. So as we think about this memory pricing, right, and this has been sort of front and central for a lot of customers and organizations to deal with, how are you tackling the memory pricing issue?
I mean, for us, it's an input cost. And what we've done is we've basically had adjusted our prices. We increased our prices in the past quarter to pass the commodity costs as is customary in our space to our customers. And so we look at it from a portfolio perspective, and we adjust our prices depending on the various impact from an input cost.
Okay. And what has been the receptivity to that sort of price increases from your customer base? Are you seeing any change in the customer behavior in terms of maybe trying to accelerate some purchases, maybe pulling forward anything? Like what are you seeing in the behavior of your customer base as you're pushing together some fairly significant price increases, multiple price increases through the course of the quarter?
Yes. I mean in the past quarter, I would say we haven't necessarily seen much demand elasticity. And when you look at the way customers budget, they do budget in terms of dollars. So -- and they do spend their budgets based on dollars. Having said that, any time you have price movements or larger price movements, you'd expect some different behaviors in terms of some accelerated purchasing, for instance, and so on. But for us, in Q4, we really saw a minimal impact to our P&L from any of that accelerated demand. And then when you think of it, not all customers have the financial flexibility to do that.
Yes. Yes. No, that's fair. In your last earnings, you noted like that some large deals came through. I think you press released a relationship with Google that basically was multiyear. So how should we think about that relationship? And what is the way in which it flows into your P&L over a longer period of time?
Yes. So we did note the agreement with Google, which is on the Google Distributed Cloud side that gave us a bit of benefit in product revenue and product gross margin in the fourth quarter. That was really an expansion of an agreement in place that has been with Google since October 2024. And so the way to think of it is it does basically serve the Google Distributed Clouds in the sovereign and secure type of environments. And in Q4, we had some revenue associated with it. And as we think through -- it's a 4.5-year agreement. And so over the next 4.5 years, we will be recognizing some support revenue as we typically do in those types of engagements. And also, we would be recognizing product revenue when we ship the product associated with it. And so that's -- it is included in our Hybrid Cloud segment.
Yes. I can't hurt to see Google raising $80 billion overnight to put in AI infrastructure. So that's kind of nice. Maybe, Wissam, just to like now talk about product gross margins, right? So I think you guys spoke about this on the call that Q1, you see the lowest product gross margins that you expect for your next fiscal year and then it should improve from there. So can you talk about why that will be the case? And what are some of the things that give you the confidence that, that trajectory is the right trajectory?
Yes. Look, at this time, this is what we see. We see Q1 being the trough, and we expect gradual improvements for the rest of the year. And it's sort of -- again, I'm not expecting necessarily a step function improvements. I think gradual improvement. That's because as we progress through the quarter and as we get into the next quarter and beyond, we start seeing more and more of the effect of the price increases that we implemented in the past quarter take effect and flow through our P&L. It does take a bit of time lag typically. We -- historically, it's taken sometimes up to 3 quarters, but we've tightened a little bit our contracts to start seeing the effect a little bit earlier.
Okay. There's been some of these memory suppliers or basically every memory suppliers talking about longer-term agreements and the potential to sort of fix some level of both pricing and capacity out in time. Is that something that NetApp would be interested in undertaking? I know like typically, this is more hyperscale domain like to do larger deals that look out like over a longer period of time. Is that something that you would entertain? How are you thinking about supply, your ability to get capacity as you need it?
Yes. I mean we're in continuous discussions with our partners and suppliers to be able to secure the various parts of the components that go into our products. There's no doubt we're in a constrained supply environment. And there are -- and there's -- over the last couple of quarters, there's -- sometimes we experienced shortage in some areas, but also lead times are also extending. But we work very closely with our suppliers. And we're -- we engage with them depending on the different needs that we have, the horizon that we have and our volumes as well as the costs. And so we're open to various arrangements as long as it helps us sort of secure the supply we need for our products.
Now when you look at where we are today at this time, we believe we have -- we can secure the adequate supply we need for our -- for the outlook we have for this fiscal year.
So as you think about this fiscal year, right, you have sort of an extra week dynamic in your fiscal 1Q and you have pricing flowing through as well at maybe a higher pace than what you already realized. So as you think about both of those and think about the seasonality of how this year plays out, how should investors calibrate to that?
So when you look at sort of our guide for Q1 and the guide for the fiscal year, yes, as you noted, Q1 has an extra week, which we've quantified to approximately $65 million. But then when you sort of factor that out and you look at the seasonality with respect to first half versus second half, we are anticipating a typical sort of historical pattern with respect to seasonality for first half versus second half.
And then when you look at our Q2 to Q4, taking into account the midpoint of the FY '27 guide, you compare Q2 to Q4 FY '27 to the same period in FY '26, that basically implies around mid-single-digit percentage growth. So that captures what we see today with respect to how FY '27 and Q1 will shape up.
Okay. That's helpful. So why should -- so maybe conversely, right, like why should that be the right seasonality, especially as you're driving pricing increases? What's your underlying assumption about pricing as you go through the course of the year? Is there incremental price increases that are baked into that guide? Or is it something that you're only thinking about Q1 where those pricing impacts are taking place? And then as the market evolves, you will decide? How should we think about that?
So within sort of the fourth quarter, we saw some really good broad-based strength in demand. We did obviously talk about our price increases, but we also have seen some nice uptick in enterprise IT spending, part of it driven by added increased activity in the enterprise AI space. And when we look at the fiscal year '27 guide, it comprehend all of these various pieces that I just mentioned. In addition, the way to think of it is if we continue to see commodity costs increase, obviously, we won't hesitate to take pricing actions to mitigate the impact to our P&L and protect our profitability. But so all of this basically is how we think of the fiscal '27.
Okay. And just to be clear, like I mean, as you think about the environment, I mean, would you say that we're still expecting an inflationary environment for the rest of your fiscal year in terms of commodity pricing? And are there things that I know like 6 months ago, you were in a favorable inventory position, for example. Is there any opportunity for that at all? Are you leveraging your balance sheet in any way to take advantage of any maybe circumstances that might show up?
As I mentioned, we work very closely with various parts of our supply chain and our suppliers. And if there's a need for us to do things like that, we won't hesitate. At the end of the day, what we -- in terms of priorities, our first priority is to secure our supply. Of course, we work on balancing supply with cost and other types of activities as we think of our business. But yes, we won't hesitate if we need to.
When you think about -- you mentioned earlier like the breadth of the portfolio. And you have the opportunity to maybe shape demand a little bit with do you -- what are the configurations where you put people with an all-flash versus what you're putting in hybrid versus what you're putting in cloud? What are customers doing with respect to each of these at the moment given that flash pricing has increased so much? Are they making other choices? Are they making adjustments? What are your salespeople telling your customers to do here?
It's -- thanks for talking about our broad portfolio. It is really exciting to see the various options that we can offer our customers in this environment, right? In addition to all-flash, we have hybrid flash, which is based on basically hard disk drive as a media. In addition, we have Keystone Storage as-a-Service and our Public Cloud business that has done really great also over the last few years.
And so when you look at Q4, we did see some nice increase in our all-flash business. But we also saw an uptick in the hybrid flash business, which is the -- based on other types of media like the hard disk drive, which is interesting because in the prior several quarters, we have seen sort of more or less a steady decline. And so that could be potentially driven by what the all-flash prices have done. But it's a little bit too early to tell. What's important, though, is our ability to serve our customers wherever they need to be. And so if they want to upgrade their hybrid flash data sort of infrastructure, we're happy to help there. And if they sort of don't want to do a big upfront CapEx investment and prefer to do more of a consumption-based approach, then we can offer Keystone Storage as-a-Service. And in some cases, if they also want to use ONTAP in the multi-cloud, Hybrid Cloud and Public Cloud environment, obviously, we can offer our Public Cloud solutions.
You've seen real strong growth on the Public Cloud side. I know the reported numbers were impacted by the spot divestiture for some period of time. You have lapped that now, like your growth looks very solid. The incremental profitability looks extremely strong. So -- and you've been moving up your profit targets, gross margin targets on the public cloud side. So can you just talk to us a little bit about what is the right growth trajectory to think about in this kind of a constrained environment, should we be expecting some kind of acceleration that can come in Public Cloud?
And secondarily, like what is enabling such high gross margins and continued increases in those gross margin rates?
Yes. So the Public Cloud business has done really great. I mean when you look at fiscal '26, it grew 17%, 18% when you account for the Spot divestiture on a year-over-year basis. Within that, the first-party and marketplace, which is really the core growth of that business grew at around 30%. And so it's growing at a really fast pace. It did deliver in the last couple of quarters, slightly more than 85% gross margin. And our target gross margin for that business is 80% to 85%. So it's operating at sort of that high end of the target range and a little bit exceeding it.
The outlook going forward is sort of a similar set of growth. I mean the growth is still sort of healthy. We expect it to continue to grow, especially in the first-party and marketplace. And sort of when you look at that it should help provide also a nice tailwind to the corporate gross margin given that, obviously, it is operating at a much higher gross margin than the corporate gross margin.
With respect to what's driving some of the dynamics in the margin itself, there's really a couple of things. We had a bit of depreciation roll-off from the initial hardware that was installed over time. But also there's more software content as we continue to improve on the offering and make it more and more competitive. Obviously, some -- basically, there's more software content with that. And that shouldn't -- basically that type of dynamic should continue in the future.
Okay. And just on the Public Cloud side, right, your implementation across the various public clouds is slightly different. And I think you originally started off with NetApp Azure Files, which was like a fairly large part of that Public Cloud business. As you think about the -- maybe how much have we diversified today in terms of the various Public Clouds? And what is sort of like your expectation of which Public Cloud might be able to contribute the most in NetApp's growth if you look over the next, call it, 2 years?
Look, all 3 are doing great. I mean we have partnerships with all the top 3 hyperscalers where they offer our ONTAP software as a native software store software solution. And we see good traction in all 3 of them. And so the size, I would say, also depends on, obviously, where -- when the business started, but we see good growth in all 3 of them. And in terms of profitability, as I mentioned earlier, this business has been operating at really the upper end of the long-term target range for quite some time.
Yes. You guys have had a very consistent history of managing your OpEx really well. And in times where your revenue starts to accelerate, like you really get a lot of leverage in the model. And kind of as you look over the next couple of years based on your top line sort of growth expectations and maybe there's more upside with pricing. How should we think about the margin flow-through? How should we think about OpEx rates in general relative to the revenue growth rates?
Yes. I mean, look, we've made a concerted effort to maintain that operating leverage in our business. And you can see as we project revenue growth, we typically grow our OpEx at less than half of the revenue growth rate. Having said that, obviously, within that, we continue to invest in our sales capacity. We did add sales capacity in fiscal '26. We plan to do more in fiscal '27 as we see good momentum in the business. We continue to invest in our research and development. Obviously, we're investing in AI data solutions.
But as we do this, we also deemphasize some areas. And so we look at focusing on the higher return areas and sort of deemphasizing lower return areas or areas we're not necessarily as focused on. And so overall, when you look at the -- how we think and how we execute our investments from an OpEx perspective, it still keeps a certain leverage in the model where basically every dollar of revenue should add a little bit more to the bottom line.
Yes. I mean, obviously, NetApp's had a fairly long history now as a public company. So when you talk about incremental sales resources, like what are the areas that you're targeting for incremental sales opportunities that were maybe not already exploited by the company?
I mean there's -- as you said, we have quite a bit of presence globally in the various markets, but there's always a need for us to rebalance resources sometimes or there's areas, for instance, where we're seeing faster growth where we sort of want to put more. For example, in the AI front, we're putting a little bit more AI specialists that would help push that and become much more sort of focused on growing that side of the business. We continue to invest in areas like Public Cloud, for example, to continue to sort of drive that nice growth that's very highly profitable for the company. And we balance different geographic areas as well depending on the needs. So these are some of the few examples.
Okay. Okay. That's helpful. Maybe just talking a little bit about cash generation, right? Like you guys have done an amazing job with free cash flow and free cash flow margins. As you think about the potential growth here, especially with enterprises potentially having to do a big storage refresh down the road with AI you could have much better economics flowing through to cash. So how are you thinking about potentially deploying that cash? How much focus, if any, is needed on M&A? And how are you thinking about overall shareholder returns?
Yes. We've had really a great free cash flow generation in fiscal '26. So we anticipate similar type of trends into fiscal '27. We -- and as you noted, I mean, if the refresh really happens, that should give us a very nice tailwind from a top line perspective. And so the way we look at our capital allocation is very much consistent with last year where we want to return up to 100% of our free cash flow to our shareholders through dividends plus share buybacks.
And from -- we're also a technology company. And so we focus on making sure that we have a competitive portfolio. And if there's a need for us to do any tuck-ins or basically enhance our portfolio and that's a good use of our capital, we also look at these types of opportunities.
Okay. Well, we're coming up on time. We've only got a couple of minutes left. So maybe, Wissam, just to wrap. What do you think investors should be most focused on with respect to NetApp? Why do you think this might be a good time to invest in the company?
I mean, look, the -- we're seeing really broad-based strength in demand. Yes, we obviously recognize and acknowledge the potential risk of some of the accelerated orders. But essentially, we're seeing an underlying broad-based demand in our business driven by increased enterprise IT spending and partly driven by increased activity on the enterprise AI front. And so as we obviously progress throughout the year, we'll be updating more based on what we see.
Excellent. Well, thank you so much for being here. Really appreciate it, Wissam, and thank you all for joining us here today.
Thanks for having me. And excited to be here.
Thank you.
Thank you.
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NetApp — Bank of America 2026 Global Technology Conference
NetApp sieht steigende Nachfrage durch Enterprise-AI und Public-Cloud-Wachstum, kurzfristig belasten höhere Speicherpreise und ein erwartet niedriges Produkt-Großmargen-Quartal.
🎯 Kernbotschaft
- Fokus: NetApp erwartet Tailwinds durch Enterprise-KI (500 AI‑Wins, >2x YoY) und eine anhaltende Migration zu All‑Flash; kurzfristig drücken gestiegene Speicher‑Inputkosten auf Produktmargen.
⚡ Strategische Highlights
- AI‑Angebot: Teilnahme am KI‑Markt mit High‑Performance All‑Flash-Systemen plus neuer disaggregierter AFX‑Architektur kombiniert mit AIDE für Inferenz und Datenvorbereitung.
- Preissetzung: Preissteigerungen wurden zur Weitergabe steigender Commodity‑Kosten umgesetzt; Management berichtet bisher von geringerer Nachfrageelastizität.
- Public Cloud: Starkes Wachstum in der Public‑Cloud-Sparte (First‑party/Marketplace ~30% Wachstum), Margen ~85%; hoher Hebel auf Konzernmarge.
🆕 Neue Informationen
- Konkretes: Offenlegung von ~500 AI‑Wins (mehr als doppelt YoY), ein 4,5‑jähriger Google‑Distributed‑Cloud‑Vertrag mit Umsatzanteilen in Q4, sowie Quantifizierung des zusätzlichen Wocheneffekts in Q1 mit ~$65M.
❓ Fragen der Analysten
- Speicher‑Preise: Analysten fragten nach Nachfrageverhalten nach mehrfachen Preissteigerungen; Management sieht bisher nur geringe Elastizität, erwartet aber punktuelle Vorzieheffekte.
- Supply‑Sicherheit: Diskussion über längerfristige Lieferverträge mit Memory‑Zulieferern; NetApp führt Verhandlungen und sagt, die benötigte Versorgung für FY27 sei gesichert.
- Mix & Margen: Nachfrageverschiebung All‑Flash vs. Hybrid/Keystone (Storage‑as‑a‑Service) und Tempo der Produkt‑Marge‑Erholung (Q1 als Tiefpunkt, dann schrittweise besser).
🧾 Bottom Line
Für Aktionäre: NetApp ist gut positioniert für ein mögliches Storage‑Refresh und enterprise‑AI‑Wachstum, leidet aber kurzfristig unter höheren Memory‑Kosten und einem erwarteten Q1‑Margen‑Tief. Preisanpassungen, gesicherte Versorgung, stark margenträchtiges Public‑Cloud‑Geschäft und eine aggressive Kapitalrückführung (bis zu 100% Free‑Cash‑Flow) begrenzen das Risiko und bieten Upside bei Margen‑Normalisierung und Deal‑Conversion.
NetApp — Q4 2026 Earnings Call
1. Management Discussion
Good day, and welcome to the NetApp Fourth Quarter and Fiscal Year 2026 Earnings Call. [Operator Instructions] Please note that this event is being recorded. I would now like to turn the conference over to Kris Newton, Vice President, Investor Relations. Please go ahead.
Hi, everyone. Thanks for joining our Q4 and fiscal year 2026 earnings call. With me today are our CEO, George Kurian; and CFO, Wissam Jabra. This call is being webcast live and will be available for replay on our website at netapp.com. During today's call, we will make forward-looking statements and projections with respect to our financial outlook and future prospects, including without limitation, our guidance for the first quarter and fiscal year 2027, our expectations regarding future revenue, profitability and shareholder returns and other growth initiatives and strategies. .
These statements are subject to various risks and uncertainties, which may cause our actual results to differ materially. For more information, please refer to the documents we file from time to time with the SEC and on our website including our most recent Form 10-K and Form 10-Q. We disclaim any obligation to update our forward-looking statements and projections.
During the call, all financial measures presented will be non-GAAP unless otherwise indicated. Reconciliations of GAAP to non-GAAP measures are available on our website. I'll now turn the call over to George.
Good afternoon, everyone. Thank you for joining us. FY '26 was a landmark year for NetApp with record results across revenue, gross profit, operating income, cash flow for operations and free cash flow supported by strong customer demand in the fourth quarter.
Our performance demonstrates our ability to capitalize on the accelerating adoption of enterprise AI and cloud. with our differentiated hybrid cloud, intelligent data infrastructure platform trusted by the world's leading enterprises and cloud providers NetApp is increasingly at the center of our customers' data-driven AI transformations.
Achieving our full year target of a 30% operating margin, underscores our commitment to profitable growth and ongoing innovation. NetApp stands at the forefront of a transformative era driven by rapid AI adoption and explosive cloud growth. Enterprises are reimagining how they operate and compete and only NetApp delivers truly hybrid intelligent data infrastructure on-premises and in the cloud, all-flash and hybrid flash to seamlessly protect, secure, govern and activate the entire data estate for AI.
Our 30 years of innovation and leadership in hybrid multi-cloud environments are more relevant than ever as our vision of a hybrid world is realized. As enterprise AI adoption scales, the primary challenge is not compute but activating large volumes of unstructured data, a significant share of the world's enterprise unstructured data resides on NetApp solutions and our ability to activate securely and efficiently across hybrid and multi-cloud environments gives us a powerful competitive advantage.
As the only true hybrid cloud platform, unifying data governance across on-premises and cloud environments, we enable zero-copy data activation. Eliminating the cost and risk of moving data and transforming fragmented infrastructure into a secure launch pad for real-time AI and automation. Our value proposition is resonating strongly with customers and the industry.
Our storage services on AWS, Azure and Google Cloud empower customers to protect, mobilize and govern their data with unmatched flexibility and consistency regardless of location. This capability is increasingly critical as customers launch and scale their AI initiatives by integrating our data infrastructure platform with the AI and analytics offerings of leading cloud providers customers can activate their data for AI workloads in place where it is created without costly or time-consuming migration or duplication.
Making NetApp the secure zero-copy foundation enterprises need to move from fragmented infrastructure to real-time AI at scale. We fueled nearly 50 partner AI factories and labs as they build out their real world test beds to accelerate AI deployment. A recent example of this is that worldwide technologies live AI proving ground, where NetApp AFX all-flash storage is featured, allowing customers to test architectures validate performance and quickly move from experimentation to deployment.
This collaboration highlights the large opportunity ahead as enterprises look for trusted partners to operationalize AI confidently. We see growing opportunity and success with Neo and sovereign cloud providers who recognize the strength of our differentiated solutions and our joint go-to-market initiatives with leading hyperscalers. These partnerships reinforce our position as a trusted collaborator in the evolving cloud ecosystem.
A leading Neo cloud turn to NetApp for intelligent all-flash storage infrastructure, eliminating complexity and powering orchestration at cloud scale. The new deployments will help accelerate AI onboarding and time to value. With this win, we can begin to expand into other workloads to become the foundational data layer.
Another significant achievement is our expanded partnership with Google Cloud for Google Distributor Cloud, which underscores both the growing opportunity in AI and sovereign cloud environments and the strength of our technology. This collaboration enables government agencies and regulated enterprises to leverage advanced AI capabilities from Google and NetApp secure by design data infrastructure platform to modernize operations and accelerate AI-driven insights even in the most sensitive environments.
We achieved record revenue in Q4 and FY '26, driven by public cloud, all-flash and Keystone, which all reached all-time highs reflecting strong demand from customers modernizing infrastructure and scaling AI workloads. Public cloud revenue grew to $68 million in FY '26, up 18% year-over-year, normalized for the divestiture of the Spot by NetApp business in March 2025.
This growth was driven by first-party and marketplace cloud services, which increased 30% in FY '26. We are seeing growing demand from both new and existing customers to extend NetApp's capabilities deeper into their cloud environments. Customer's are increasingly choosing net adds to simplify and scale their hybrid and multi-cloud environments, leveraging our unified data management capabilities for operational consistency and agility.
Our expanding cloud portfolio is unlocking new use cases and verticals, including AI, fueling growth and expanding our addressable market. For example, a leading insurance company accelerated financial risk modeling and data science by connecting Azure Databricks directly to their data in Azure NetApp files, ensuring security, governance and performance.
Similarly, an Asian engineering company streamlined its Gen AI chatbot deployment on AWS by leveraging FSX for NetApp on TAP, allowing secure permission aware access to data in place and reducing operational overhead. Across these wins, the common thread is NetApp's ability to deliver secure governed, high-performance data access for AI workloads, enabling customers to innovate faster and operate more efficiently, all while maintaining control and compliance.
FY '26 all-flash revenue was $4.2 billion, an increase of 11% from last year, propelled by robust Q4 performance with revenue of $1.2 billion, up 18% year-over-year. Customers are choosing NetApp to power their most mission-critical workloads and our momentum in this segment is a testament to the strength of our innovation and go-to-market execution.
A prime example of this is the European aerospace company that shows NetApp displacing competitors in a greenfield win. The data management capabilities of NetApp, all Flash arrays stood out for their high performance, cyber resilience and ransomware protection as well as seamless integration with a broad ecosystem of partners.
Our comprehensive solution delivered the security, simplicity and strategic value needed to support critical initiatives. Revenue from our Keystone Storage as a Service offering grew approximately 65% from FY '25 and as more customers embrace the flexibility and simplicity of a cloud-like experience for their on-premises data. This momentum reflects the broader shift towards consumption-based IT models and our ability to meet customers wherever they are on their transformation journeys.
A leading manufacturer chose NetApp Keystone with all-flash and storage grid to support its AI strategy requiring a secure, flexible platform for massive data sets. Keystone delivers secure, governed self-service at scale enabling rapid collaboration and predictable on-demand performance. Our unified platform streamlines data management with multi-protocol support native S3 tiering and cloud integration for maximum efficiency.
AI was a clear growth engine for us in FY '26. We had approximately 500 AI and data preparation wins in Q4 alone, bringing the FY '26 total to over 1,100, our ability to help customers operationalize AI at scale, accelerate time to insight and drive real business outcomes is putting us increasingly at the center of our customers' AI journeys.
In FY '26, we furthered our AI innovation, launching next-generation solutions, including AFX and AI data engine, which are seeing strong early momentum and positive feedback from customers and partners. Additionally, we announced enhancements to the performance and capabilities of our all-flash arrays and expanded our converged AI solutions.
These offerings help organizations simplify their AI infrastructure, eliminate silos and accelerate their data pipelines. Reinforcing NetApp's role as the data infrastructure platform for AI. Let me walk through a couple of additional customer wins that Spotlight NetApp's competitive advantages.
A European government agency required real-time situational awareness with ultrafast latency-free data processing. NetApp's disaggregated AFX solution for their NVIDIA superpad environment, enabled independent scaling of compute and storage, delivering flexible future-proof infrastructure. Our rapid execution and expertise empowered a robust mission-critical AI platform to meet evolving operational demands.
A global financial leader signed a $20 million deal with NetApp to accelerate its AI-driven fraud detection and customer personalization. NetApp's GPU ready low latency data lake platform delivers high performance access to multi-petabyte data sets, enabling global real-time fraud scoring continuous model retraining and robust enterprise governance and resiliency.
Its high impact wins like these that helped us achieve record-setting results while navigating a dynamic macro environment. We're managing rising memory and component costs by working closely with our supply chain partners and adjusting pricing to balance growth and margins. Data generation continues unabated, and customers need solutions that best optimize performance and cost.
Our ability to offer a broad range of solutions with flexible purchasing options, including cloud, Keystone and hybrid flash strengthens our competitive position, resilience and flexibility. FY '26 also set a new bar for cash generation. Our strong free cash flow enables us to invest in innovation while returning value to shareholders through dividends and share repurchases.
We remain committed to disciplined capital allocation and long-term value creation. I want to thank the entire NetApp team for their customer-centric focus and hard work in FY '26. It was a year of strong execution, innovation and accelerating growth.
Clear proof that our strategy is working and our portfolio is resonating in the market. The investments we made this year have expanded our opportunities and set a solid foundation for future growth. Looking ahead, we are encouraged by the robust demand signals we're seeing and are confident in our ability to maintain this momentum as reflected in our fiscal year 2017 outlook.
Our hybrid multi-cloud leadership, differentiated AI offerings and flexible storage and consumption offerings position NetApp for continued success as customers accelerate their data-driven AI transformation. With that, I'll turn the call over to Wissam.
Thanks, George, and good afternoon, everyone. In the fiscal fourth quarter, we delivered strong results exceeding the high end of both the revenue and EPS guidance ranges. Revenue for the quarter was $1.95 billion, up 12% year-over-year and 14% sequentially. Non-GAAP earnings per share was $2.43, up 26% year-over-year.
Excluding the divested spot business, which generated $9 million of revenue in the fourth quarter of the prior year. Revenue grew 13% year-over-year. Revenue was up 10% year-over-year, excluding the effect of foreign currency exchange rates which had little impact relative to guidance.
This marks our tenth consecutive quarter of year-over-year revenue growth. Looking at revenue by segment. Hybrid cloud revenue of $1.77 billion was up 13% year-over-year. Product revenue of $966 million was up 14% year-over-year driven by the execution of a multiyear agreement with Google Cloud to deliver secure AI-ready data infrastructure to Google distributed cloud environments.
In prior quarters, we mentioned the potential for large deals to materialize in the second half of fiscal year 2026, and this came to fruition in Q4. Support revenue of $688 million was up 10% year-over-year, partly driven by a onetime item. Professional Services revenue of $112 million was up 14% year-over-year, mainly driven by growth in Keystone, our Storage as a Service offering which continues to build momentum.
Q4 public cloud revenue of $182 million was up 11% year-over-year. Excluding spot, public cloud revenue grew 18% year-over-year driven by a strong demand for first-party and marketplace storage services. We exited fiscal year 2026 with $4.85 billion in deferred revenue, an increase of 7% year-over-year and 6% year-over-year in constant currency.
Remaining performance obligations were $5.65 billion, up 14% year-over-year. unbilled remaining performance obligations, a key indicator of future Keystone Storage as a Service revenue growth were $807 million, up 88% year-over-year. This outperformance was driven by an increase in support performance obligations associated with the Google agreement as well as Keystone unbilled RPO, which grew at a similar rate to the prior quarters on a year-over-year basis.
Moving to the rest of the income statement. Please note, my comments will be related to non-GAAP results unless stated otherwise. Q4 gross margin was 70.5% and up 100 basis points year-over-year, driven by public cloud gross margin expansion. Gross profit was $1.37 billion, up 14% compared to Q4 2025. Hybrid cloud gross margin was 69%, down 60 basis points sequentially due to higher product revenue in the quarter. Product gross margin was 56.1%, and up 80 basis points sequentially due to the benefit from the Google Cloud Enterprise Agreement offsetting higher component costs.
Our recurring support business continues to be highly profitable with gross margin of 93%. Professional Services gross margin was 32.1%, improving 80 basis points sequentially. We Public cloud gross margin was 85.7%, up 60 basis points sequentially and over 6 percentage points year-over-year.
The public cloud business has operated within the 80% to 85% long-term target range in the first half of the fiscal year and above the high end of that range in the last 2 quarters. Operating expenses of $750 million were up 6% year-over-year and 9% sequentially.
Operating income was $624 million up 26% compared to Q4 2025 and operating margin was 32%, up 340 basis points year-over-year, both all-time records, driven by higher revenue. Earnings per share was $2.43, up 26% year-over-year and exceeding the high end of the guidance range. Our results demonstrate strong execution on key revenue growth opportunities in all-flash public cloud and AI, along with a continued focus on operational discipline, resulting in record highs for quarterly operating income and EPS.
In Q4, cash flow from operations was $950 million and free cash flow was $900 million, both up over 40% year-over-year and all-time records. These strong cash flow metrics were driven by increased collections from higher billings. During the fourth quarter, we returned $303 million of capital to our shareholders with $200 million in share repurchases and $103 million paid in dividends or $0.52 per share.
Q4 diluted share count of $199 million decreased by 7 million shares or 3% year-over-year. At the end of the fiscal year 2026, there was approximately $500 million remaining from our current share repurchase authorization -- and today, we are announcing an increase in debt authorization by $1 billion.
Moving to a review of our results for the full fiscal year 2026. Revenue of $6.93 billion was up 5% year-over-year, exceeding the high end of our guidance range. Excluding the divested spot business, revenue was up 7% year-over-year and in line with our long-term target model. Our strict focus on operating leverage allowed us to drive bottom line profitability at a faster pace, all contributing to record highs in operating margin, EPS and cash flow.
Gross margin was 71.3%, up 20 basis points year-over-year, driven by public cloud and professional services gross margin expansion and partially offset by lower product gross margin. Operating margin was 30.2%, up 190 basis points year-over-year, driven by 1% year-over-year growth in operating expenses relative to 5% year-over-year revenue growth.
Full year EPS was $8.13, up 12% year-over-year, more than double the rate of revenue growth. Operating cash flow was $2.07 billion, and free cash flow generation was $1.87 billion, up close to 40% year-over-year primarily due to stronger cash collections and net working capital benefits.
Our balance sheet remains very healthy as we returned a total of $1.36 billion in value to our shareholders through share repurchases and cash dividends. all as we continue to invest in the next generation of AI data solutions. We closed the year with $358 billion in cash and short-term investments, and $2.49 billion in gross debt outstanding, resulting in a net cash position of $1.1 billion. Inventories expanded both year-over-year and quarter-over-quarter.
Inventory turns decreased sequentially to 12%. Now turning to non-GAAP guidance, starting with fiscal year 2027. Let me begin by underscoring the confidence in our strategy and in the strength of our position as we address key customer priorities. Our guidance reflects a solid underlying enterprise IT demand environment with enterprise AI activity increasing relative to fiscal year 2026.
At the same time, we recognize the potential for pockets of demand driven by accelerated purchasing. We also remain focused on adjusting prices as needed to track any material movements in memory and component costs, while maintaining a disciplined balance between growth and margin.
On that basis, we expect fiscal year 2027 revenue to be in the range of $7.325 billion to 7.575 billion. At the $7.45 billion midpoint, this implies 8% year-over-year growth, representing an acceleration from the 5% growth we successfully delivered in fiscal year 2026.
We expect gross margin to be in the range of 68.5% to 69.5%. We expect operating margin to be in the range of 29.1% to 30.1%. For the full year, we expect the effective tax rate to be in the range of 20% to 21%. We expect EPS to be in the range of $8.70 to $9 an at the $8.85 midpoint, this represents 9% year-over-year growth.
In fiscal year 2027, we intend to return up to 100% of free cash flow to shareholders through cash dividends and share repurchases. We also expect to reduce share count by low single-digit percentage points year-over-year. Now turning to Q1 guidance. As a reminder, Q1 includes an extra week, which is expected to contribute approximately $65 million of revenue, primarily in support and cloud. with a minimal impact on product and to add $21 million of operating expenses.
We expect revenue to be in the range of $1.75 billion to $1.9 billion. At the $1.825 billion midpoint, this implies 17% year-over-year growth. We expect gross margin to be in the range of 69.1% to 70.1% and operating margin to be in the range of 28.4% to 29.4%.
We expect EPS to be in the range of $2.05 and $2.15 and with a midpoint of $2.10. In closing, as we look ahead to fiscal year 2027, we are confident in our strategy and execution capabilities. We remain focused on delivering revenue growth and profitability, increasing free cash flow and creating sustainable long-term value for shareholders.
With that, I'll turn the call over to Kris for Q&A.
Thanks, with. Operator, let's begin the Q&A. .
[Operator Instructions] And your first question comes from David Vogt with UBS.
2. Question Answer
Maybe George, for you. Can you touch on sort of the demand strength again. I appreciate all the color you provided in the call, but all-flash was exceptionally strong in the quarter. And just we're going to get a lot of questions on sort of the cadence of that demand.
How was it from a linearity perspective? Did the price changes in the industry have an impact on demand? Anything that you can provide from a color perspective or granularity would be helpful in how we think about the demand drivers, particularly as we move into the subsequent quarters for the full year, that would be helpful as well. And then I have a follow-up. .
Thank you for your question. Momentum in the business was very, very strong. IT spending is forecasted to be up strongly, driven by enterprises ready for AI and we are seeing that across all segments of our business: cloud, flash, AI and Keystone.
And it shows the differentiation in our offering as well as solid execution by our customer-facing teams. We have seen some accelerated decision-making -- but we also know that most customers do not have the flexibility to do so.
On the face of the Q4 P&L, the impact of pull forward or accelerated decision-making was minimal. Our Q4 results were tied to the big deals we told you to expect when we guided the fiscal year. And we see really strong outlook for this coming year powered by our confidence in our position and what we see as growing evidence that enterprise AI is happening in front of our eyes.
Great. And maybe one for Wissam on product gross margin. Obviously, it's a very challenging component backdrop, DRAM and NAND and other issues. If I just kind of take your public cloud business and I kind of strip out support as well, it kind of looks like product gross margin could be near a trough in the July quarter and kind of stay relatively stable from a product perspective as we move through the year. Is that kind of what you're suggesting based on sort of the outlook for the year? .
Yes. Thanks, David. I think you got it right. For us, July quarter is more or less the trough. And from there on, we're anticipating gradual improvements. Really, we've been taking a lot of actions in terms of price adjustments as we see component costs increase. And so those price adjustments will start seeing more and more effect as the year progresses. And so that's really the dynamic driving the product gross margin. .
Your next question comes from the line of Amit Daryanani Evercore ISI.
Maybe just ask on the all-flash array side. Revenue obviously accelerated pretty well at 18% growth. George, I heard you on the limited pull-in dynamic. But I was wondering is there a way to think about in ASP was a bit of a tailwind versus unit growth is the way to think about that?
And then how do you think of AFA growth broadly into fiscal '27. Maybe I'll ask my follow-up as well, which is we are starting to see a fairly strong growth, I think, from the traditional service side driven by enterprise and starting to get more and more AI ready.
How should investors think about the attach rate and opportunity between AI compute deployments that are happening at a big rate right now? And that attached rate to the high-performance storage that you folks sell .
Thank you for your question. Our AI business performed really strongly in the quarter. we noted about 500 AI wins in the quarter, 1,100 for the full year, those compared to roughly 400 for the whole of the prior fiscal year. So you are seeing strong uptick in enterprise AI.
In enterprise AI configuration the -- all elements of our flash portfolio performed strongly, high performance flash capacity flash and block storage. And so we see customers deploying these high-performance compute and storage environments to make sure that the GPUs are fully used their expensive GPUs, they need to be fed with a lot of data.
What we also saw was that in the non-demanding AI environment customers are starting to buy more of hybrid flash, which we are uniquely positioned to deliver under a single operating system. So both like all-flash and hybrid flash grew and all-flash grew particularly in the AI use case the Summit.
Your next question comes from the line of Erik Woodring with Morgan Stanley.
George, you called out the 50-day wins in 4Q is certainly that you can help us think about how much of your fiscal '27 revenue guide is driven by some of these secured and anticipated AI wins and just curious on those AI wins, if there's a way that you can kind of parse out what is part of kind of public cloud versus kind of what is on-prem solutions? And then a quick follow-up, please.
All of the 500 AI wins are on-prem wins and they combine a mix of enterprise as well as Neo Cloud. I think if you look at the mix of the use cases, they are roughly the same pattern as we saw before. Half of them are really tied to data preparation, large-scale analytic environment that are now being operated under GPU compute.
And then the remainder are roughly half and half between training and fine-tuning large language model and inferencing. So it's roughly 50%, 25%, 25%, roughly speaking. That pattern has stayed pretty similar through all of the year. In terms of the -- how we see that play into our business next year in fiscal year '27, listen, this is what gives us confidence to show an acceleration in our business.
We think that the strength is broad-based across segments and verticals and geographies -- we think that we are very well positioned because of our installed base of data, a hybrid cloud data infrastructure pipelines that make it much easier for customers to use AI and the fact that we can offer our customers life cycle cost management from super high performance to exceptionally cost-effective disk-based environment.
So we're optimistic -- we see the demand. We see the momentum in our business, and we are investing some additional sales resources just like we did last year to support our outlook.
Okay. Amazing. And just a quick follow-up for you is -- some of your peers are kind of messaging expanding storage gross margins this year. I'm wondering, as we think about your gross margin guide, is there a degree of kind of prudence or conservatism that you're trying to embed there just given we're kind of an unprecedented pricing territory.
Or is there kind of enough component cost pressure that you see today that regardless, it would be challenging to expand margins. I would just love to know maybe the conservatism that you're thinking about as you think about your gross margin guide for the full year.
Yes. Thanks, Eric. So look, the guide is based on the information we have at this time. And so we look at what -- how the business developed through the next few quarters and based on what we know from a component cost perspective.
Now granted, if component costs vary moving forward, we will continue to take action to make sure we mitigate the impact to margins. And of course, we will do whatever we can to improve from that. When you look at -- so this is really the comment around the product gross margin.
I do have to just saying a reminder here that we're not really moving from our long-term goal or target from a product gross margin, which is really is -- still is the mid-50s to high 50%. So that's still in our long-term target, and we will -- we will still strive to get there in the future. What we also are looking at, we look overall at the total gross margin for the company.
And when you look at the total gross margin for the company, the public cloud business has seen some really nice uptick in fiscal '26. And as that business grows, it does give us a bit of a nice tailwind to the margin line.
And the same thing for the Keystone business that continues to grow at a nice pace and build momentum, and that has a little bit of a tailwind as well. Then maybe the last few comments I'll make here on margin. It's -- we also are targeting gross profit because, obviously, that's what drives our earnings power. And so we look at gross profit growth year-over-year as well as something that we continue to make sure we improve
Your next question comes from the line of Wamsi Mohan with Bank of America.
George, can you talk about your -- or how you're seeing your large deal pipeline evolve? You obviously saw strength in the quarter that you had messaged previously. But is that strength something that we expect that we should expect will sustain? And what's baked into guidance? And I have a follow-up. .
I think what we saw in the large steel pipelines were some related to infrastructure modernization that you could say could be people bringing forward spending. But a very large part of the pipeline were related to AI wins. And those were projects that we had worked on and some that we saw accelerate as the business needs came on.
What I feel really, really good about is the fact that especially in our AI business, the number of customers who we are able to win in accounts that are not traditionally NetApp large installed base accounts have been super strong. And so what that gives me confidence is we are winning on customers' business priorities, which are durable even in the face of commodity price variations.
Okay. And maybe just on the pull forward, like it sounds like you really didn't see more evidence of forward and large deals drove the upside in the quarter. But as we talk to like resellers, it seems like a lot of the annual budget is being spent in the first half of the calendar year.
We're hearing about a scramble for securing supply from customers. So just curious why would you not have seen that customer behavior of trying to accelerate purchases in the first half ahead of price increases?
And maybe some sense of how you're thinking about the cadence of price increases from here. You've already instituted some, but how are you thinking about the cadence of price increases on a go-forward basis.
Thanks for your question, Juan. What I said was that on the face of the Q4 P&L, the impact of pull-forward demand was minimal. Our Q4 results from a revenue standpoint were tied to big deals that we told you about when we guided the fiscal year.
We are seeing some accelerated decision-making and we also know that many customers cannot -- don't have the flexibility to do so. And so our goal is to make sure that we can meet customer demand we can balance cost and availability of supply and that we can maintain lead times within customers' normal expectations.
We feel really good about the momentum in our business, and we'll tell you more about our business through the course of the year. what I feel confident about is that we have factored in to the best of our knowledge, the risks of pull-ins and the dynamics it creates through the fiscal year, and we'll tell you more about it. As part of our go-forward plan.
Your next question comes from the line of Tim Long with Barclays.
Thank you. One and a follow-up, if I could. First, maybe just talking about the public cloud revenues. I think you've talked about 18% growth at spot and 30% on the first-party storage.
As we head into next year with no spot -- just curious how you're thinking about sustainability of the growth rate there? And does the Google deal in the quarter impact that at all? And then on the follow-up, on Keystone, it sounds like really good growth again.
Do you think this is simply just wanting to find other ways to deal with higher NAND pricing -- or is this more durable than just a pricing or payment mechanism. So we love your views on both of those.
Yes. Thank you for your question. On public cloud, we continue to see super strong demand for our cloud storage services, both first party and marketplace. They are -- they grew 30% year-on-year. And given their growth rate relative to the rest of the cloud portfolio, they are, as you can imagine, the predominant part of the cloud business overall.
We see continued momentum in that part of our business, which should cause cloud to grow faster next year than it did the prior year at really strong gross margin. super excited about the cloud. We did a lot of innovations through the course of the year.
We are, as I said in my comments, starting to see some of the AI use cases also show up in the cloud and customers starting to use our tools in the cloud for AI use cases. With regard to Keystone, we see a broad-based shift in the market towards consumption-based offerings like Keystone.
Some of that is driven by customers having used public cloud and now getting confident about how to operate their own environments like the public cloud. There was possibly some customers who bought Keystone because they felt that it would be a more optimal way to balance cost and use in a time of inflationary costs.
But in general, a Storage as a Service business should grow faster than our traditional business. And Tim, just to clarify, I think part of your question on public cloud included the Google agreement. I just want to clarify that the agreement is more in the hybrid cloud segment. So this is, of course, independent of all the comments that George just made. It helps our hybrid cloud business, which is what to help us in Q4.
And we'll -- just like any hybrid cloud agreement business, it will help us also going forward on the support revenue as well.
Your next question comes from the line of Samik Chatterjee with JPMorgan.
George, maybe just to go back to your response earlier to Wamsi's question about you are seeing some accelerated decisions from customers, although some of them cannot really change those decisions right now.
And you also have this impact of 1 extra week in 1Q, like typically, you've ended up with, I think, 48% of your revenue in the first half of the year. Do you expect like the yield look very different from maybe some of your prior years because of the dynamics going on right now?
We think, as we said, we think that we have broad-based durable demand in our business, driven by customers prioritizing data infrastructure for AI -- and you saw that in our Q4 print, which did not benefit the results in the quarter on the P&L did not benefit from any pull forward. .
We see the same, roughly speaking, demand pattern at the start of the new fiscal year, which is the first half and the second half, like you said, Samik, roughly in the same kind of percentages, adjusting, of course, for the extra week in the first quarter. So it's early in the year. We feel really good about the momentum in our business. We acknowledge that there are probably some amounts of pull forward, but the demand is broad-based, and we'll provide you updates as we go through the year.
Got it. Got it. And then maybe just help me think through -- sorry, for my follow-up, the Google, the agreement that you had with Google relative to the hybrid cloud business. Trying to think around sort of what opportunity that creates for you? Is it in specific customer verticals? Trying to frame around sort of what the size of that opportunity would lead to. .
Yes, Google distributed cloud is where Google brings its advanced technology stack to a disconnected or likely connected data center. It could be for regulated industries.
It could be for public sector environment, it could be for national security environment and NetApp was chosen by Google to be a large chunk of the data infrastructure within the Google distributed cloud architecture. So there are 2 benefits to NetApp. One, of course, it allows us to broaden our reach into sovereign and your environments that are incrementally TAM expanding for NetApp.
And second, it allows us to build these really secure differentiated hybrid infrastructures across on-premises and public cloud and secure cloud for these clients. This is the expansion of the Google distributed cloud deal that we have worked on for quite a while. And so there's -- since 2024 -- we have been working with them on various different opportunities, and then we have expanded our franchise with them quite substantially with this Google distributed cloud relationship.
Our next question comes from the line of Steven Fox with Fox Advisors.
I had a couple of questions I think are related. One is I'm trying to understand in the full year margin guidance at the corporate level, how we think about sort of the mix effect of higher NAND prices? Obviously, there could be puts and takes, whether we're looking at product versus public cloud or Keystone?
And then related to that, how much can you give us a sense on how much revenue growth in the quarter and going forward is related to just higher ASPs and passing through higher NAND prices.
So the quick answer on the first part of the question, the NAND prices would manifest themselves in the product gross margin. that's where basically the main impact is. The rest of the margin line shouldn't be as affected. I mean there's a bit Keystone, but it shouldn't be as affected given that it's recognized over time.
And when it comes to the second part of the question, look, obviously, we talked about raising prices to offset component cost inflation. Our goal is to protect the profitability of our business, and we will continue to do so if needed. And so more than those qualitative comments, do then not get into the -- quantifying it because it's really too early in the year. And so let's wait until we see how Q1 develops, and maybe we can talk about that in the next quarters.
Yes, just maybe to add, historically, customers' budget in dollars and there has been little elasticity of demand just because of price increases. I think, of course, as Wissam mentioned, we are in a unique territory -- it's hard for us to tell you exactly. So we'll give you updates as we go through the year.
Your next question comes from the line of Aaron Rakers with Wells Fargo.
This is Jake on for Aaron. Congrats on the great quarter. Just wondering if you could just give some color on the early feedback you're seeing on AFX and AI data engine and when they should become bigger revenue contributors moving forward?
We are pleased with the progress on AFX and the early feedback on AI data engine. AFX has already had good with Neo Cloud in financial services in hedge funds and in life sciences, which were the target customers. For it, and we are seeing more and more customers beginning to qualify it. It will take time. It's a new architecture.
We always believe it would take time, but it is serving the purpose for what we created it for -- with regard to AIE, we have brought it to certain clients, and we are seeing good kind of good feedback on the value and the benefits it provides especially as our large installed base of customers who have huge amounts of unstructured data on NetApp wanting to organize that data for AI projects AI is a big help to them in doing so. And that feedback is coming back from our clients. SP551990915 Great. And then maybe just as a follow-up. I was wondering on the all-flash momentum, it's really, really impressive. Just some more color on how much of the growth is driven by pricing versus capacity and unit growth -- and then maybe just looking at the installed base, where does it stand now? And how much conversion runway do you still have going forward?
From an installed base perspective, like we have said, it picked up another 1% to 48% of the installed base. With regard to the performance in the quarter. Listen, it was really having differentiated solutions for a broad range of priority customer use cases. We raised prices during the quarter but we have not seen that materially translates into what we saw in the customers that -- into the transactions that we recorded in the quarter. It takes a little bit of time for that to flow through. In the past, it's taken about 3 quarters. We have tightened up our agreements with customers. So you should see that flow through the system over the next quarter to 2 quarters. .
Your next question comes from the line of Asiya Merchant with Citigroup.
This is Mike Cadiz for Merchant Citi. So I just have question.
It's looking into fiscal '27, how would we be thinking about strategic M&A at this point and leveraging growth and innovation in that respect, looking in the fiscal year .
Thank you for your question. We constantly look at opportunities for M&A, and we make decisions on whether that is the right use of capital. We feel good about our portfolio, but we won't rule anything in or rule anything out at this point in the year. .
Your next question comes from the line of Krish Sankar with Cowen.
I had to George, you kind of mentioned a large New York cloud win I'm kind of curious, are you sole source in that win? How do you think about the opportunity? Because I did not think that near clouds are big consumers of storage exabytes. So any color on that would be helpful and another follow-up.
I don't want to comment about their environment. This is a large meaning top 5 U.S. NEO cloud where they were looking to expand their offerings, especially to serve high-performance use cases for enterprise AI, and we were fortunate to be chosen to be the platform to do so. .
Our experience in architecting solutions for hyperscale is playing out to our advantage when we speak with New York clouds as they begin to broaden the set of use cases and offerings that they have for the enterprise.
Got it. That is very helpful. And then maybe a question for either George or Visa. When I look at your product revenues, is there a way to parse it out by what percentage of product revenue is actually gen AI related?
Yes. I mean, look, we don't break it out to that novel, Chris. We know that there's obviously the activity and the number of wins we mentioned generate revenue for us -- we just don't break it out to that level of details. The other thing I would say is, as you noticed, perhaps over the quarters, the few quarters that we've been disclosing the number of wins, these number of wins have been increasing.
And so you could assume that it's becoming a sort of a growing portion of our revenue, but it's not broken out to that level of detail.
Your next question comes from the line of Param Singh with Oppenheimer.
I had a couple. One, I wanted to understand the incremental revenue opportunity from AID. And do you view this as something that will help you gain share in the traditional market? Or is that an add-on module that you can sell and expand into addressing more AI workloads? How do you think about that? And how do you think about quantifying how would you monetize that in terms of percentage of revenue and so forth.
There's 2 use cases. Thank you for your question. There's 2 use cases. As you correctly said, one for our installed base, it creates a very sticky competitive moat where we are able to give them a huge amount of value for their existing infrastructure.
We can choose to monetize that as either stand-alone software subscription or as part of a broader offering a fuller solution, including storage. And then I think with regard to the net new environment, as I said, I was particularly pleased with the fact that a very large percentage of our AI wins were from customers who we are not the incumbent data infrastructure provider.
And there, what we are able to do is combine AIDE together with our storage so that they can build a really good data lake or a data prep environment, and we saw momentum on that this past quarter.
And on the second part, George, how do you think about pricing your product for that? I mean is it . Does the ASP go up by 10%, 15%? Or is it something related to the type of workloads you're running? How are you thinking about monetizing it?
It really depends on the volume of data and the type of data and services that we are offering. Broadly speaking, it's tied to the infrastructure, the size of the data set and the value that we are offering the customer related to the type of data use cases that they are using with AIBE.
Your next question comes from the line of Katherine Murphy with Goldman Sachs.
You talked about investing in additional sales resources against this AR AI opportunity that you've highlighted. Is there anything you could share about how NetApp's go-to-market strategy is evolving as you go after more of these neo Cloud and sovereign opportunities in addition to your base enterprise customer.
Yes. We have built out a specialist team to pursue AI opportunities, both those that are focused on completely use segments like Neo and sovereign cloud or to help our frontline teams to drive AI wins in the enterprise.
We have also expanded coverage of accounts because we feel good about our opportunity to gain share. So we have added more accounts to our directly managed coverage resources -- and it's a sign of confidence. We have seen momentum building in our business through the course of this year, and our outlook for next year feels really robust.
Your next question comes from the line of Simon Leopold with Raymond James.
I guess I'm sort of looking at the midpoint of the guidance for Q1 as well as the endpoint for the full fiscal year. And I think this implies relatively little sequential growth through the year. And I get the extra week add some complication.
But it seems as if you're sort of suggesting that the year could have less than seasonal patterns. Could you help me understand what you're thinking here?
Yes. Let me address that. So when you look at the first half versus second half of the year. As George said, we're expecting a seasonal pattern in the typical first half, second half when adjusting for the extra week in Q1. In other words, we take out the extra week in Q1, which is approximately $65 million. And you do the math, you would end up with roughly similar type of seasonality first half second half.
And so that's part of it. And then when you sort of look at the midpoint of the guide for Q1 and then midpoint of the guide for the fiscal year and sort of look at the Q2 through Q4, it gets you still in the sort of mid-single-digit percent growth over the same time period in fiscal '26.
Great. And just as my follow-up, we obviously understand the memory issues, NAND and hard does, DRAM. Just wondering what you've observed or experienced in terms of other supply chain constraints and how you might see those risks relative to the memory challenges?
Yes. Listen, I think that we work with multiple suppliers for pretty much every component of our kind of silicon lineup. We are cognizant that there could be constraints in other parts of the ecosystem. And I think this is why we have a broad range of offerings as well. I think one of the things that we have seen clients talk to us about is on HDDs.
We've always believed that HDDs were an important part of customers' overall lineup, and we have a strong set of solutions for that. At this point, given where we are in the year, I want to just say 2 things. One is, listen, we feel really good about the momentum in our business. We are early in the year.
We'll tell you more about how it plays out through the course of the year. Second, at this time, we believe we can source adequate supply to meet our outlook for the year.
Your next question comes from the line of Ananda Baruah with Loop Capital.
Really appreciate the question. I guess I'll just sort of quickly ask 2 in 1 part here. You guys have mentioned that you expect next year of a cloud ex spot to see accelerating revenue growth -- any view on over time what a normalized growth rate could look like? Or should we expect growth rate acceleration for the foreseeable future?
And then can you just remind us with some -- how to think about the sort of the mechanics underlying the gross margin expansion. It sounds like there's some mix component going on, but the margin has been expanding for a while now. So if there's anything in addition to mix, that would be helpful as well to know about.
Listen, maybe I'll just tell you at a high level, right? We're not providing specific guidance numbers and so on. I think what we see is continued strength in our 1P and marketplace cloud storage services. Those have grown consistently above the overall cloud storage business -- cloud business and are now a much bigger part of the cloud business than they were a year ago.
And so our view of how the cloud portfolio evolves over the next year is essentially, if you remove stock from the compare to last year, we just see the same trend continuing through the next year. But because cloud storage is a bigger part of the mix, you can do the math on what that does to the overall cloud storage, cloud business.
And with respect to the margin question, look, the target margin for the public cloud business is 80% to 85%, and we've been operating at sort of higher end of that range. And so as the business continues to grow faster than the rest of the company, it does give us a bit of a nice margin tailwind.
We have time for 1 more question, and that question comes from Nehal Chokshi with Northland Capital Markets.
Congrats on the execution and realized acceleration that you've talked about here. And it sounds like a lot of this is coming from AI-related demand. And you're giving these metrics in terms of the number of deals, but we still don't have a good sense as far as like what percent of bookings or revenue that is. Can you help us out a little bit on that front?
Yes. Thanks for the question, Nehal. We don't break it out. As I mentioned earlier, I think the previous question, we only talk about -- we quantify the number of opportunities or activity, let's say, wins in the on-prem business, but we don't break out bookings or revenue for AI.
It sounds like though that the revenue per deal has gone up significantly in this past quarter as it does sound like some of these large deals that came to [indiscernible] are in that AI category deals that's in that 500 dare, is that correct?
Yes. Look, I -- it's a wide range of sizes. I wouldn't want to venture any sort of anything that may not be -- there may or may not be correct. So I'll leave it at that.
All right. Well, thank you, Nehal. I'm going to hand it over to George for some closing comments.
Thank you, Kris. FY '26 was a record year for NetApp. Reflecting strong execution and accelerating demand for AI and cloud solution. Our hybrid cloud intelligent data infrastructure platform is at the center of customers' data-driven transformation, delivering secure, real-time zero-copy data activation for AI.
Our broad portfolio allows us to deliver the right balance of cost and performance for our customers, strengthening our resilience in a dynamic market, continued innovation and strategic partnerships are expanding our opportunities and driving sustainable growth and strong financial results and disciplined capital allocation enabled us to invest in the future and return value to shareholders.
As we look to FY '27, we are confident in our strategy and our ability to deliver ongoing growth and leadership in AI and cloud. Thank you.
Ladies and gentlemen, this does conclude today's conference call. Thank you for your participation, and you may now disconnect.
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NetApp — Q4 2026 Earnings Call
NetApp — Q4 2026 Earnings Call
NetApp meldet ein Rekordquartal: starke AI- und Cloud-Nachfrage, Bestwerte bei Margen und Cashflow; FY27-Guidance signalisiert Beschleunigung.
📊 Quartal auf einen Blick
- Umsatz: $1,95 Mrd. (+12% im Jahresvergleich (YoY); +13% ex‑Spot)
- EPS: $2,43 (non‑GAAP, +26% YoY)
- Bruttomarge: 70,5% (+100 Basispunkte YoY)
- Operativmarge: 32,0% (Rekord, +340 Basispunkte YoY)
- Free Cashflow: $900 Mio. (↑>40% YoY); Kapitalrückfluss $303 Mio. in Q4
🎯 Was das Management sagt
- AI‑Fokus: NetApp positioniert sich als Datenplattform für Enterprise‑AI: Zero‑copy‑Datenaktivierung on‑premise und in Clouds.
- Hybrid & Keystone: Keystone‑Storage‑as‑a‑Service wächst stark (~+65% FY), Verbrauchsmodelle treiben Nachfrage.
- Partnerschaften: Erweiterte Hyperscaler‑ und sovereign‑Cloud‑Allianzen (z.B. Google Distributed Cloud) zur Adressenerweiterung.
🔭 Ausblick & Guidance
- FY27 Umsatz: $7,325–7,575 Mrd. (Mittelwert $7,45 Mrd., +8% YoY)
- Margen: Bruttomarge 68,5–69,5%; Operativmarge 29,1–30,1%
- EPS & Kapitalpolitik: $8,70–9,00 (Mittel $8,85, +9% YoY); Rückgabe bis zu 100% des Free Cashflow, Reduktion der Aktienzahl low‑single‑digit
- Q1‑Hinweis: Q1 enthält eine Zusatzwoche (~$65M Umsatz, +$21M Opex); Q1 Umsatz erwart. $1,75–1,90 Mrd., EPS $2,05–2,15
❓ Fragen der Analysten
- Nachhaltigkeit der Nachfrage: Analysten hinterfragten, wie viel des AI‑ und All‑Flash‑Upswings Pull‑forward vs. dauerhafte Nachfrage ist; Management sieht nur begrenzte Pull‑forward‑Effekte.
- Produktmargen & Komponentenpreise: NAND/DRAM‑Druck bleibt Kernrisiko; Firma hat Preisanpassungen vorgenommen, erwartet Q1 als Margen‑Tiefpunkt für Produktbereich und dann graduelle Verbesserung.
- AI‑Revenues & Transparenz: Viele Fragen zu Anteil von AI an Buchungen/Revenue – Management berichtet Win‑Zahlen, bricht aber keine AI‑Umsätze separat aus.
⚡ Bottom Line
- Fazit: Starkes operatives Momentum mit Rekordmargen und Cashflow untermauert NetApps Argument als Dateninfrastruktur‑Plattform für Enterprise‑AI; Guidance signalisiert beschleunigtes Wachstum, aber Komponentenpreise und Sichtbarkeit von AI‑Umsätzen bleiben wesentliche Unsicherheiten für Anleger.
NetApp — Morgan Stanley Technology
1. Question Answer
All right. Why don't I start? So good morning, everyone. Welcome to day 3 of the Flagship TMT Conference. My name is Erik Woodring. I lead the U.S. IT hardware research coverage here at Morgan Stanley.
I am delighted to be joined this morning by NetApp's CEO, George Kurian. George has obviously been at NetApp for over 15 years, been the CEO since 2015. He played a major role in kind of transforming the business into what it's become today. So George, thank you. Thank you very much. Thank you for coming to the conference. Good to see you.
Thank you, Erik. Good morning.
So before we start, just from Morgan Stanley side, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures for important disclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. I don't have the safe harbor agreement yet. But Jeriel, do you want to come up and read it?
We have a safe harbor statement that we would like to read ahead of the presentation.
It's in the NetApp here. Perfect. Thank you, Jeriel. So just from the NetApp side, today's discussion may include forward-looking statements regarding NetApp's future performance, share are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q filed with the SEC, and available on their website at netapp.com. NetApp disclaims any obligation to update information in any forward-looking statement for any reason. Thank you, Jeriel.
Perfect, sir. Thank you.
George. Welcome, obviously, a lot to talk about. I think the most natural kind of starting point is just a review of earnings reported last week. And maybe to that, the 2 or 3 things, most important kind of key highlights from the quarter, speak to the momentum in the business, and then we can get into specifics from there.
Yes. Thank you for having me. We just concluded and reported Q3 of our fiscal year. We had a strong performance, as we indicated we saw acceleration in our business in the second half of the year. Revenue growth ex the divestiture of spot was 6%. All of our focused growth priorities did very well. We had close to 300 AI wins. We had 11% growth in our all-flash arrays, again, well ahead of the market. We had growth in our high-margin public cloud business. Again, ex spot total cloud grew 17% with our first parties and marketplace services growing 27% year-on-year, and our Keystone Storage as a Service business grew approximately 65%, 68% year-on-year.
So overall, really good momentum across the business. Operating income and EPS were also record highs. So I feel good heading into the final quarter of this year and the momentum heading into next year.
So I want to maybe start just on the AI side. And to your point, you highlighted about 300 AI wins in the quarter. That was up from 200 in the quarter prior. Can you just help us understand those wins, those workloads, how does that kind of differ in either intensity or product as it relates to kind of the traditional backward-looking kind of storage customers?
Yes. I think in the AI landscape, we have 3 different areas of focus. One is what you call data preparation and data lakes, where customers are bringing data of multiple types together to analyze, the second is model training and fine-tuning, and the third is RAG and inference, where you take a model and actually use it for either classic inference or increasingly agentic use cases. We have -- we reported in the quarter that 60% were the first bucket, 20% middle and 20% the last bucket. They are essentially use our all-flash arrays for high-performance use cases, and then they use our object storage, for example, for cold data. A data lake, for example, could be a hybrid of those where they use all-flash for high-performance parts of the data lake and our object store for the big archive of data.
And maybe building on that kind of more of a philosophical or strategic question is how -- as we think about the world shifting in that direction, how do you differentiate from competitors that are trying to do the same thing, position themselves within kind of the AI opportunity?
Yes. I think we have worked on AI for many, many years. I think that we started out with sort of predictive AI. We have hundreds and thousands of customers using predictive AI models with us. In an AI landscape, we differentiate on sort of multiple dimensions. The first is, you've got to have competitive cost performance, and we do. We have introduced a new family of products, which takes performance and scale to yet another level, the AFX family. The second is a suite of tools that allow you to manage your data efficiently because these AI environments, while they're about speed, they also need to have multi-tenancy built in cyber resilience so that somebody doesn't go and hack in and take this data that you are using for your AI models or poison it in certain ways.
You've got a variety of data management tools that make it easy to version models and data sets. And we have built those over many, many, many years. I think the third area of differentiation is on hybrid and multi-cloud. We were the pioneer in building integrated solutions in the hyperscale environment. And now we are integrating data pipeline into those hybrid -- into the hyperscaler applications. For example, we announced a capability called S3 access points with Amazon that we had worked on for a long time.
This allows an enterprise to take their data and directly pipe it into an Amazon AI tool like SageMaker or Bedrock or variety, a broad suite of tools and makes it super easy for an enterprise to use their data.
And then the last is, listen, we are one of the largest holders of unstructured data in the world, and it gives us an incumbent advantage.
Perfect. Maybe, again, staying on AI, I think as a follow-up, you mentioned, I think in the quarter, 40% of AI deals, you won were for workloads in production the quarter prior was 25% to 30%. So if we take that 200 and 300 customers, that means the number of customers that are doing workloads entering production is basically doubling sequentially, 60 to 120 quarter-over-quarter. What does this tell you about, it doesn't have to be an inflection point for kind of AI-driven enterprise data demand. But what does that tell you in terms of the momentum or the inertia? Where are we in that ball game, so to speak?
I think we are encouraged by the momentum. We follow the mix of our business every quarter. I think it's still early days for enterprise AI. We certainly see, for example, regulated industries, who have their data better organized like certain parts of public sector for national security use cases, certain parts of health care and life sciences where their data has been well organized either for advanced patient care, better diagnostics or faster drug discovery. You look in certain parts of financial services for advanced quantitative modeling, risk management, fraud detection. So it's still specific use cases, but we're starting to see better momentum across the broad mix of our business, particularly geographical. Now you're starting to see other parts of the world begin to adopt it.
And to that point, I think what I hear from you is you kind of the U.S. is leading that momentum, but you're starting to see Europe and Asia kind of start to follow.
Correct.
Okay. Cool. You also, in the quarter, I thought something that was important, you highlighted growing interest from neoclouds. You highlighted the neocloud win in the quarter. You're working with them on what you call the differentiated value proposition that brings the AFX conversation into this broader conversation.
How significant is the opportunity if we, not next quarter, but just take a big step back and say, neocloud's AFX more broadly relative to your traditional legacy markets? Maybe the first question, is just how big can that actually become?
It's still early to tell what mix of the overall AI market will happen between hyperscale, neocloud, sovereign cloud, colocation and enterprise data center, right? I think there's lots of speculation, but it's still work in progress. We want to participate as broadly as possible in all the sustainable parts of the AI landscape. We have strong solutions that we have developed over many years and strong presence in sovereign environments across the globe, national flag carriers in Asia, many of the leading European cloud service providers. And as they build their AI stacks, we are a natural partner. And so we have several wins there. With the neoclouds, we are pushing 2 sets of capabilities that allow us to stand apart in addition to super high-performance flash-based storage for training and model fine-tuning.
We also are working with them on more sustainable, longer-term business models for them by helping them bridge enterprise data into their neoclouds, just like we have done with the hyperscalers. And in the hyperscaler world, listen, we are built into many of the hyperscaler sovereign environments. For example, as they build out sovereign regions or sovereign environments for national security or for European providers, we're part of those.
So our goal is to compete as broadly as possible and to help those service providers build sustainable value by bringing enterprise clients in better solutions to them.
Does the go-to-market change significantly for you? Do you have to make significant changes to kind of capture that opportunity?
There's some optimizations like we do all the time, but we know how to co-sell with large cloud providers across the globe, and this is just another version of that.
Okay. And then I want to kind of tie that into then kind of the product set and really how that's changing, talking a lot about disaggregated architecture, private cloud, it kind of brings us back to your event last October. Just how does the rise of kind of Agentic AI and generative AI more broadly impact storage and data requirements, but then also impact the way that you think about innovation and what you need to roll out to make sure that you can stay ahead of your competitors and capture this opportunity?
Yes. Very simply, Agentic AI will hallucinate, deliver bad actions, not just bad data, if the quality of data and the guardrails put around the data are weak and frankly, compromised, right? And so for Agentic AI to work, you need a good data foundation. That data foundation needs to be fast and resilient because these agents constantly go back to the storage to ask for new sets of data to refine their reasoning.
And then the second is you need a series of data preparation and organization tools to help the models find the right data. And so we introduced the AFX platform for the first, which is super high performance, scalable storage, and then we introduced the AI data engine, which is a suite of software that allows the organizations to discover, organize and put guardrails around the data for the second challenge.
And if we now kind of take what you've said in past Analyst Days or your most recent Analyst Day, and then kind of layer on the opportunity associated with AI more broadly and how that could expand the TAM. I realize, it's early days, but just how do we think about from a growth trajectory perspective, whether that's how you think about the market or what it could pertain to NetApp. Does that -- is it too early to understand how that could reshape the growth algorithm? Or just your thoughts around how it actually could reshape that growth algorithm?
AI will definitely grow storage because you need more data to analyze your business better, and in the process of analyzing your business better, you will probably generate more data as well so that you can automate various elements of your business process. And so we expect that to accelerate storage growth over time, and we intend to be an unfair beneficiary of that by taking market share in that growing market.
Okay. I want to maybe shift from the market opportunity to the customer set. And U.S. public, we saw a nice recovery in the business last quarter, after some of the challenges that you saw earlier in the year. I guess, the simple question is has U.S. public turned the corner, but maybe the broader question is just help us understand, maybe what's shifting with that customer kind of customer cohort, how that's contributing, how you're thinking about the world as it's emerging.
Yes. I think a year ago at this time, there was a lot of disruption in U.S. public sector. Usually, the year after a new administration takes office, there is some shifting in both budget outlook, as well as which agencies get budget. And so we are accustomed to that. But if you look back a year ago, Doji was sort of running across the U.S. government looking at various elements of contracts and there was a really hard time figuring out, even if you won a deal when the deal would actually flow through the procurement process, we then had in the first half of this fiscal year, a softer U.S. government result because of the shutdown and the duration of when appropriations actually hit agencies and funding vehicles.
Q3 was a bit better as we had expected, still soft, but you saw the performance. Our performance met our expectations, although it was a bit subdued. And we are looking to see strength growing through the rest of this fiscal year for the government.
Okay. Very helpful. It took us 8 questions to get into the memory question, but I just want to make sure that we do touch on it. Interestingly, historically, in times of inflationary cost pressures, you've been able to pass through higher input costs to customers you've adjusted list prices. It has been a tailwind to both growth and margins. This period is a little bit more unprecedented to say the least, right? I'd love to just maybe at a high-level start, how does NetApp approach this situation differently, given the differences versus past memory cycles or past input cost inflation cycles?
This feels quite like the year after COVID where there were significant supply chain constraints. We work in a 360-degree manner to -- across all of our stakeholders. I think the first is the industry has over its long history, passed through commodity price increases to customers when they go up and pass through commodity price decreases to customers when they go down. So I don't think that customers see the industry as doing something unusual when we pass through price increases. We have raised prices, and we will continue to if we have to do so again, we will continue to do so. That is in line with our prior practice.
We are working with our customers and channel partners, given the dynamic nature of pricing to be more agile, meaning have shorter durations of price protections in our contracts. And conversely, when prices go down to be able to pass it through to them faster.
The timing of those adjustments are not always going to be perfectly aligned with the timing of the cost increases or decreases, right? And so we are working super hard to get those balanced. We are working -- we have done prebuys to assure ourselves of supply. Sometimes, the mix of components in the prebuys may be a little different than what we had planned than what we see because some customers will come and say, "I want this component as opposed to another one, and so in Q3, we had to go out and do some open market purchases." And in Q4, we are running ahead of our outlook. We are substantially ahead in terms of revenue relative to what we forecast. So sometimes you have to go out into the open market to procure supply.
In addition, we have multiple suppliers. We are working with pretty much every vendor in the industry to qualify alternate sources of silicon because our priority is to have available supply, on the one hand. And the second is to drive to a gross profit dollar target that we set to give us the earnings outlook that we have given the Street.
Yes. So I was going to touch on that. And the question was, I'd love, if you could maybe elaborate on that a little bit, which just as we think about how you can optimize given the input cost pressure, it sounds like a focus on optimizing for gross profit dollar growth versus maximizing gross margins. Can you maybe just double-click on that a little bit?
Yes. We have a broad portfolio of solutions, right? And so we start with, hey, position the right product for the right use case. So for example, we have a suite of hybrid flash products, which are much more economical than all-flash products for capacity and price-sensitive use cases that allows us a competitive advantage over flash-only players.
The second is to position tools like Keystone or cloud, where customers don't need to or don't want to buy a large CapEx purchase. I think with those in mind, you're always trying to balance gross margin dollars -- with gross margin percent with gross profit dollars. Ultimately, we run the company for gross profit dollars, right? Because that's the earnings engine and profitability engine of the company. But you're always trying to balance lots of different factors.
Yes. And maybe last related question is, we're still in the early days of pricing increases. And congrats because you nailed the prepurchases last summer. How have your customers responded thus far, not only to the pricing increases, but when you talk about agility in some of those shorter windows, what's the feedback that you're getting in kind of real time from your customer base?
Yes. I think, first of all, we are not the only ones who have raised prices. I think everybody in every part of the tech industry has raised prices including the PC vendors, right? So I don't think we are operating in an environment where customers don't know what's going on. I don't think anyone is happy that prices go up, but they also appreciate that we have a broad range of solutions to offer them, and they are evaluating those alternatives. And the second is, I think that we have been transparent with them, and I think they appreciate that transparency.
Okay. Good. Again, shifting to the maybe customer response, and I wrote one can envision shifts in buying patterns, you brought up Keystone. So shifting from kind of a CapEx to an OpEx model. We talked about a renewed interest in hybrid flash. Can you maybe just elaborate a little bit more on Keystone? I know it's smaller, but maybe the question is when you talk to customers, the intentions of shifting to an OpEx model, does that become some kind of permanency there? Does that become elongated? Is this specific to the environment? Or is Keystone something that in this market, it causes them to take maybe longer term changes to how they buy from you, so to speak?
Our Keystone business has been incredibly sticky. We originally brought Keystone into the market, because we thought clients had temporal use cases where they said, I'm not really sure about my plans. I want to use your Keystone as a bridge to an alternative plan, maybe to go to your cloud offerings or retire an application. What we have found is, it is incredibly sticky.
And many customers who started out saying it would be temporary now have run those environments for many years, well beyond the original contract term. I think with regard to these types of environments, we have seen in prior use cases, prior such situations, people moving the mix of how they buy to maybe cheaper alternatives to traditional flash-based solutions. We have seen them look at, hey, should I finance the environment using leasing or some other alternative? And so we expect them to continue to consider those. And perhaps Keystone is one of the really good ways that I would envision a customer looking at choices.
And then just one point of clarity. I believe Keystone is margin accretive. Can you maybe just talk to, again, the financial benefit that you get from Keystone as well there?
Yes. Keystone is, you deploy equipment at the customer premise initially, so it would be a smaller revenue and lower margin initially. But over the course of the term, it becomes very, very profitable. And so we think that as Keystone becomes a broader mix of customers with the balance of mature customers, and new adopter customers, the margin trends up. And for a mature customer, it is accretive to the gross margin profile of the company.
I want to maybe go back to a comment that you made earlier when we talked about international markets or at least geographic trends. You did mention Europe showing improvement last week. What's the strategy that you guys have for expanding in some of these maybe smaller, but because of that faster growth market. So are there specific markets where you see an outsized opportunity to either capture share or where there is faster growth that you can go after, to get to kind of change that growth algorithm?
Yes. I think the first is we have been able to outpace much larger competitors by being focused in where we deploy our resources. When you're competing with companies that are 5x your size, if you try to cover the waterfront in as many places as they do, you won't be able to beat them. And so we have concentrated our attack plan in the biggest markets, and I can tell you that, for example, in Europe, if you lose #1 position in Germany, France and the U.K., the smaller countries in Europe don't matter. They can't make it up. And we have successfully executed that strategy.
We have -- early on, many years ago, we decided that China was not going to be a durable long-term bet for American tech companies. And so we partnered with Lenovo to use their scale and local knowledge in China and built a JV that has been a good win for both companies, and we continued to do that.
Within the sort of the mature markets, North America, Europe, Western Europe are really the focus areas, and we are -- we have gotten to #1 in many of those markets. And our aspirations are to build a significant moat between #1 and #2 in those markets. We have also invested in select growth markets that we think are longer-term bets.
So India, which we think is going to be a big market over time; Middle East, which we see as an AI hub; we're expanding our investments in Korea; we see the Japanese incumbent vendors and storage are mortally wounded, so we're investing in Japan. And then in the rest of the world, we are leveraging strong partnerships with locally knowledgeable local scale players to penetrate the market.
Okay. You -- I don't think you mentioned leveraging AI for software development. And obviously, that's kind of been a big theme over the last few weeks, not necessarily in the world of hardware, but I'd love to maybe just, I don't think we've asked this question, but is there any AI disruption risk when we think about the fact that you do have differentiated software, and it's such a focus point for you guys, is there any AI disruption risk as we think about that?
Yes. We use AI tools in software development. I think that those tools require man in the middle or human in the loop to make sure that they are accurate, that they don't compromise the resilience, the performance of the system. And so you need to have a lot of knowledge of how distributed systems work to actually use AI tools. It's not like AI tools can just generate a file system, right? We are decades away from that despite what other people might say. I think the second is we are using AI tools to build velocity and productivity into our development organization, velocity measured by how much output we are able to deliver in terms of payload to bring competitive capability to the market. And productivity measured in terms of the number of get commits per developer, for example, and we're seeing encouraging trends there.
I think the third area is, we are using deep learning and machine learning models to automate the behavior of our systems to optimize the cost performance of data across its life cycle and most importantly, to enhance built-in cyber resilience capability so that we can detect anomalies or malicious behavior instantly and block it.
And I want to ask you maybe building on that in terms of what you're doing internally as we think about companies leveraging AI to be more efficient, to be productive. You mentioned some of those initiatives. What's the impact that you -- that we should maybe expect on your operating model, headcount needs, your ability to drive leverage in that OpEx base?
Yes. As you know, we have been a steady grower of operating profits over many, many years. I think our operating margins this past quarter were north of 30%. And so we feel good about the trajectory of continued discipline. We are using AI tools broadly across the company to make our go-to-market more efficient to deliver more value in products to streamline the back office. And our expectation is to continue to do that.
We will balance sort of margin accretion to invest more in the business as well. We see an opportunity in the market where we have some tailwinds from AI and cloud and some of these growth opportunities and also several weakened competitors that we can attack.
Yes. Okay. So just to make sure that -- maybe to summarize that is we'll find ways to drive efficiencies and gain efficiencies, but there is also an opportunity to reinvest, and we don't want to necessarily not do that, so to speak.
Correct.
Right. Great. Last 2 questions for me. Just kind of capital allocation and capital structure beyond share repurchases and dividends. If you could just -- I don't think anything is changing there, but just kind of maybe reinforce that. And then the second part would be just the strategic importance of M&A to either the financial model or expanding, complementing your current technology set?
Yes. I think we have been disciplined stewards of capital. We have returned in the range of 100% of free cash flow to shareholders over the last many years through a combination of dividends and buybacks. I think when we look at the go-forward opportunities, I think we will be, again, on M&A with large-scale M&A, never say never, but our strong preference is for tuck-ins, especially software tuck-ins that enhance our differentiation in capabilities like cyber or AI data prep and data pipelines.
Okay. Great. I want to give you the opportunity as we're wrapping up here. Just to maybe share the final word, and that is either what you're most excited about as we look forward, that could be what you think Wall Street might not fully appreciate about the NetApp story. But just what's the kind of final message you want to leave everyone with here?
Yes. We are excited about the opportunities that data has to transform businesses. AI is really dependent on high-quality data and unifying it is a requirement for all enterprises so that they can be successful. And we have been stewards of unifying data from 2004.
We talked about unifying different types of data, and then we talked about unifying all of the locations you have your data. And then we are adding a suite of services and capabilities to make it easier to secure your data to protect it and use it for competitive advantage.
So our multiyear view of what the enterprise will want and the bets that we have made are paying off, giving us the ability to gain share in all-flash storage, to have a unique and fast-growing high-margin cloud business that continues to create a competitive wedge against our traditional competitors and to innovate in new areas like AI, data prep, cyber resilience and new business models like Keystone.
So overall, from a top line perspective, feel really good. We have an experienced management team that has been through many of these cycles before. And so we have kind of capabilities to manage through kind of memory costs. We have a broad portfolio and different ways to serve customers, and we are disciplined operators. So I feel like we have strong long-term value creation potential in a market where traditional competitors are much, much weaker than they ever have been, and we intend to take advantage of that.
Perfect. We are just up on time. Thank you very much.
Thank you. Thank you very much for having me.
Thank you.
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NetApp — Morgan Stanley Technology
🎯 Kernbotschaft
- Kern: NetApp positioniert sich als Data‑Foundation für Enterprise‑AI: starke Q3‑Momentum, rund 300 AI‑Wins, beschleunigte Auslieferung in Produktion und wachsendes Cloud/Keystone‑Geschäft. Management betont Hybrid/Multi‑Cloud, Cyber‑Resilienz und Daten‑Governance als Entscheidungsfaktoren.
🔑 Strategische Highlights
- Produkt: AFX‑Familie (hohe Performance/Skalierbarkeit) plus AI Data Engine für Daten‑Vorbereitung, Versionierung und Guardrails.
- Cloud: Cloudgeschäft ex‑Spot +17% YoY; First‑party & Marketplace +27% YoY; S3 Access Points mit AWS zur direkten Daten‑Pipelining‑Integration.
- GTM & Modelle: Keystone als sticky OpEx‑Angebot, starkes Wachstum (~65–68% YoY) und langfristig margin‑akzretiv.
🆕 Neue Informationen
- Neu: Keine geänderte Finanz‑Guidance, aber Management meldet Q4‑Revenue deutlich über der eigenen Outlook‑Prognose; konkrete Ergänzungen vor allem operative Detail‑Farbe zu AI‑Workload‑Mix, Neocloud‑Wins und Supply‑Flexibilisierung.
❓ Fragen der Analysten
- AI‑Produktion: Nachfrageverlagerung: Anteil produktiver AI‑Workloads stieg nennenswert (Sequenzanstieg von ~25–30% auf ~40% der Deals); Analysten fragten nach Nachhaltigkeit und Skaleneffekten.
- Neoclouds & GTM: Nachfrage nach Größe des Neocloud‑Opportunities; Management nannte mehrere Wins, vermied aber konkrete TAM‑Prognose — zu früh, um Mix zu quantifizieren.
- Inputkosten: Memory/Komponentenpreise & Preisdurchsetzung — Fragen zu Preisanpassungen, Prebuys und Optimierung auf Gross‑Profit‑Dollar; Management erklärt agile Preisfenster und Multi‑Supplier‑Strategie.
⚡ Bottom Line
- Fazit: NetApp liefert klare Narrative: AI und Cloud treiben Nachfrage, Keystone sorgt für wiederkehrende Einnahmen, AFX/AI‑Software stärken Differenzierung. Wichtige Risikotreiber bleiben Inputkosten, Supply‑Mix und die Geschwindigkeit, mit der AI‑Projekte in breite Produktion gelangen. Für Aktionäre bedeutet das: ausgewogenes Upside durch Marktanteilsgewinne bei zugleich beobachtbarem Execution‑ und Kostenrisiko.
NetApp — Q3 2026 Earnings Call
1. Management Discussion
Good day, and welcome to the NetApp Third Quarter of Fiscal Year 2026 Earnings Call. [Operator Instructions] Please note, this event is being recorded.
I would now like to turn the conference over to Kris Newton, Vice President, Investor Relations. Please go ahead, ma'am.
Hi, everyone. Thanks for joining us. With me today are our CEO, George Kurian; and CFO, Wissam Jabre.
This call is being webcast live and will be available for replay on our website at netapp.com.
During today's call, we will make forward-looking statements and projections with respect to our financial outlook and future prospects, including, without limitation, our guidance for the fourth quarter and fiscal year 2026, our expectations regarding future revenue, profitability and shareholder returns and other growth initiatives and strategies. These statements are subject to various risks and uncertainties, which may cause our actual results to differ materially.
For more information, please refer to the documents we file from time to time with the SEC and on our website, including our most recent Form 10-K and Form 10-Q. We disclaim any obligation to update our forward-looking statements and projections.
During the call, all financial measures presented will be non-GAAP unless otherwise indicated. Reconciliations of GAAP to non-GAAP measures are available on our website.
I'll now turn the call over to George.
Thank you, Kris. Good afternoon, everyone. Thank you for joining us today.
We delivered another strong quarter with Q3 revenue of $1.71 billion, an increase of 4% year-over-year. Excluding the divested Spot business, total revenue was up 6%. Our accelerating growth, coupled with continued operational discipline has enabled us to drive profitability metrics higher. Operating income and EPS achieved record highs. We are in a strong position to deliver sustained growth and are on track to deliver our strongest year yet.
I'm proud to share a marquee moment that underscores our pivotal role as the intelligent backbone for modern data-driven innovation. The Super Bowl is more than the biggest sports event of the year. It is a global showcase of innovation and partnership. During Super Bowl LX, our technology transformed Levi's Stadium into an interactive data center. We manage billions of data points powering everything from video boards to real-time inventory and security operations. In this most demanding, no-fail environment, we demonstrated our ability to deliver flawlessly.
In the AI era, organizations face security threats, fragmented architectures, shortage of expertise and operational complexity, which make it difficult to unify and harness data for its full potential. We help enterprises solve these pressing data challenges by delivering a data platform that is optimized, secured and AI ready. Customers rely on NetApp technologies to be the data foundation to support AI innovation, modernize data infrastructure, strengthen cyber resilience and transform cloud strategies.
In Q3, approximately 300 customers selected NetApp to help prepare their data for AI and to be the storage foundation for their AI innovations. Last October, we announced major enhancements to our enterprise-grade data platform for AI workloads. These new solutions, AFX and AI data engines are generating significant customer interest and engagement. AFX is our disaggregated storage system purpose built for AI that gives customers the benefit of enterprise-grade security and capabilities, coupled with extreme performance and scale.
We are excited to report strong early momentum in AFX in its first quarter of shipment. We have secured significant AFX wins across key industries, including neocloud, financial services and semiconductor. An example of an early AFX win is for model training and fine-tuning at a neocloud. AFX stood out among competitive disaggregated architectures for its multi-tenant management, container integration, cyber resilience and replication capabilities.
One of the biggest challenges in AI is data. The AI data engine helps to improve time to value in AI projects by simplifying workflows with integrated data discovery, curation, policy-driven guardrails and real-time vectorization for Gen AI. By understanding where their data is, customers can ramp AI projects faster, boost results accuracy and slash time to insight. Our early access program has been highly successful, engaging customers from key industries such as semiconductor, media and entertainment, financial services and IT services. AIDE will be generally available in Q4.
NetApp helps customers modernize their environments with a unified adaptive data foundation that extends across on-premises and cloud, delivering high performance, availability and integrated security. As data center demands grow, customers are leveraging all-flash arrays to achieve density and power requirements, strong customer engagement and interest in our unified and block optimized all-flash storage portfolio, delivered another record all-flash array revenue quarter, growing 11% year-over-year to $1 billion in Q3 for an annualized run rate of $4.2 billion.
The importance of our robust cyber resilience capabilities cannot be overstated as customers look to safeguard their most valuable asset, data. The NetApp data platform delivers comprehensive ransomware protection, backup disaster recovery and data governance in a single secure foundation that reduces the time to detect anomalies, recover data and get our customers back to business. Embedded protections and our ransomware recovery guarantee help customers confidently withstand today's sophisticated threats and prepare for tomorrow's challenges.
These capabilities foster trust in NetApp in an increasingly volatile digital landscape, enabling us to win new customers and displace competitors. An example of this is a European financial services company needing to refresh its entire data center to enable scalability and compliance with current regulations. In Q3, this customer selected NetApp all-flash systems to replace multiple competitors. Critical to the win were our anti-ransomware services, data classification, and write once, read many snapshots, delivering business continuity, robust data protection and regulatory compliance while positioning the customer to manage future growth.
Keystone, our storage as a service offering continues to perform well as customers navigate infrastructure transitions, cloud migrations and rising memory costs. Keystone revenue grew approximately 65% from Q3 a year ago. In Q3, an insurance technology company planning a multiyear migration to the cloud selected NetApp Keystone as the storage solution to enable this transition. This new to NetApp customer selected Keystone for a fast and efficient way to eliminate a competitor storage as a service footprint that did not offer a true path to the cloud. As that example demonstrates, our first-party relationships with the hyperscale cloud providers is a real differentiator for us.
Adjusted for the Spot divestiture, our public cloud services revenue grew 17% year-over-year driven by first-party and marketplace services, which grew 27%. These services are a powerful driver for new customer acquisition. About half of the revenue driven by new first-party and marketplace customers in Q3 came from new to NetApp customers, highlighting the role cloud play in expanding our customer base.
Let me share a couple of examples of how our cloud services are displacing competitors. A multinational insurance company aiming to overcome the complexity of its legacy infrastructure and improved agility selected Azure NetApp Files for its proven performance, ease of use and enterprise-grade reliability, ANF is now the cornerstone of their cloud transformation.
Similarly, a retailer after experiencing a ransomware attack, moved off a competitor's infrastructure to the cloud. They chose AWS FSx for NetApp ONTAP for its support of immutable volume copies, providing data protection against cyber attacks. FSxN is now their default storage service in AWS.
As a leading enterprise storage solution provider and the only one with first-party data storage services native to the public cloud, NetApp is uniquely equipped to help customers easily connect their data with the leading cloud-based AI applications and accelerate modern workloads like AI in the cloud. In Q3, we introduced a new capability, enabling Amazon S3 access points for Amazon FSx for NetApp ONTAP. This allows enterprises to make their workflow simpler and more efficient by connecting the many AWS AI and analytics services directly with their NetApp data, both in the cloud and on-premises. Also in Q3, we announced the public preview of Object REST API on Azure NetApp Files, enabling seamless real-time integration between an organization's data and Azure's advanced analytics and AI services.
With direct and secure access to enterprise data, companies can extract actionable insights and make data-driven decisions faster giving them a competitive edge in an increasingly data-driven world. Already, these connections are being used by customers. In Q3, a multinational manufacturing company selected FSxN as the high-performance data layer for its AI workloads on AWS. The customers leveraging our recently introduced S3 support to bring AI to its large existing trial-based data sets without having to duplicate or replatform its data.
Before I wrap up, I'd like to address how we are managing through the unprecedented inflation in memory prices currently affecting the global market. First, we have raised our pricing and will do so again as needed. Second, we are working with our customers and channel partners to be more agile in this dynamic environment. Third, we are working with our multiple suppliers to address availability and manage costs as we have successfully done in the past. And finally, unlike our all-flash-only competitors, we have a broad portfolio that includes hybrid flash arrays giving us the opportunity to better service price-sensitive workloads.
In summary, solid execution and operational discipline delivered another strong quarter. Customers are choosing NetApp for our unified data platform that delivers exceptional value and operational efficiencies, solidifying our position as the intelligent data backbone for the AI era.
As I look to the future, I am confident in the opportunity ahead and in our ability to successfully execute on our strategic plan. We will continue to invest in key areas that drive growth and provide long-term value for our shareholders.
I'll now hand it over to Wissam.
Thanks, George, and good afternoon, everyone.
As George mentioned, in the fiscal third quarter, we delivered strong results, exceeding both the midpoint of the revenue guidance range and the high end of the EPS guidance range. Total revenue for the quarter was $1.71 billion, up 4% year-over-year. Non-GAAP earnings per share was $2.12, up 11% year-over-year.
Excluding the divested Spot business, which generated $25 million of revenue in the third quarter of the prior year, total revenue was up 6% year-over-year. The effect of foreign currency exchange rates was favorable to revenue growth by approximately 2 percentage points year-over-year, while it was immaterial relative to guidance.
Looking at revenue by segment. Hybrid Cloud revenue of $1.54 billion was up 5% year-over-year, driven by product, support and Keystone. Keystone continues to build momentum with revenue growth of approximately 65% year-over-year. Public Cloud revenue of $174 million was in line with last year's third quarter revenue. Excluding Spot, Public Cloud revenue was up 17% year-over-year, driven by strong demand for first-party and marketplace storage services.
At the end of the quarter, our deferred revenue balance was $4.63 billion, up 12% year-over-year and 9% year-over-year in constant currency. Remaining performance obligations were $5.11 billion, growing 14% year-over-year. Unbilled RPO, a key indicator of future Keystone revenue was $482 million, up 38% year-over-year.
Moving to the rest of the income statement. Please note, my comments will be related to non-GAAP results unless stated otherwise. Gross margin for the fiscal third quarter was 71.2%, up 50 basis points year-over-year, driven by Public Cloud gross margin expansion. Gross profit was $1.22 billion, up 5% compared to Q3 2025.
Hybrid Cloud gross margin was 69.6%, down 1.8 percentage points sequentially as product gross margin declined by 4.2 percentage points to 55.3%. This was primarily due to an unfavorable revenue mix and to a lesser extent, the need to make market purchases to be unexpectedly higher demand for certain products.
Our Support business continues to be highly profitable at 92.5%. Professional Services gross margin was 31.3%, improving 100 basis points sequentially, driven by higher Keystone revenue mix. Public Cloud gross margin was 85.1%, up approximately 2 percentage points sequentially and approximately 9 percentage points year-over-year.
Operating expenses of $686 million were down 3% sequentially. Operating expenses were up 3% year-over-year, in part due to the unfavorable effect of foreign currency exchange rates. Operating income was $533 million, up 8% compared to Q3 2025. Operating margin was 31.1%, up 1.1 percentage points year-over-year.
Earnings per share was $2.12, growing 11% year-over-year, exceeding the high end of our guidance range.
Our results demonstrate strong execution on key revenue growth opportunities in all-flash, Public Cloud and AI, along with the continued focus on operational discipline, resulting in record highs in both quarterly operating income and EPS.
Cash flow from operations was $317 million and free cash flow generation was $271 million. During the quarter, we returned $303 million of capital to our shareholders, with $200 million in share repurchases and $103 million paid in dividends of $0.52 per share. The Q3 diluted share count of 200 million decreased by 8 million shares or 4% year-over-year. Cash and short-term investments were $3 billion. And gross debt outstanding was $2.5 billion, resulting in a net cash position of $522 million.
I'll now turn to non-GAAP guidance, starting with Q4. We expect revenue of $1.87 billion, plus or minus $75 million. At the midpoint, this implies a growth of 8% year-over-year. Excluding the divested Spot business from the year ago comparison, our revenue guidance implies a 9% growth. We expect Q4 gross margin to be between 69.5% and 70.5%. Operating margin is anticipated to be in the range of 30.5% to 31.5%. We expect EPS to be between $2.21 and $2.31.
Turning to full year 2026. We now expect fiscal year 2026 revenue to be between $6.772 billion and $6.922 billion, which at the $6.847 billion midpoint, reflects 4% growth year-over-year. Excluding Spot, our revenue guidance implies a growth of 5% year-over-year. We expect gross margin to be in the range of 70.7% to 71.7% and operating margin to be in the range of 29.3% and to 30.3%. Other income and expenses are anticipated to result in approximately a $24 million net expense.
For the year, the tax rate is expected to be in the range of 20.2% to 21.2%. EPS is expected to be in the range of $7.92 to $8.02.
In closing, as we look ahead to the rest of the fiscal year, we remain committed to our strategic vision and are confident in our ability to navigate this dynamic environment. Our focus on revenue growth and disciplined execution is yielding positive results and record profitability. We are dedicated to delivering exceptional long-term value to our customers and shareholders.
I'll now turn the call over to Kris for Q&A.
Thanks, Wissam. Operator, let's begin the Q&A.
[Operator Instructions] We'll go first to Param Singh from Oppenheimer.
2. Question Answer
Really appreciate if you could give some more color on what's driving this incremental growth on the product side. What are you seeing in terms of adoption? And how persistent is that?
We have, as we guided from the start of the year, been working on large deals that for many quarters, some of those deals closed in Q3 and a number of them are expected to close in Q4. And so we're excited about the momentum in our business and ability to close these large deals.
Got it. And maybe one for Wissam. Look, the product gross margin, obviously, is going to be a little bit difficult to manage in this pricing environment. Help us think through what can you pass through to customers? What's your supply chain agreements? And can you get enough componentry not only on the DRAM and NAND side, but also on the HDDs.
Yes, sure. Thanks for the question. So look, as we've said all along, we are operating in a dynamic environment. Commodity prices are increasing at fast pace. However, we do have agility and the ability also to manage the situation through either adjusting prices working with our customers and partners and partners to be more agile. And we also have our products qualified at several suppliers that we work very closely with to understand what the supply is doing and negotiate prices in advance where we can. And also, we have the ability to offer alternatives for some of our customers for price-sensitive workloads, we have the ability to offer our hybrid flash array or for some customers who have much more interest in the consumption model, we can go for our Keystone, which is storage as a service or our Public Cloud business.
With respect to maybe the second part of your question, you mentioned also hard drives. We are seeing some price increases there, but it's nothing compared to the rest of the components we're seeing, for instance, on the NAND memory, obviously, has been in the news for quite some time and other types of semiconductor supply chain.
Katherine Murphy from Goldman Sachs has the next question.
You talked about 300 AI deals signed in the quarter, up from 200 in the previous quarter. And I was wondering if there's anything you could share here about the mix across use cases and customer types, if there's any areas you're seeing particular traction. And just as a follow-up, anything you could share to help us think about the potential contributions of AFX and AIDE as we think about 2027 and what the potential margin profile would look like there?
We have seen strong momentum in our AI business across multiple industries, public sector, manufacturing, health care and life sciences and financial services in particular as well as early signs of adoption of AI in semiconductors, for example. In each of those cases, our hybrid architecture, our ability to deliver performance at scale with a rich set of data management capabilities has us standing out.
With the introduction of the AFX, we are also seeing momentum in the neoclouds for use cases such as model training and fine-tuning. In terms of the outlook for AFX and AIDE. AFX is a new architecture, so it requires qualification by customers. It comes with a proven software set, but still, customers will test and adopt it. We were ahead of our expectations in the first quarter of availability, but we are also not predicting a ramp like you saw, for example, with the C-Series, AIDE provides differentiation not only for new environments, but also for brownfield environments where customers can expand the value from their existing investments with us. and we'll tell you more on the outlook of these products as we head into the next fiscal year.
The next question is from Samik Chatterjee, JPMorgan.
George, maybe if I can start with your price increases and if you can share what is the magnitude of the price increases you've taken? And how are you seeing sort of customers respond to it? I assume if prices are going up, customer budgets don't flex up to the same extent? Or what are you seeing sort of as a typical customer response to that? And I have a quick follow-up.
Yes. We raised prices at the start of this quarter, and those increases were roughly in line with what you saw in the market. It varies, of course, by type of product. With regard to customers, we have said for many, many, many years, customers budget in dollars, not in systems, and those dollars are tied to their IT spending priorities. We offer them a range of options as Wissam mentioned earlier, hybrid flash, all-flash, Keystone consumption, cloud offerings as well as a huge range of features to optimize the use of flash in their existing systems to give them more value. And so those conversations are ongoing, just like they've been every quarter for many years.
Got it. Got it. And maybe for Wissam, if you can walk us through the gross margin drivers at the company level between sort of 3Q and 4Q? And is it really the moderation just driven by product gross margin. And I think on the last call, you had outlined that you still believe that when it comes to fiscal '27 gross margins can still be sort of basically flat over fiscal '26, even with memory prices going up. Is that still your expectation because memory prices have changed quite a bit over the last sort of 90 days?
So let me start with -- there's a few parts of the question. Let me start with Q3. Look, Q3 to Q4, really, the dynamics moving from quarters is very much driven by the revenue mix, the component of the revenue mix. When we look at Q3 versus Q4 revenue, we're seeing growth across the board. And so just the revenue mix is pretty much what's driving these components. And what's driving the ultimate 70% midpoint, let's say, on the guidance.
When I look at fiscal '27, one, I think it's too early for us to really guide to '27. And I don't recall necessarily saying that we're expecting to be to be in line as much as to say that we would be very actively managing our business, like I mentioned earlier, with respect to working with our suppliers to track the plan as much in advance as possible and where there is opportunities for us to lock in prices to do that, but also working through our -- with our customers to maintain that agility and help them find the right solutions for them in an environment that's dynamic, to also adjusting prices if needed to make sure we continue to protect our profitability.
Look, as we think through our product margin, I would say really a couple of things. One is our long-term product gross margin target is still that sort of mid-50s to high 50%. And then the second thing I would say is, from a company perspective, we really are focused on the total company margin. But more importantly, we're also focused on the gross profit. because we believe that gross profit for the company is really what drives our earnings growth.
The next question is from Aaron Rakers, Wells Fargo.
Just to kind of build off that last question a little bit. Wissam, maybe it would be helpful to appreciate what are you seeing from a pricing perspective, particularly on NAND flash? What's kind of embedded in your gross margin assumptions today?
And then talk a little bit about the duration or how the duration of your supply commitments have changed. I think in the last couple of quarters, you kind of talked about having good visibility through the fiscal year. But how has that evolved to kind of think about next fiscal year and any inputs into that?
So look, I mean we talked about also when you look at Q3, for instance, sometimes we have mix that is not as predictable. We did have to buy a little bit in the open market or basically replenish some inventories in Q3 because we had some unexpected high demand on certain products. But as we look for fiscal '26, the dynamics haven't changed from what we discussed before. We're still mostly covered from our prebuys that we did earlier in the fiscal year.
For Q4, we may have some demand where we're replenishing inventory. I'd rather not talk much about fiscal '27, given that we're still focused on really closing the fiscal '26 in a strong way. And there's a lot of -- I mean, as you know, this is a very dynamic environment. I wouldn't want to sort of make a statement on duration of cycle or [ any ] comments on the price, that's not necessarily my area of expertise.
Maybe I can just comment on the price increases. We did raise at the start of the quarter. As we have said many times, it takes a little while for those to be actually actionable at customers because we want to give them some amount of time to plan their purchases. And so we typically give customers a period of time like 90 days to 120 days to manage their purchasing agreements with us. So we raised prices at the start of this quarter, and we'll give you an update when we report the quarter.
Yes. Very helpful. And as a quick follow-up in this environment, I'm curious, you kind of alluded to, I think, the fourth point you highlighted in your prepared comments. You do have a hybrid product portfolio. Are you seeing customers actively maybe move away from deciding to go all-flash back to hybrid, maybe Keystone versus CapEx-centric purchases? Any change in behavior that you're seeing across customers in that regard?
It's too early to draw a trend. We are certainly seeing more interest from customers around some of those topics that you mentioned, hybrid flash, Keystone and other alternatives.
Wamsi Mohan from Bank of America has the next question.
Maybe, George, you can just help us think about some of the purchasing behavior trends you're seeing in storage if there's any concern around supply availability, which is causing people to perhaps prebuy, perhaps prebuy ahead of some of the price increases that the industry knows is coming. It'd be helpful to get sort of what you're picking up from your customer conversations. And I have a quick follow-up.
Yes. Thanks for the question, Wamsi. While we can certainly understand the behavior that you were describing, our Q3 results were not a result of pull-ins. And importantly, our Q4 guidance does not rely on pull-ins.
As we have said from the start of this fiscal year, we expected increasing momentum through the second half of the year for a few different reasons. First, as we said, Europe started to get better through the second quarter. And as you saw in Q3, we have increased momentum in Europe. We said that U.S. public sector would be less of a headwind in the second half of the year, and while it hasn't fully recovered, it was -- met our softer expectations in Q3. And we said that we were working on large deals that would happen in the second half of the year at the start of our fiscal. And we have been working on those deals. And we have seen some of them come through in Q3, and we expect more to come through in Q4.
Finally, with regard to what we see broadly in the market, IT spending has always been tied to customers' business outlook. And what we see today is that business outlook is pretty favorable. It is quite similar to what we saw last quarter, but in certain markets like Europe, things are picking up. And so IT spending, you can see in the public reports is expected to be reasonably durable this coming 12 months.
Customers then prioritize business projects and associated with those business projects, infrastructure projects, like we said, cyber resilience, cloud transformation, data center infrastructure upgrades, as well as AI projects, and we are well positioned to capture our share of those markets. And we are seeing that reflected in the mix of our business, high performance flash to support AI workloads growing number of AI use cases and of course, growth in cloud. We'll tell you more. It's a dynamic environment. We'll tell you more when we report next quarter.
Okay. And a quick follow-up. How do you feel about the supply availability on SSDs as you go into next year? There's been a lot of talk about memory companies coming back to renegotiate pricing at a faster rate, not necessarily honoring all the LTAs that were put in place prior. Obviously, you guys have a lot of scale. So just wondering what you're seeing on that end from a component both availability and negotiation standpoint of if that's -- the window of that is shrinking from maybe a quarterly negotiation to a monthly negotiation? And any color on LTAs, too.
Yes. I think we work very closely every year and every quarter with a broad base of suppliers for virtually every component in our systems. We are not experiencing any supply shortages at this time and are not aware of any that is upcoming. Of course, it's a dynamic environment. And so we are staying super close to our suppliers, qualifying multiple different components so that we have, first, access to supply so that we can meet customer demand; and second, competitive price points for those supply. So these are dynamic. It's not -- we don't see any specific trend to comment, Wamsi, other than, listen, we're engaged like we always have been with our suppliers.
The next question is from Erik Woodring, Morgan Stanley.
George, not to belabor the point here on memory inflation, but if you take some of the public views on future memory price hikes, we could be in store -- the industry could be in store for multiple price hikes this year. I would just love to know how you approach balancing protecting margins and keeping those product gross margins within the mid- to high 50% range, while also limiting the risk of demand destruction or even market share losses? I know historically, storage has an elasticity of less than 1, but we're in pretty unprecedented time. So just curious how you're thinking about balancing that in this environment.
Yes. Listen, I think that we anticipate pricing and the sort of the tight supply environment to continue for a period of time. And so we are not expecting this to be a short-term issue. I think, as we said, the first thing is to make sure we have adequate supply across multiple suppliers to both assure that we can meet customer demand as well as so that we can have competitive positions in the market from a pricing standpoint.
With regard to our operating model, listen, it's -- every quarter has puts and takes. There are deals that we want to be competitive on and there are deals where we say, listen, we probably don't want to be a part of that specific transaction. And I think those continue to date. I think with regard to our kind of operating model, as we said, as Wissam mentioned, our core focus is to drive gross profit dollars because that, in turn, drives the earnings per share model of the company. I think, of course, within that, we look at matching supplier cost to us with our pricing to customers while respecting that it may not happen immediately because we want to give customers some time to adjust. And so that's kind of how we are operating.
I think that -- with regard to demand, I think as we have said many, many, many times, customers budget in dollars and they budget against business priorities. It is our responsibility to be in the spending priority stream of our customers and to give them the best value offering for the budget dollars they have to spend, and so we bring a lot of different options. We bring competitive storage-efficient flash, we bring hybrid flash solutions. We'll bring cloud solutions. We'll bring Keystone and we'll bring the full portfolio. Just like we do every quarter, certainly now it's an elevated environment, and so we'll do even more of that.
Okay. Understood. And then just a quick follow-up maybe for you, Wissam, and maybe it's a clarification. But I think when we look -- when you were talking about fiscal 3Q product gross margins, you were talking about kind of unfavorable mix as the reason why margins were down sequentially. All-flash was up 11%, that was stronger than your overall product growth. So can you just maybe help us better understand why mix was the headwind to product gross margins when that part of your business, when all-flash was outperforming. We just want to make sure I understand that dynamic.
Yes, of course, Erik. So when we talk about revenue mix, it could be the multitude of things or a combination thereof. Revenue mix is driven by geos, by customer type, by customer, by product. And so there's multitude of things that contributed to that. I wouldn't want to get in more details than this.
Krish Sankar from TD Cowen is up next.
Two of them. George, first one, I'm just kind of curious, where do you think we are in enterprise AI storage adoption cycle. It looks like last year, they were still going through pilot and data preparedness. Do you think we enter production this year? Or do you think that's still TBD? And then I have a follow-up.
I think, as we said, our AI business has grown in terms of AI customer wins. I think this quarter, a year ago, it was around 100-plus wins, it's now close to 300. So we're seeing acceleration in our AI business. Within the AI business itself, there are industries and use cases that are certainly more advanced and more repeatable in customers, and there are others that are further behind.
So for example, in regulated industries where their data is well organized, you are seeing customers put stuff into production or if you want to call it a pilot, it's a very large-scale pilot. Health care, life sciences, some parts of public sector, manufacturing, there are lots of use cases there that are starting to progress well beyond what's the pilot. Within our mix of business this quarter, roughly 60% were still in the data prep, data readiness, data lake models and 40% were in production, training or production inferencing use cases.
Got it. Got it. And then just a quick follow-up. In the past, like your visibility on lead times for storage used to be a few months. Has that changed now with the memory dynamics, i.e., commodity costs going up, [ you're ] raising prices, has that really changed the visibility timeline?
Listen, it's certainly a dynamic environment. We are staying on top of lead times. I think that it would be inappropriate of me to say that lead times are uniformly extending. We're not experiencing that. There are, of course, specific components that might be on one configuration that are causing a longer lead time. We're not experiencing anything across the board and so far. And we are working hard to bring alternate silicon into those configurations so that we can meet reasonable lead times.
As you know, in the prior supply chain situation that we experienced a few years ago, we were able to manage through that without having really long extended lead times because we use merchant silicon that's off the shelf. And we have multiple suppliers who we qualify for a particular piece of silicon. That being said, it's dynamic, and we're staying on top of it.
The next question is from Steven Fox, Fox Advisors.
I guess I was just curious if you can provide more color going forward as NAND prices go higher, your assumptions on sort of hybrid arrays selling more? Are you seeing -- can you maybe talk about how much replacement demand you're seeing from customers that were looking at maybe lower-end AFAs now are going into hybrids replacement into other consigned business, et cetera. How does that mix look going forward?
I think it's a great question. It is a topic of ongoing discussion at our customers. As we said earlier, we raised prices at the start of this quarter. And so that has triggered some of the discussions with customers about what's the optimal architecture, and we are seeing more discussions of HFA. It's too early for me to say it's a trend, but there are certainly a lot more discussions once we raise prices, and those price increases were more on AFA rather than HFA.
And I know you said that, obviously, HDD prices aren't going up nearly as much as NAND prices. But can you just give us a sense for ability to procure HDDs at this point going forward?
Yes. Listen, I think that we are well aware of the constraints in the market. So far, on HDDs, we feel good about our ability to procure what we need even with an elevated demand picture potentially. I think that specifically, we use HDDs that are dissimilar to the ones that are in short supply. We are not buying the highest capacity HDDs, which are the ones that are more constrained. I hope that gives you enough color.
Tim Long from Barclays has the next question.
Let's see if I can get a prize for asking 2 without one of them being on memory. So maybe eleven here. Can you just touch on the Public Cloud business, maybe 2-parter on the Public Cloud business. Excluding Spot, I think we've been running in this high teens range for the last several quarters here. Talk to us a little bit about going forward how you think we could potentially break out of that range? Are there any new offerings or new customer sets or anything that you see in the pipeline that could maybe accelerate the growth in that piece of the business?
And then related to that, obviously, the gross margin in the Public Cloud was really high, I think, kind of above ranges. So Wissam, if you could talk a little bit about profitability of that business and how much more room is there, or are we kind of tapped out on the margin side for Public Cloud?
I'll take the first one. Thank you for the question. With regard to continued growth in Public Cloud, it's sort of threefold. One is to take the new customers who we continue to add at a good clip, get them to adopt more and more of our portfolio. We call that cohort management, and it's really expanding within our growing customer set to use more of our technology. That includes offering different price points for storage solution, adding new capabilities and so on.
The second is to connect into the AI growth rates of the hyperscalers. I think you saw us bring innovations to the market like S3 access points for AWS that allows customers to use their AWS' broad suite of tools alongside our storage solutions. This gives us the ability to expand into new wallet opportunities and customers.
And then the third is to scale go to market. I think we have done a good job in certain countries. We need to leverage more indirect routes to market as well as broaden the number of places we are growing. And you will see us continue to look at ways to invest to grow the business. It is a highly profitable business, and it's extraordinarily sticky.
And so I'll turn it over to Wissam for the second part.
Yes. And Tim, for the second part, we did provide the long-term range being 80% to 85% from a profitability perspective on the gross margin line for the Public Cloud business. Obviously, we are at the high end of that range in Q3, and we're comfortable operating at this level for now. I wouldn't say we're tapped out, but it's also too early for us to sort of move from that range.
The nice thing about the Public Cloud business, when you sort of put it also in the context of the overall company, if we go back to the comments around the margin for the total company and the gross profit for the total company, it is an accretive business and it's growing at a faster pace than the rest of our revenue streams. So all in all, it [ cuts us ] on the margin line.
Next question comes from Jason Ader, William Blair.
Just firstly, on the Q4 gross margin guidance. It just seems to imply if we keep everything else kind of equal, it seems to imply that the product gross margin will be sort of flattish sequentially, and I wanted to just confirm that, that's the right way to think about it, Wissam.
So Jason, without getting into a lot of the details on line by line, as I said earlier, when you look at the Q4 guidance for gross margin, really, the dynamics quarter-to-quarter are driven by very much the overall components of the revenue, basically, the revenue mix.
Right. But I mean like the other parts of the business, the cost of services has been pretty much 84-ish percent, right? So that was -- I'm just trying to do the math here based on what your guidance was. I just wanted to make sure that there's nothing on the maybe cost of services side that should be called out that would vary from where you've been over the last couple of quarters?
I mean, to your point, typically, there's sometimes minor fluctuations quarter-to-quarter on these lines. And so I really would rather not get into the line-by-line guidance because we typically guide [ for the ] total company. But yes, when you look at sort of the various components, there's fluctuations, minor fluctuations quarter-to-quarter.
Okay. Great. And then for George. George, as you kind of look at the just dramatic improvements, especially on the software engineering side that AI is bringing to bear, how are you thinking about the development organization at NetApp? Are you continuing to hire? Is this an area where you think there could be some pretty substantial efficiencies over the next couple of years at NetApp? Just what's your overall philosophy strategy at this moment? You may have seen there's some chatter today, the company Square is like laying off like half its workforce. So I know that's maybe a very extreme example, but -- and they're doing great. So it's just -- it's basically about AI and efficiency. Maybe just speak to that larger topic.
Yes. I think, listen, we have been prudent stewards of expenditure. Our operating margins are north of 30%, right? And so we will continue to look for efficiencies with regard to using AI to develop software. We already do so. And our first priority is to, at this moment of weakness for many competitors, to accelerate the amount of innovation we put into market. And so while we'll always look to be prudent and optimize spending to the right parts of the business, we also see that it's important for us to continue to bring innovation so that we can capitalize on some of our weaker competitors. And you'll see us provide more instructive direction on that as we go through the next fiscal year.
We'll take the next question from David Vogt, UBS.
So George, I jumped on late, I might have missed this. Have you seen a recovery in sort of the federal category that's been sort of an albatross in the industry for a while. And the reason why I'm asking is you said you saw some orders that you've been working on for a couple of quarters close. And what is kind of your expectation or that particular vertical as we move forward given sort of all the noise, particularly out of [ TC ] as of late. And then I have a follow-up for Wissam.
Yes. At the end of last quarter, we said that our outlook for the second half of the year was cautiously optimistic. We said that we saw people starting to come back to work in our Q3, but it was too early for us to see broad-based funding into programs translating into orders. We met our cautious expectations in our expectations for Q4 is that it improves from Q3. And then we'll tell you more about next year when we get to next year. I think that Q2 was, of course, because of the shutdown [ of ] severe impairment. Our expectation is that Q3 and Q4 were better than that, it's too early to comment whether it's robust yet.
Got it. Okay. And for Wissam, I know I might have missed this again. I didn't catch in either the prepared remarks or any responses to a question regarding your purchase commitments. I know you talked about you're covered based on the inventory and kind of the commitments that you've made. Can you kind of share with us sort of the magnitude of the purchase commitments that you have on balance and so we can kind of get a sense of how to think about that playing out over the next couple of quarters? And when we think about that also, what is sort of the working capital commitment or obviously, your program or your strategy to mitigate sort of the higher component costs that are flowing through the market right now?
Yes. So we didn't talk much about the purchase commitments. But I would say for fiscal '26, there isn't much of a change from what we talked about from what we talked about last quarter, David. I mean we did replenish some inventory in Q3, we're probably doing some in Q4 just to make sure that we have what we need from a mix perspective to deliver the revenue. It's too early to talk about fiscal '27. Obviously, our supply chain team works with all of our suppliers on a regular basis, as George mentioned earlier, and we continue to work to -- with -- the top priority for us is to ensure supply availability and then, of course, to be able to negotiate whatever pricing, better prices or best prices that we can.
Relative to working capital, look, we have a very strong balance sheet and there is no concern there if we need to take action to secure supply or protect or better pricing or do a combination of the two, then we have plenty of flexibility. And also sometimes we work with third-party logistics companies that could help with that. So this -- from my perspective, there's no concern on working capital fluctuations.
The next question is Simon Leopold, Raymond James.
I wanted to see if you could talk a little bit about the competitive environment, specifically in light of price adjustments. And what I'm trying to understand is, is every participate in every vendor raising price by the same amount at the same time. How much variation is there? And how should we think about this dynamic?
Thanks for your question. It's always been a competitive industry, and our -- most of the players in the market are rational. With regard to the price at the customer versus the list price, different vendors take different approaches. Some of them raised list prices and have the same discount level. Others may not raise list prices as much. But restrict discounting.
The net of it is everybody is roughly in the same boat in terms of the cost structure of their commodity supply. And so it really becomes around the software value you bring, the range of offerings that you can present to customers and the discipline at which you run your business. And so we don't see much deviation from that. I think one of the places that we have are sort of working on it to position the right offering for the right use case, particularly HSAs are starting to see a lot of interest from customers. And it's too early to comment whether that's a trend, but there's certainly a lot more discussion about that going on.
The next question is from Alek Valero, Loop Capital.
Alek on for Ananda. So my question is, how do you see the rise of AI agents impacting, first off, your AI business? And how should we think about the progression from where we are today in early adoption to a point where AI agents become a meaningful part of -- drive a meaningful part of your revenue and demand for your products?
I think it's a long question, but I'll try to give you a couple of short answers, right? I think, one is AI agents depend on high-quality data and good guardrails so that they don't make mistakes. We have introduced a series of technologies that we call the AI Data Engine that makes those data preparation and guardrails and enforcement much easier to do.
The second is AI engines typically repeatedly go back and do what's called a recursive kind of request for data so that it can improve its analytical outcomes. And so our higher performance systems like our AFX system, some of the cashing technologies that we have built to optimize the data pipeline, those become useful as the world moves to agentic. And there's a lot more innovation we are working on that we will tell you more as we bring that to market.
Our final question today comes from Asiya Merchant, Citi.
George, I don't know if you commented on this, and again, apologies if I joined in late. But just your opportunities to win business with some of the neoclouds, I mean, not necessarily the hyperscaler. And I know you have your first-party services on a lot of these hyperscale offerings. But how do you look at the sovereign or the neocloud opportunity? And was there any traction there that you're seeing? Just any color you could provide on that sort of customer segment would be great.
Yes. I think that once we introduce the AFX solutions, we are seeing growing interest in the neoclouds. As we said, we had a win in a large Asian neocloud this quarter with the AFX in its first quarter of availability. We are working with other neoclouds to provide a differentiated value proposition that includes the rich suite of cloud-ready data services like multi-tenancy, like integrated security, all of the things that we have proven in the hyperscalers, which now these neoclouds want in their environment. Of course, performance, scale, all of those capabilities.
And then hybrid use cases where as they move their business towards addressing enterprise AI, our incumbency and our ability to bridge on-prem to neocloud is quite differentiated. And so we'll tell you more about it over the next few quarters. We recognize that, that's a large segment that we can pursue and we're making a focused effort to go after it. It's early, but we'll tell you more, and we are encouraged by what we see.
Thank you, Asfiya. I'll now hand it over to George for some final comments.
Thanks, Kris. Thank you for joining us today. Our strong execution and operational discipline enabled us to deliver another outstanding quarter. Our unified data platform delivers exceptional value and operational efficiencies, solidifying our position as the intelligent data backbone for the AI era. And our broad portfolio positions us well to navigate the current inflationary memory environment.
We are on track to deliver our strongest year yet. And looking ahead, I am confident that our visionary approach to a data-driven future will enable us to outpace market growth and capture additional share, driving significant value for our customers, partners and shareholders.
Thanks, everyone.
And once again, ladies and gentlemen, that does conclude today's conference. Thank you all for your participation. You may now disconnect.
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NetApp — Q3 2026 Earnings Call
NetApp — Q3 2026 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $1,71 Mrd (+4% YoY; +6% ex‑Spot‑Divestiture)
- Non‑GAAP EPS: $2,12 (bereinigtes Ergebnis je Aktie, +11% YoY; über dem oberen Guidance‑Band)
- Bruttomarge: 71,2% (+50 Basispunkte YoY)
- Operatives Ergebnis: $533M (operative Marge 31,1%)
- Cash & Kapital: Free Cashflow $271M; Kapitalrückführung $303M (Rückkauf $200M, Dividende $103M)
🎯 Was das Management sagt
- AI‑Plattform: NetApp positioniert sich als Datenbasis für KI—AFX (disaggregated storage) und AIDE (AI Data Engine) zeigen frühe Nachfrage; AFX erste Auslieferungen, AIDE GA in Q4.
- Cloud & Keystone: Keystone‑Umsatz +65% YoY; Public‑Cloud‑Services treiben Neukundengewinn und Verschiebung von Wettbewerbern.
- Inflationsmanagement: Reagiert mit Preiserhöhungen, Lieferanten‑Diversifizierung und dem Vorteil eines Hybrid‑Portfolios für preisempfindliche Workloads.
🔭 Ausblick & Guidance
- Q4‑Guidance: Umsatz $1,87 Mrd ±$75M (Midpoint +8% YoY); Bruttomarge 69,5–70,5%; operative Marge 30,5–31,5%; EPS $2,21–$2,31.
- FY‑2026: Umsatz $6,772–6,922 Mrd (Midpoint $6,847 Mrd, +4% YoY); Bruttomarge 70,7–71,7%; operative Marge 29,3–30,3%; EPS $7,92–$8,02.
- Risiken: Hauptrisiko bleibt volatile Speicherpreise (NAND/DRAM) und damit verbundene Supply‑Dynamik.
❓ Fragen der Analysten
- Preisdruck & Marge: Viele Nachfragen zu NAND/DRAM‑Preiserhöhungen und wie viel weitergereicht werden kann; Management beschreibt Preiserhöhungen und Lieferantenverhandlungen, gab aber keine quantitativen Langfrist‑Commitments für FY27.
- Supply & Lead‑Times: Analysten forderten Details zu Kaufverpflichtungen; NetApp meldet aktuell keine Engpässe, arbeitet mit mehreren Lieferanten und prebuys, vermeidet jedoch detaillierte FY27‑Aussagen.
- AI‑Ramp: Nachfrage zu AFX/AIDE‑Rampen und Margenprofilen; Management bestätigt frühe Dynamik (≈300 AI‑Deals), verweigert konkrete 2027‑Prognosen.
⚡ Bottom Line
- Fazit: NetApp lieferte ein guidance‑übertreffendes Quartal mit Rekord‑EBIT und hohem Cashflow. Treiber sind AFX/AIDE, Keystone und Public‑Cloud‑Services; kurzfristig positiv durch Profitabilität und Kapitalrückführung. Mittelfristiger Wert hängt von Speicherpreis‑Entwicklung und dem Tempo des AFX/AIDE‑Ramps ab.
NetApp — Barclays 23rd Annual Global Technology Conference
1. Question Answer
Hi, everybody, thank you for joining Tim Long, IT hardware, com equipment at Barclays, very happy to have with him here from NetApp, CFO, relatively new CFO. But oddly enough, I did a fireside chat with this fine gentleman at their headquarters a few weeks ago. So we get to turn the tables a little bit here.
So maybe I think you got to read a little disclosure, and then we'll start.
Yes. Just make sure I read the safe harbor. So today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in NetApp's most recent 10-K and then 10-Q filed with the SEC and available on our website at netapp.com.
NetApp disclaims any obligation to update information in any forward-looking statement for any reason. Thank you.
Okay. Thank you. I appreciate the time. I know it's pretty crazy times for everybody. So got a few kind of hot topics here, but maybe we'll start off. You're still relatively new to the CFO seat at NetApp. And so maybe talk a little bit about kind of your first year and maybe the priorities that you're focused on, and then we'll get into some of the parts of the business.
That's great. First, thank you so much, Tim, for having me, and happy to be here. So yes, first year at NetApp, very excited. It's a great company with great technology and great future. The key priorities are no surprise focusing on revenue growth as well as profitability expansion. So basically, from top line to the bottom line, focusing on various elements, including our investment on the portfolio side, making sure that we're investing in growth opportunities with high ROI, all of our project from an R&D perspective and also looking at the go-to-market space, selling and marketing and making sure that we're investing our resources where we have the highest return on investment from a revenue generation perspective.
On the -- and obviously, with the focus on growth and profitability, the fallout of that is continuing to improve on free cash flow generation. The company has had a great record of being very disciplined in investment were very disciplined in where the OpEx goes and also very disciplined in cash generation. And so my goal is to improve on that as well as continuing to focus our capital allocation like we've done in the past on continuing to invest in the business as well as returning capital to our shareholders.
As you know, this year, we're returning up to actually over the last few years, including this year. We're returning up to 100% of our free cash flow to our shareholders through dividends and buybacks. Happy to be here.
Great. Great. Let's get into sort of topics that we obviously get a lot of questions on, and we got to start with the product gross margin. Really great performance last quarter. You got the question a million times rising and environment. How do you deal with it? So maybe walk us through how you see the moving parts around product gross margin. I think it was a very big surprise, most in the hardware world, had pretty nice surprises. We can never tell with pricing or what's in inventory.
So just give us your view of how to frame the outlook for product gross margins, particularly in the light of at some point, you're going to be facing more directly the increased NAND costs?
Yes. So we ended our Q2 with the product gross margin of 59.5%, which was a nice sequential improvement relative to the first quarter of the year. A lot of it was driven by improved cost, our cost structure. We did have -- we did lock in some good pricing on NAND for this fiscal year. And so for the remaining couple of quarters for fiscal '26, we expect product gross margin to be more or less stable. And the way we sort of think of it in the future is, obviously, if commodity prices are higher and we see headwinds on the product gross margin line in the storage industry, we would pass increased prices or commodity prices as price increases to our customers. Just like also in a deflationary environment, we also pass the benefits in terms of price adjustments to our customers.
It's a good -- I mean I tend to think of this as if the prices are up for the key components, you're raising pricing. Most customers are probably buying on a dollar basis. So maybe they wind up buying less bits. But from a financial standpoint, it could be similar revenues and gross margin percent. Is that a good way to think of it?
I think that's a reasonable way to think of it. Our customers tend to plan and budget on a dollar basis. And so let's say they have budgets of x millions or x dollars, then they would basically come to us with what problems they're trying to solve when we work rather to find the best solution for them in terms of what type of kit or what type of hardware/software we basically are offering.
And then in the years where NAND prices are higher, they may get a little bit less of a footprint. In the years where NAND prices are lower, they may get more of a footprint. So that's a reasonable way of looking at it.
Okay. Yes. And in past cycles, I know you weren't there, but I'm sure you've looked at it, just talk a little bit about how the company has managed through the changing commodity environments?
Yes. And look, we have a very experienced team on the supply management side as well as, obviously, on the leadership side. And in past cycles, we've managed through it really well. In fact, during those periods, also we saw increased EPS. And so we're -- we have processes, and we're very focused on that, as you would expect.
The way to think of this whole situation though, if I sort of want to step back and look at our financial statement or our P&L, we also focus on gross margin. I mean our gross margins are very healthy last quarter. We delivered a gross margin of 72.6%, which is really healthy when you look at the competitive landscape. We focus on gross margin, but we also focus on gross profit dollars. This is a key leverage for the sort of leverage points for the P&L. And so if I sort of want to look at that line and dissect how the various components of the gross margin line, we talked about the [indiscernible] product gross margin but there's a few other things that are happening within that line as well. One of them, if I want to think -- if I want to sort of stay in the hybrid cloud segment, one of them is our Keystone business, which is smaller but growing at a very healthy pace. In the first half of fiscal '26, the business grew approximately 8%. This also -- it has an accretive effect on the professional services margin. Within that same business we have -- sorry, same segment. We also have our support revenue that attracts 92-plus percent margin and very healthy.
And then when you look at the rest of the components, our Public Cloud business, Public Cloud segment, that has been growing at a really healthy pace. Last quarter, if we adjust for the divestiture of spot, that segment grew around 18% and delivered 83% gross margin. And so we're also targeting in that segment, 80% to 85%. So we're sort of towards the middle of that range. But the point is that segment is growing. And so from a portfolio perspective, we have high growth and high margin components of the revenue as well. And so the mix is favorable for us going forward relative to gross margin.
Okay. Great. Great. Yes, I did want to transition to Public, it's good you brought that up. You mentioned the 18% growth ex spot. Optically, it's still going to be overall challenged on the growth rate until you anniversary the divestiture spot. But how are you thinking about the growth of that business on an organic basis? Obviously, the first-party storage is very strong. So maybe give us your sense of how well that piece of the business is growing? And what will that growth rate kind of like once spot is fully gone.
Yes, of course. So yes, so by the first quarter of 2017 would be probably the first quarter where sort of year-on-year totally clean because we still have the tail end of spot in the fourth quarter of -- that was in the fourth quarter of fiscal '25.
And so when you look at the businesses, as I said, the Public Cloud segment ex Spot grew at around 18% last quarter. Within that, the first party and marketplace, the business the portion of the business you mentioned, grew at around 32%. So it's growing at a fast pace. This is really the growth engine of the Public Cloud segment.
And it's growing really for a couple of reasons. One, we continue to see healthy growth, just basically driven by the growth rate of the cloud. In addition, we continue to enhance the capabilities and the offering. And so we have -- we continue to add features into our Public Cloud across the 3 hyperscalers basically are with Microsoft, Amazon and Google.
When we -- when the business first started, it was very much in a narrower swim lane focused on Public Cloud environment. And now we're beyond that. We're also -- there's also exposure into the sovereign cloud and distributed cloud. And so there's more with the more features and capabilities. We're able to sort of expand the presence in the offering.
Most recently, we brought block to our offering at Google in addition to the Amazon -- our offering at Amazon. And so we continue to make improvements. In fact, we also a couple of weeks ago, there were some announcements around integration with AWS AI on the Amazon Public Cloud service basically our native solution there. And so we continue to expand the capabilities. And the business is, as I said, we're targeting 80% to 85% gross margin in that segment. Last quarter, we were at 83%, and there's no reason for it to improve from there.
Okay. That's helpful. Yes, basically 10% of revenues now. So it's pretty differentiated from competitive storage companies or peer groups. So are you -- you guys have a very big lead in this cloud-based storage as a service. Are you starting are you expecting to see some of the more traditional on-prem peers trying to develop this type of business model? Or is it they're so far behind, it's going to be difficult for them to replicate the success you've had?
Look, at the end of the day, we're focused on our capabilities and our offering. And we haven't -- so far, we haven't seen similar offerings in the marketplace. We have quite a bit of differentiation also in the offering because it's sort of -- it's all based on ONTAP, where you can also for customers who use ONTAP, hybrid cloud and public cloud, they have the capabilities to sort of move also similarly between the two. And so there's quite a bit of differentiation in that service.
Okay. And I believe there's a pretty healthy mix of new to NetApp as well in the public cloud. So talk about how you get those wins. I mean it helps to be cross-selling and have the hyperscaler sales force selling the solution on their own. So is that the main driver of the non-NetApp on-prem piece of that business?
This is a great point. So yes, I mean, it is a different another route to market for us. And if you think of it as sort of our go-to-market routes, that's another route to market for us. And it does also attract new customers to NetApp especially if you think of the customers that we typically don't reach with our on-prem business. Smaller- to medium-sized businesses, for instance, that don't typically fall within the large enterprise target audience for our on-prem business. Those tend to be, obviously, new adds to NetApp. And it's as they grow, obviously, they could also expand into cross-selling into the on-prem business as well. So all in all, it's a great segment for us, and it's seen a great growth.
Okay. Great. Maybe if we go over to the tech conference to talk AI. So in the context of NetApp and storage, obviously, it's been -- a lot of the AI has been large language models on big cloud. So there hasn't been a lot of storage arrays being sold. But you talked about a lot of data lake modernization. So a lot of customer accounts really growing. So maybe walk us through how you think AI more on the enterprise side is going to benefit NetApp.
NetApp? Yes, of course. And so as we see AI moving from training to sort of training large language models to inferencing, we think this will also create opportunity for data storage or data storage modernization on the enterprise side. And so we talked about having 200 wins last quarter, which if we compare it to the same quarter in the prior year, it's almost double the number of wins. It's just we continue to see good momentum in terms of activity and wins in that space.
We view these -- when we look at these wins, we categorize them into 3 categories. One is data prep. This is where enterprises are getting ready to implement -- for AI workloads, things like data lake modernization and data infrastructure modernization, that enables them to have sort of a unified view of the data. And so that's one category.
The second one is training and fine-tuning of large language models, either they're training their own model or fine-tuning sort of a pretrained model to optimize it for their own data. And then the last category is inferencing. So you can think of inferencing or RAC type of applications. And so the if we look at those sort of 200 wins, they're roughly around 45% of them was in the data prep type of category, around 25% in the training type of category and around 35% in the inferencing side.
Now we think the last category, which is the inferencing is what drives really the data infrastructure and sort of data sort of our part of the market. as it grows. If AI were to be successful, obviously, more and more inferencing will be adopted by enterprises and that, in our mind, would create a nice tailwind and sort of growth engine for the data infrastructure.
Okay. Investors like to see a revenue number, percentage, whatever. Do you envision these different AI use cases that NetApp has involved in a year or 2 from now translating into you having the ability to say x percentage of our business is now driven by AI? Or will it be too difficult to parse out with kind of the core business?
Well, this is the goal, Tim. We I mean, we'll as it becomes a more sizable portion of our revenue, then we should be able to be to quantify it and talk about it more in terms of the dollar incentive.
Okay. And would there be any margin differentiation or difference with these type of more advanced use cases relative to kind of the traditional storage business?
It's probably too early to tell. I mean for me now, I would say probably not necessarily. Now if there's a certain element of data, let's say, services or software, bigger software element then there could be some. But for now, I'm assuming that it's sort of in line with the content.
Okay. Okay. maybe back to you gave a forecast of, I think, 3% or so growth for next year at the midpoint. Talk a little bit about kind of the moving parts when you think of the businesses. Obviously, we're going to have very good growth on the cloud ARR piece. What's kind of underpinning the rest of that growth dynamic into fiscal '26?
Yes. So there's I would say a couple of things. In addition to the cloud continuing to grow at a healthy rate. I mean, we talked about the 80% ex Spot. So expect it to be in the sort of the high teens range. We expect, obviously, continuing growth in all-flash for the remaining part of the year. In fact, we're forecasting the second half of the year to be growing to be accelerating relative to the first half of the year. I think ex Spot, we're projecting around 5% or so growth for the second half of the year.
Within that, there's also when we look at the U.S. public sector, we did see some weakness we also see a subseasonal growth in Q3. But we think by the time we get into Q4, we would be getting back to normalcy. Obviously, this is this was a short-term effect from the shutdown, and we don't expect it to have a long-term effect on the business. And so when you put all this together, that gives us sort of -- we're close to that sort of 3%.
Okay. And you mentioned all-flash array. It's been a pretty good move for NetApp. Obviously, it tends to be a little bit better margin maybe 2 years ago or so, 2 or 3 years ago, really more aggressive with QLC NAND. So maybe talk a little bit about what you see the all-flash mix doing? And a little bit more exposure to QLC, maybe for some secondary workloads. What is that doing to kind of market share and ability to enjoy better margins, maybe at not the highest end of the market, but that mid-tier of the market?
Yes. So what -- if you look at our market share development over the last couple of years, we did gain share in all-flash. And part of that is some of the dynamics you mentioned, obviously, part of that is also all-flash portfolio and our ability to compete very effectively of course, ONTAP is a big element of that. And so when I look at these dynamics going forward, those are the same type of dynamics that should allow us to continue to sort of see more traction and potentially gain share in the space.
As of last quarter, we had around 2/3 of our Hybrid Cloud segment very much on -- in all-flash. And so that continues to grow as a percent of [indiscernible]
Okay. And it's still a pretty small percentage of the installed base that's on it. So how does that translate to upgrades and as you're looking out the next few years?
Yes. If you think of the installed base, we're around 46% of the installed base sort of refreshed from hard drive. And so if you think -- the way we've seen it develop and the way we think of it also going forward, we think that should continue to increase approximately 1 percentage point a quarter. So to get to that sort of 60%, let's say, it's going to take us a few years. We still have a few years of growth ahead of us. And those, obviously, as you said, our all-flash array business tends to attract a little bit better margin. So that also, in a way, provides us sort of a tail to the margin for the future.
Okay. And when you're looking at kind of just the overall mix of the business, obviously, the Public Cloud is going to be faster growth. Keystone is smaller, but very high growth in the maintenance services business, pretty stable growth. So is this a dynamic where the recurring revenue percentage as well, given some of those pieces underneath will continue to take higher for the company?
That's exactly how this works. I mean, you described it much better than I would, Tim, but that's exactly.
Okay. You mentioned public sector. You do have a fair amount of exposure there. So I guess the next water still a little subseasonal. So that's just some conservatism around when we'll start to get approvals flowing and that type of thing. But outside of that, there's a lot of focus from the federal vertical. It seems to modernize. So do you think once we get out of this post-shutdown mode will see that segment of the business in a much better growth algorithm heading [indiscernible]
Yes. So as I said earlier, what we've seen in Q2 and what we're seeing in Q3 is temporary. This is all sort of a result of the shutdown. We don't see a long-term effect on the business. And so to the extent that IT spending from the government side sort of increases in the future, we would be beneficiaries of that, and we should see that materialize.
Okay. And one of the areas, other verticals that was a little bit more challenging. was EMEA, a lot of macro situations over there. It seems like it was a little better last quarter. Where are we in the cycle for the Europe business?
So the nice thing about EMEA is we talked about it being sort of down in Q1. But in Q2, it came back nicely. I mean what we see is in Q2 is places like U.K. and Germany did well. It has a lot to do with GDP growth and how the GDP sort of the -- yes, GDP growth develops in various countries.
We do have really a strong presence in EMEA. Our team did really great in the second quarter. And so we expect to continue to do well there.
Okay. Maybe just going back to the Public Cloud business. I think there was a period, maybe it was spot, but there was some elements of the business that were just far too lumpy and not predictable. When that's anniversaried and you got more of this first-party end marketplace storage, do you envision other offerings and other technologies? I mean you're getting block in, you're doing kind of some of the blocking and tackling and getting all the relevant offerings into the big 3? Do you envision either M&A or other solutions that NetApp can offer to leverage the pretty big installed base you have with those customers?
Look, from an M&A perspective, we're a technology company, and we'll continue to look at options for value-enhancing tuck-ins that would be basically good, nice complementary for our product portfolio. At the end of the day, we want to make sure we have the most competitive product portfolio that allows us to continue to drive the growth of the business, the profitability and value creation.
Okay. And then just back to Keystone, you mentioned the 80% growth, very impressive off a smaller base. Are you seeing customers wanting that type of consumption model? Is it a push model still? Is it a pull model? How do you see that happening? And how is the sales force at adding on this could be challenging if I'm selling an array for $100 compared to a Keystone for $30 over 3 years in a row, 4 years in a row. How do you manage that transition? And will that limit revenue growth a little bit until you get it up to more scale?
Yes. Well, look, we typically go we're very customer-centric. We typically go wherever our customers want to go. We would we're always happy to propose to our customers the best in that suits their needs. And so in the event where Keystone is that we're happy to work with them there. And if it's not, then obviously, in on-prem sort of CapEx solution would work. That's sort of one view.
In addition, I would say it also depends on the customers. Some customers who aren't as sort of -- who are more sort of focused on this preferred subscription model or a consumption model would go for a Keystone agreement.
From a NetApp perspective and from a sales team perspective, the team is compensated either way. So there's no sort of incentive one way or the other, the team is incentivized to sell all of our services and provide the best service to our customers.
Okay. Maybe one last quick one. Would you say because others are trying for that on-prem business to turn into as a service business, everyone wants less hardware and more recurring. The strong position you have with the hyperscalers and how mature that model is, how does that translate to helping Keystone be differentiated from what a Dell or an HP or others want to do?
I mean the Public Cloud business is and as a service business, right? And it's nice. It's all consumption based. Some of it is subscription. And so it's a nice complementary service business to the Keystone business. So if you think of, let's say, if I go back to some of the comments I made earlier about some smaller-sized customers who are not necessarily very large enterprises, who would prefer to sort of get exposed to NetApp through the Public Cloud business, they could also be good customers or good sort of target customers for our Keystone service. So that's also the very -- these 2 businesses are very complementary.
Okay. Great. Great. I think we're run up on time. Thanks for, I think, being the last presentation of the day, I believe. So really appreciate coming out. Thanks, everyone, for listening, and thanks a lot.
Thank you so much, Tim. Happy to be here.
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NetApp — Barclays 23rd Annual Global Technology Conference
🎯 Kernbotschaft
- Priorität: CFO Wissam Jabre betont Wachstum und Profitabilitätsausbau gleichzeitig – Topline-Expansion, Margenverbesserung und Free Cash Flow (FCF) stehen gleichrangig.
- Kapitalrückgabe: NetApp will historischen Kurs fortsetzen und bis zu 100% des FCF an Aktionäre zurückführen (Dividenden + Buybacks).
- Portfolio-Drive: Public Cloud- und All‑Flash‑Wachstum sowie AI‑Use‑Cases sind die kurzfristig wichtigsten Hebel.
💡 Strategische Highlights
- Margenfokus: Produkt-GM in Q2 bei 59,5%; Gesamt-GM 72,6% – Management erwartet für FY26 weitgehend stabile Produktmargen dank abgesicherter NAND‑Preise und Preispass‑Through.
- Public Cloud: Segment ex‑Spot +18% y/y; First‑party/Marketplace ≈+32%; Segment‑GM ~83% (Ziel 80–85%); macht rund 10% des Umsatzes aus.
- Keystone & All‑Flash: Keystone wächst (~8% H1 FY26), Hybrid‑Cloud zu ~2/3 All‑Flash; installierte Basis ~46% refreshed, ~+1 Punkten/Q erwartet.
🔭 Neue Informationen
- Operativ: Keine neue Finanz‑Guidance; Management nennt NAND‑Preisabsicherungen für FY26 und plant Preisanpassungen bei steigenden Commodity‑Kosten.
- Produkt: Erweiterte Public‑Cloud‑Funktionalität (Block bei Google, Integrationen mit AWS AI) als konkreter Ausbau der Cloud‑Offerte.
- AI‑Tracking: 200 AI‑Wins erwähnt; Management will AI‑Umsatz künftig quantifizierbar machen, derzeit aber noch keine Zahl.
❓ Fragen der Analysten
- Margen vs NAND: Kritische Nachfrage, wie nachhaltig hohe Produktmargen sind; Antwort: Preise können weitergegeben werden, kurzfristig stabil gehalten.
- Public Cloud‑Lumpiness: Rolle der Spot‑Divestiture und Zeitpunkt sauberer YoY‑Vergleiche; Management nennt schrittweise Bereinigung (anniversary) aber keine exakten Quartale außer Hinweis auf fortlaufende Remediation.
- AI‑Monetarisierung: Nachfrage nach Prozent‑Angaben der AI‑getriebenen Umsätze; Management will das künftig berichten, vermeidet jedoch konkrete Schätzungen jetzt.
⚡ Bottom Line
- Kurzkommentar: Call bestätigt einen defensiv‑wachstumsorientierten Kurs: stabile Margenpolitik, starke FCF‑Priorität und klar erkennbare Wachstumshebel (Public Cloud, All‑Flash, AI). Near‑term Risiken sind NAND‑Preise und temporäre Sektor‑Volatilität; für Aktionäre bedeutet das ein ausgewogenes Chance‑/Risikoprofil mit Fokus auf Cash‑Return.
NetApp — Raymond James TMT & Consumer Conference
1. Question Answer
Thanks a lot, folks. My name is Simon Leopold, Raymond James semiconductor and data infrastructure analyst. So we're here at our TMT+C Conference here in New York City, fireside chat. And we have from NetApp, Jeriel Ong, who is the Director of the Investor Relations team. So fireside chat format, but folks have questions in the audience. But Jeriel, before I start, do you want to do a safe harbor?
Yes. The safe harbor statement, team will kill me if I don't read this, I almost forgot. So today's discussion may include forward-looking statements regarding NetApp's future performance, which is subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. NetApp disclaims any obligation to update information in any forward-looking statement for any reason.
You're now safe.
Yes. I'm now safe.
Okay. Good. It's interesting. Only about 1/3 of my companies are reading safe harbor. I don't...
The rest of them are taking the risks.
Yes. Do whatever you want, whatever makes you happy, we're good. We're accommodating.
So I'd like to sort of start off in order to maybe set the groundwork for maybe you've got some investors who are interested, but new to the story. So how do you like to introduce NetApp to a prospective new investor?
Yes. So NetApp is a data infrastructure storage provider, right? We make your data valuable. We make the insights valuable. We deliver this variety of mediums as a service through our solution called Keystone in the public cloud on 3 major public cloud providers and then in a traditional kind of CapEx delivery way through our HDD and Hybrid Solutions as well as our all-flash solutions.
Great. And I want to sort of split it up. I definitely want to get to sort of the AI discussion, but I want to get to kind of the foundational aspect of the business, which is selling to enterprises. So I feel like we've gone through the last couple of years, post kind of the supply chain dynamics from the pandemic with worry about macro recessions, slowing enterprise. So what's your take on sort of core enterprise demand?
Yes. I would classify core enterprise demand as it's not amazing. It's not terrible. I think you can kind of see that in our most recent results. Our revenues, excluding the U.S. public sector business grew mid-single digits in the private Americas business, in APAC as well as EMEA. So that is -- if you look historically at NetApp, not the strongest revenue growth that NetApp has done in the last 5 years, personally not the weakest either, right? So it does feel like it's a tepid environment, but neither too strong or too weak.
And are you observing any sort of notable deviations either by geography or by vertical other than the federal? And one comes to my mind is historically, and I don't know the reason you guys have typically had very high exposure to Germany. What sort of ebbs and flows or differences are you seeing? Or is it really uniform across the globe?
Yes. We are a global company. About half of our business is based -- we have about 1/3 of our business is in EMEA, predominantly Europe and then probably somewhere in the mid-teens of our revenues are in Asia Pacific. So what Simon mentioned, we do have a pretty strong position in Europe. Germany is #1 market share geography as an example. There are other European countries where we're #1.
And in the Americas, we're solidly 2 or worse. Dell is by far the largest company in the United States in terms of share. Yes, but so in Europe, we are a little bit more macro exposed relative to Americas, where I think some of the company-specific performance can outstrip a broader macro environment. Yes, there are countries out there that are underperforming and overperforming. I think on the whole across these big geographical splits, there's nothing really to call out in terms of something that is overly one way or another.
I think the main call out to your point and to your original question is in that U.S. public sector business, which is down year-on-year in the most recent quarter that we reported and down year-to-date for the first 2 fiscal quarters of the year we had so far as well. And that's been driven by a bunch of cost cutting and cost control efforts that's happening at the U.S. federal government. The U.S. federal government is the majority of the U.S. public sector business. We have some state and local business in there as well, but it's probably about 3/4 of our U.S. public sector revenues, and that's really been -- has been what's been pressured.
And so the way I look at it is the business really, excluding this sector, grew mid-single digits, but our total revenues grew closer to 2% to 3%, and that's been really weighed down by this public sector dynamic.
So some of the other companies we follow selling into federal vertical have said, but our federal business is mostly DoD and DoD is not getting cut. And so we're going to be fine, don't worry about it. Others have said, well, if you're exposed to agencies like Department of Education, you're going to feel it. What's sort of maybe double-click the mix of your federal exposure?
Yes. So our U.S. public sector disclosure is any given quarter, anywhere from 10% to, let's say, 14% of revenues, depending on whether it's a heavier quarter or a lighter quarter. U.S. public sector is about 75% of that. So let's call it high single digits percentage of our total revenues. As I split down that high single digits, it is pretty split evenly into 3 categories. So there's like -- there's a military angle to that. That's probably about 1/3. There's FBI, CIA, DEA, those kind of agency, that's probably about another 1/3. And then the remaining 1/3 are what I would call civilian-based agencies.
I'm not sure I have any triple click to click down on what exactly of the federal government is being impacted between these 3 segments. But that kind of gives you a rough sense for the mix of our business and that federal segment as a whole is really what's holding down that -- our U.S. public sector revenues in terms of declines relative to state and local portion.
So I want to pivot the discussion to supply chain and memory chips. And maybe as a first step, educate maybe somebody who's new to the story, you've got different types of memory. There's DRAM, there's HBM and there's NAND. NAND presumably is the important one for you guys. But maybe give folks a little bit of education and let's talk about why this is important to you guys.
Yes. So we are an enterprise storage provider. And so what that means is people -- customers are buying our products because they have a certain workload that they want to store those bits on. I think that it's important to highlight that customers are buying our products not for direct access to bits. They're buying it because they value ONTAP as a software system on top of those bits, right? So I would argue if all you want is access to bits, any enterprise storage provider is actually a very expensive way to get access to those bits because we are a 70% gross margin company.
Customers -- so when customers are buying our products, DRAM is a very small portion of our bill of materials, call it, low single digits historically. And then SSDs are a growing portion of our bill of materials because we are increasingly -- the mix of our revenues are increasingly becoming all-flash revenues. So we still buy HDDs, we buy SSDs and SDCs are growing.
If I look at our COGS, which is about $2 billion annually in that range, not even anywhere close to the majority of this is related to these memory components. It's less than half related to, let's say, HDDs and SSDs. SSDs growing in the percentage of that mix. And so it is -- we spend a lot -- there's a lot of money in COGS and other things like other semiconductors, assembly, freight, EMS costs, warranty costs. There's a lot in there that is not related to commodities.
And I guess one of the challenges for the investment community is I think we're bombarded with headlines about spot prices on memory. And presumably, you don't buy much on the spot market. So how does the company manage the supply chain? And I'd say in your defense, gross margins were actually pretty good this quarter. People thought they were going to be terrible. What is sort of the operational aspect that allows you to sort of not pay these spot prices?
Yes. So we buy in volume. We're buying in much higher volumes. And so that's the first thing. When you have a volume, there is a discount relative to spot that you can get from that. But we're also opportunistic. So we don't buy on a steady cadence. So if we need, let's say, 1 terabyte in month 1, we don't just keep buying 1 terabyte every single month through the year. We buy it in spurts. And so yes, yes, we wait for -- we work with different providers effectively to achieve our needs.
We have a procurement team. They forecast -- they have -- they form their own view on the prices of these products and potentially which vendors to work with over the course of the year or 2. And yes, we remain kind of flexible to when we purchase products for commodities for our products.
And I guess talking to you guys and your peers, it sounds like basically, there is inflation, but there may be somewhat different strategies as to how you as a vendor go about raising price. So we're hearing about combinations of, well, we do less discounting. We're raising list price. What's sort of been NetApp's approach and philosophy managing the price hikes with your customers?
Yes. So what Simon is referring to is a little bit more complicated than perhaps just changing the price of an iPhone on the website, right? So we have a list price that is officially listed on our website or perhaps given to our channel partners. Typically, there's a discount rate that is applied to that. And so there's effective price that the customer experiences. And so different companies in the storage industry manage the effective price in different ways.
Some of them raise the list price and then have the same discount to rate and some companies reduce their discounting but have the same effective list price. But effectively, you're changing the actual customer experience price depending on your strategy. Our strategy is to try to manage both, right? I think that we raise our list prices if the commodity costs do increase, and we have in the past. In fact, we did it recently. And yes, then we try to manage up that effective price of the customer experiences through both efforts.
Now in the past, I think maybe the prior cycle might have been 2017, which might have been before you were over there. But the perception we've had is that sort of when the market share leader raises price, everybody just follows. Is that sort of been the dynamic in this cycle? Or is it somewhat different nowadays?
So number one, the cycle is yet to play out. So we'll see how this one plays out. Yes. I think that there is a little bit of a -- let's wait to see if we are in line with everybody else type dynamic with these price changes. I think what happens is, again, prices are typically on a decline. They kind of edge down over time because commodity costs are coming down over time, right? That's kind of what enables these storage systems to address more and more storage over time.
Yes, on the price raise, they tend to be a little bit more abrupt, I guess, or a little bit more of like a step function up. And so yes, there is a little bit of a, what is the industry doing dynamic. I think the reality is the market leader is smaller today than they were in 2017. So there's perhaps a little bit of like a let's wait to see what one company does dynamic in the industry. Yes, but we'll see how the cycle plays out.
Just to make sure I understand, your guidance, the forecast you've given the Street for this year suggests that your margins should hold in and/or improve through the year. You're not expecting further degradation. Is that accurate?
Yes. I think if you look at our fiscal 2026 guidance and what we've done this year, it certainly implies that gross margins kind of maintain in a similar range. And depending on your assumptions, we don't guide specifically to the product gross margin line. It could be in the range or maybe slightly lower, but not materially lower than the 59.5% that we just reported.
So I want to pivot to sort of the AI topic because that's sort of what's exciting these days. And I think it's interesting in that when we look at the IT space as a whole, compute is obviously sort of the center of the storm and storage has not readily participated. Now I feel like the narrative that we've been hearing from NetApp and peers sets it up to be a beneficiary. How do you envision sort of the storage angle of kind of the AI theme playing out?
Yes. I think that our thesis is that as the AI industry shifts its spending from training AI models to inference that storage has a bigger presence in that inference cycle in terms of, a, maybe contributing data that's been created in enterprise over -- sometimes decades to improving that AI model, but also as an AI model is used again and again to create outcomes, that data that is created needs to be stored. And that is the inference step that will generate more data for an enterprise storage provider than perhaps the training stage has so far.
So we still think that growth is still to come. Certainly, in the most recent quarter, we've already seen evidence of that. We talked about 200 design wins, AI design wins in the quarter, up from 100 a year ago. So that's evidence, it's happening, but that still feels like more sort of the tip of the iceberg in terms of future growth than it is we are right in the thick of that AI inference stage really taking off.
So what can you tell us about these 200 design wins? Are there common themes? Are they 200 completely different projects? What's sort of the nature of the customers and the applications?
Yes. There isn't really a geographical or, let's say, end customer mix that really heavily skews one way that I can call out. What I would say is that there's still a lot of data lake modernization wins in that number. And what data lake modernization is, it's kind of like -- it's an in-between step in AI where you have a broad data estate, perhaps it's extremely siloed across different vendors and you're aggregating that data into one data lake so you can improve your AI workloads.
So it's a copy effectively. It's a copy of your data. There's a lot of that still happening, which kind of indicates perhaps we're not as much in that inference stage strongly as we'd like to be. But I don't think that's specific to NetApp. I think that's more indicative of where the industry more broadly is at in this. And so yes, I think we hope that this AI inferencing -- these AI inferencing workloads continue to take off, and we really think NetApp will be a beneficiary once that -- as that kind of plays out.
And I think one of the logical and probably as yet unknown debates is when enterprises engage and use AI, where? So what's the mix that you would expect on public cloud, private cloud, on-prem and what makes a difference to NetApp?
That's a tough one to predict, if I'm being honest. I think that's where -- just because the inference stage isn't in its maturation stage, I think a lot of industry participants are just in their prediction stage. I would say one thing, one hat is in the ring why it makes more sense on-premise is that a lot of the data that will improve and augment and improve the quality of your AI outcomes is data that's from on-premise, number one. So that's the first point.
I think the second point is high-performance, low-latency workloads tend to be more on-premise, right? So if you look at the current spending in storage, if you have a lot of backup, a lot of recovery, a lot of low-touch stuff, you don't care if the cloud is down for an hour. It doesn't -- you don't really touch that workload very frequently. But if you have a workload that is essential to running your company on a daily basis, you want that to be a low failure rate, low latency, high-performance workload.
That's an all-flash workload, and that's an on-premise workload. So it feels like if an AI workload looks more like that, that there could be a higher chance it's on-premise, but we'll see how the market kind of plays out.
Yes. I have not made up my mind either, so I don't want to give you the impression that have some bias on that. I think it's probably the interesting debate. We'll get more clarity over the course of next year is my hope.
Yes. Yes. I think -- yes, we'll see what happens.
And then about a year ago, you guys announced a platform called the AFX, which I think inserted you more strongly into these AI discussions. Maybe help people understand what is it about the platform that was an evolution and what makes it more relevant to AI use cases?
Yes. So AFX was announced at INSIGHT. This happened in October of this year, so relatively recently. It's in the hands of some customers. So we'll see -- we'll get a better sense as we move through fiscal '26, what the traction on this is like. This product is fundamentally a little bit different than what NetApp has delivered in the past. So NetApp was founded in 1992. It was essentially a one product company, something called FAS. It was HDD-centric product, right? Eventually, we released something called A-Series. This is a high-performance all-flash product, NAND or SSD only.
And most recently, a few years ago, we released C-Series. The common -- which is also an all-flash product. The common theme through all these 3 products is that we are delivering our products in an integrated approach. So what that means is they get access to ONTAP, but the only way they get access to ONTAP is when they buy our storage arrays. It is a product. It's similar to -- if you buy an iPhone, if you want iOS, the only way you're going to get iOS is if you buy an iPhone, you cannot get iOS without an iPhone, right?
That's how the entire industry delivers storage technology to the -- to its customers. But really, AFX is disaggregated. It's AI focused. And the AI market has kind of increased the significance of disaggregated solutions. And so this new solution delivers our technology in a fundamentally different way for a different market. And so we will see the traction that this has. And I think that it's really where customers are wanting to consume ONTAP technology.
And so how does this contrast with the AFF, the A9000 -- or 900, A900.
Yes. So it contrasts in this kind of like integrated versus disaggregated approach, right, to the technology. But also the product that you're specifically describing is a very, very high-performance solution. So in terms of where exactly AFX stand in that stack is still kind of yet to be seen. We have a lot of options that consumers can offer there. But if it goes the way of all-flash solutions so far, I think AFX will probably be pretty high-end solution as well.
So you mentioned sort of well, you can't get iOS without the iPhone, but you guys have your PCS, your Public Cloud Services. So isn't that sort of a way to get ONTAP without necessarily...
Yes, Simon, so you make a good point here. So yes, we've had some experience already kind of disaggregating the technology. So when we first started selling ONTAP in the public cloud, we actually had to install our hardware on the public cloud itself. But as the business has matured, it's really shifted to more a software-only solution where the public cloud providers source and install their own hardware.
So in that sense, yes, it is kind of similar in that sense where we have offered our technology in a more disaggregated fashion. Our software -- our public cloud line is increasingly a lot more software only, so to speak. But yes, I think in terms of for that enterprise customer, it really has -- they really haven't had a disaggregated kind of solution to consume unless they go for the public cloud. So it's a little bit different from that respect.
And the way I've thought about it is -- and I won't be embarrassed if you correct me, is that this is the way that an enterprise customer can have the experience with ONTAP, but be in the public cloud. So they're using your software, your application, your interface, but it's public cloud economics, right?
Yes, I think that's fair. Yes, I think there's thousands of customers on our public cloud solution, big and small. I think on the small end, what's interesting is there are customers that really perhaps are large customers, but start off at really small workloads that maybe wouldn't have choose NetApp or NetApp wouldn't really have had a chance to address this customer in the first place. And then they become very big customers either through the growth in the company or the fact that it was just a testing environment that really worked really well, but then they're outgrowing pretty materially.
So we've seen a lot of good use case growth from this public cloud business. I think there's a sense out there that we're only -- it's kind of a little bit of left-hand, right-hand thing where they would have otherwise bought it on-prem, now they're buying on the cloud. Certainly, that doesn't feel like that's the case. Half of these customers are new to NetApp customers, never gotten a core product for our business ever until they were a public cloud customer.
And so it does feel like we're growing our customer base with this product. It's growing really well. The first-party marketplace revenue disclosure, which is about 3/4 of our public cloud revenues in the most recent quarter, grew in the low 30% range year-on-year. So this business is gaining a lot of traction. And yes, it continues to grow really well. It's a good business for the company.
And not arguing that point, I guess one of the things I've sort of struggled with is, well, why would the public cloud want to introduce competition to its own storage offering. So for them, what's the logic?
Yes. This is a good question. So ONTAP offers a set of features that is pretty fully featured, and it offers a different offering than what the public cloud has and has had already for coming on 2 decades now. So that's the main logic is that they have -- the public cloud -- each public cloud vendor has an incentive to offer as much on the public cloud relative to what the customer could choose on-premise, like at a high level, right?
And so NetApp offers that opportunity to move a workload that maybe would have been on-prem on to public cloud instead is really the single line. And really, within that category of fully featured products, ONTAP is, frankly, the best solution relative to the other core vendors that we compete with on-premise. And so every time a vendor chooses something in our category, so to speak, ONTAP is really winning in spades. And so that's why we feel really good about this business. I kind of acknowledge the risk kind of side of the question you're saying, which is that, well, if you're getting so big that perhaps you're bigger than the public cloud itself on the public cloud, like why wouldn't they just build a solution themselves? And -- we're just such a small insignificant revenue relative to their own solutions right now that it's really not even a question or a topic right now that really I think they're even thinking about.
I want to talk a little bit about the competitive dynamics, partly because one of your CEO from one of your competitors like he characterized as a knife fight in a phone booth. And that's just such a profound visual to characterize your market. Now it seems as if it's competitive, but it also seems as if everybody is doing pretty well right now in terms of not getting hurt by memory costs. So maybe it's not quite as brutal as that.
But how do you like to sort of think about or characterize the competitive landscape? It seems as if you guys have generally been a share gainer. What's enabled that?
Yes. We're generally a share gainer. So our share has been increasing according to IDC data. Roughly speaking, we're in the high teens in market share in the all-flash market at this point. At some point, if you kind of rewind it back a few years, we were probably in the low teens. So we've been gaining share and the market is consolidating. The top 7 vendors in all-flash have 90% of the market. I think what's enabling us is, yes, it's our operating system. It's our launch of our C-Series product a few years ago that enabled QLC NAND in all-flash enterprise workloads.
That was an expansion of the all-flash market. And I think in that expansion phase, I think there were certain vendors that did better and certain vendors did worse, and we happen to be one that did better in that transition. Yes. I think at a high level, yes, it is competitive. I wouldn't say it's -- scale 1 to 10, is it 10 out of 10 competitive? I mean I wouldn't say it's like crazy, crazy or crazy uncompetitive. It feels like we're still in that kind of middle ground where things are competitive. There's always -- especially for a new customer that is considering a new very large workload, yes, it's going to be competitive to win that. But yes, I like NetApp's odds in general. I think we've done well.
So I think one of the things we've observed really, I'd say, roughly in the last year is when we've done channel checks, it sounds to us that NetApp and Pure Storage are encountering each other more often than they used to. I felt like in the past, each of you had kind of a swim lane and you did your own thing, and it seems like you're competing more. And we're also getting questions from investors about, I'll say, noisier private companies, the WEKA's, the VAST, HAMR space. What do you see in terms of the smaller players and the newer players?
Yes. I think the smaller players and newer players have -- are more disaggregated versus integrated in terms of the solution delivery strategy. They have a lot -- a little more customer concentration, a little less features. But this is actually -- what I'm describing is actually very consistent with the history of storage start-ups, right? Like you can never start a solution from the ground up and have a fully featured set. You have to kind of pick and choose what features and what products you want to deliver. And then as you grow as a company, you expand that.
And so when a company choose -- when a customer chooses them, this is why the -- some of these companies are winning in the AI training space is because they don't need these fully fledged out features that the rest of the industry already provides. So that's what we kind of observed there is that they're winning AI training. We'll see what happens, who can make this leap to AI inference or perhaps more enterprise use cases. But ultimately, you have to win in enterprise if you want to become a fully fledged storage company because the vast majority of the spending is from an enterprise customer.
I think as it relates to Pure, I mean, yes, they've gotten big, right? And so are we. I mean I think our business is -- our all-flash business is in the $4 billion run rate size, and they're slightly smaller than that. And so as companies get big, you just kind of rub shoulders a lot more. I think this is also true for Dell or HPE. I think the market is more consolidated. The top 7 manufacturers in all-flash have 90% market share, like I said. But in the non-all-flash market, the top 7 have 55% share. So you just rub shoulders with a lot of different companies when you're talking about a hybrid or HDD estate versus the all-flash market.
Well, believe it or not, our time is pretty much flown by. I'd like to close with the following. What do you think is either the least appreciated or most misunderstood aspect of the NetApp story?
I would highlight like just how NetApp has changed over the years. Like I said, NetApp is founded in 1992. At that point, all-flash did not exist, right? It was an HDD-only market. And so we've built up an all-flash business that is now 2/3 of our revenues. The cloud business didn't exist 5 years ago in a material size. And now that's run rating at $600 million to $700 million, built largely from the ground up. And so I think I'd just highlight NetApp's ability to kind of continuing to drive innovation, continue to change itself as a company. A lot of companies in tech really have a hard time progressing beyond their first successful product, right?
Like that is really the history of technology, frankly. And NetApp has really done that twice, and we're kind of in this kind of reinvention stage, so to speak. And so yes, I think that will continue, and I think that's really the most underappreciated aspect of the company.
Well, great. Jeriel, thanks for joining us. Folks, thanks for joining us. This is our session with NetApp. Thanks a lot.
Thanks.
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NetApp — Raymond James TMT & Consumer Conference
🎯 Kernbotschaft
- Kurzfassung: NetApp positioniert sich als wachsender Daten‑Infrastruktur‑Anbieter mit ~2/3 All‑Flash‑Umsätzen, starkem Public‑Cloud‑Momentum (Run‑Rate $600–700M) und ersten AI‑Design‑Wins (200 im Quartal vs. 100 vor einem Jahr). Fokus: disaggregierte AI‑Plattform (AFX) und Margenstabilität trotz volatiler Memory‑Märkte.
🚀 Strategische Highlights
- Produkt: AFX als disaggregierte, AI‑fokussierte Plattform (Ankündigung im Oktober); erste Kundenlieferungen, Ziel: ONTAP‑Funktionalität in neuen Consumption‑Modellen.
- Cloud: Public‑Cloud‑Geschäft wächst stark (First‑party‑Marktplatz ≈+low‑30% YoY); viele Neukunden über Cloud; Run‑Rate $600–700M.
- Preis & Marge: Einkauf in Volumenschüben und opportunistische Beschaffung reduziert Spot‑Risiko; Listpreis‑Anpassungen wurden vorgenommen; Guidance impliziert Bruttomarge um ~59.5%.
🔭 Neue Informationen
- Update gegenüber Guidance: Keine formale Re‑Guidance, aber konkrete Farbe: AFX‑Rollout in Kundenhand, 200 AI‑Design‑Wins im Quartal (vs.100 p.a.), U.S. Public Sector macht 10–14% des Umsatzes (≈75% federal), COGS‑Volumen ~ $2 Mrd.
❓ Fragen der Analysten
- Nachfrage: Kern‑Enterprise Nachfrage als „tepid“ beschrieben; Umsätze ex‑U.S. Public Sector wuchsen mid‑single digits, Gesamtwachstum näher 2–3% belastet durch Federal‑Cuts.
- Supply‑Chain: Wie vermeidet NetApp Spot‑Schocks? Antwort: Volumen‑Einkauf, opportunistische Käufe, Procurement‑Forecasting; keine detaillierten Preis‑Breakdowns geliefert.
- AI‑Thema: 200 Design‑Wins, viele Data‑Lake‑Modernisierungen; Management vermeidet definitive Vorhersage zu Cloud vs. On‑Prem‑Mix für inference‑Workloads—Inference‑phase noch früh.
⚡ Bottom Line
- Bewertung: NetApp zeigt eine glaubhafte Transformation (All‑Flash, Cloud, AI‑Initiativen) mit stabiler Margen‑Guidance; kurzfristig dämpfen US‑Public‑Sector‑Cuts und noch‑frühe AI‑Inference‑Adoption das Wachstum. Für Anleger: langfristiges Upside‑Potential bei moderatem Near‑Term‑Risikoprofil.
NetApp — 53rd Annual Nasdaq Investor Conference
1. Question Answer
Awesome. So we're going to get started, not a lot of turnaround time here. So my name is Erik Woodring. I lead Morgan Stanley's U.S. IT hardware coverage. I'm pleased to be joined by George Kurian, CEO of NetApp.
Before we start, quickly, before we begin, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures.
And then from the NetApp side, today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in our most recent 10-K and 10-Q filed with the SEC and available on our website at www.netapp.com. We disclaim any obligation to update any information in addition to forward-looking statements for any reason.
So I'm, again, delighted to be joined this afternoon by George Kurian, CEO of NetApp. I think, George, maybe the best place to start. I know last week at a separate conference, you kind of discussed the October quarter pretty thoroughly.
Instead of doing a review, maybe just like what are two or three highlights that you want to leave the crowd with your key takeaways from the quarter or the January quarter guide -- full-year guide, everyone should kind of be aware of as kind of a starting point for our conversation?
Yes. I think, first of all, thanks for having me. Thank you for being here. In Q2, ex of our Spot business divestiture, we grew 4% year-on-year. We had continued strong momentum in our growth engines, first-party and cloud storage, which grew 32% year-on-year; all-flash, which grew 9% year-on-year, and we doubled the number of AI wins in the quarter. Product gross margins were above our expectations, driven by mix and continued prudent management of costs. Operating margins, gross profit margins and EPS were all records for the -- for Q2. And we have strong expectations going forward, where our business outside of U.S. public sector performed extremely well, showing our competitive position.
Okay. Perfect. And we'll kind of touch on a number of those points. I want to start just high level and really focus maybe first, like it's almost a little technical, but you and your peers all kind of had Analyst Days, product days over the last kind of 1.5 months. What we tend to hear is single pane of glass, we have the best software. ONTAP is world renowned.
And so I would love if you could maybe just help us understand where do you think NetApp is truly differentiated? And how do you leverage that differentiation to try and drive sustainable share gains?
Yes. I think we have pioneered many of the ideas that are coming to fruition in the customers. For many, many years, from the early 2000s, we have been believers in the idea that you want to unify your data across all your departmental boundaries, across all of your different data types so that you can actually have not only better management of your data, but the ability to extract insight. That is now de facto the norm that everybody in the industry is trying to get to.
The second, when cloud happened, we always believed that the world would be hybrid and multi-cloud. And so we built a hybrid multi-cloud architecture where our software is now deeply integrated into the major cloud providers, Amazon, Microsoft and Google; in a way that it's a decade-long journey that we have undertaken and are well ahead of anybody else in the market.
And then the third has been that in addition to having super high-performance scalable systems, which is sort of a basic requirement that many vendors can meet, we have a lot of data management value in terms of how people can exploit the value of data sitting in their systems.
This could mean advanced cybersecurity functions, the ease of management of data across hybrid cloud estates and increasingly a suite of tools that allow you to discover where your data is and to build super efficient pipelines so that you can take data from your enterprise applications and apply AI to it.
Okay. Perfect. So that's a good start. Let's kind of go higher level and turn to kind of the market opportunity. Can you just help us maybe understand two things. One is kind of how you think about the market growth of your end markets? And maybe you can separate cloud and on-prem stuff.
And then you've been clear that there is kind of a macro overhang on spending. Storage spend has lagged kind of server and compute spend. What needs to change to kind of get storage spend to kind of catch up to server a little bit?
I think broadly speaking, IT infrastructure spending is correlated to macro and within macro-specific business outlook. And we have not seen a major refresh of the infrastructure deployed in customers since 2018, 2019, the first Trump administration's favorable tax structure and cash repatriation period.
What that means is customers typically prioritize spending on infrastructure based on their application needs and their workload needs. And we are seeing a rotation of that workload mix into AI-specific applications, which we can talk about.
I think with regard to the compute cycle, it has been driven by AI. And I think what you see in the AI world is you have a lot of work to get ready for AI, all the model training, getting the models to a place where they can be applied to the data, that's what's been going on. And so we do not expect storage to uptick at the same pace and timing as compute.
Right. Okay. Before we turn to AI, I just want to quickly touch on U.S. public. And the question really is, at least what our view is, is that the government will always find a way to spend its own money. We just need to get kind of that engine moving again, get appropriations moving through the right agencies.
How do you think about government spending kind of coming back post the shutdown? And what are some of the signposts that we should be looking for as maybe like a precursor to that unlock?
Yes. I think we look at U.S. public sector as a combination of U.S. federal and U.S. state, local and higher education. For our business, U.S. public sector is low double-digit percentage of the total business, of which roughly 75% is U.S. Fed.
Within U.S. Fed, there are probably three or four things that we are part of and that we track. The first is multiyear appropriations. These are program spend vehicles. It could be defense programs, it could be infrastructure programs or national security programs. We are embedded in a lot of them, and they are immune from the annual appropriation cycle. And so our goal there is to capture more and more of those program dollars, and we have pursuit teams that have been successful doing that.
Then within the -- when an administration changes, usually the first year of an administration change, we watch for their spending priority shifts between, let's say, civilian and defense or any other kinds of budget shifts, and we move our resources to where the targets are. We saw some of those shifts within this administration as well. And that's part of the natural cycle of federal spending.
I think what we track now is the movement of appropriations to agency spending programs and the predictability of those spending programs and sort of translating from awards to actually orders, right?
And I think on the first one, in terms of appropriations being translated to spending, I think there's still work to be done. OBBB is still flowing down into the agencies and some of that was disrupted because of the shutdown.
And then the second, while there were some challenges, notably with DOGE earlier, in the year, those challenges have kind of abated. And so we are hopeful that by the spring time, the U.S. government is back in business. I think that we have been cautious about our Q3 because of just how long does it take for the government to come back. a normal course and speed.
Okay. Okay. Perfect. So that's kind of a good segue, get that out of the way. Turn to AI. Your point, George, kind of resonates when you talk about we didn't necessarily expect that to come right now.
Can you maybe help us understand what is the opportunity in AI? I think it's simplistic to say, well, there's just more data that will be generated, more data that will be stored. But is this something that you believe happens on-premise, but also you kind of have this hybrid model. So how do we think NetApp benefits from that? So kind of how does AI permeate the opportunity? And then what is kind of the hybrid opportunity for NetApp with AI?
Yes. We can capture value from data and data growth wherever it is because of our hybrid model. I think what we see is sort of three buckets of use cases within the enterprise, which is really our focus. You see sort of data prep and getting data ready for AI. You see people saying, "Hey, I want to take my models that are derivatives of big foundation models and kind of distill it or make it useful for my enterprise." And then you see people actually applying the two to actually run their business with AI, which is what is called inferencing or RAG.
I think for storage, data storage growth, the third bucket is the big bucket over time. And I think for enterprise productivity gains, it is also the big bucket, right? If inferencing is not useful for the enterprise, AI is more fluff than wave, right? And so that's what I think everybody in the industry is tracking.
We have seen the number of AI projects year-on-year double. So we said approximately 200 wins in the quarter. These are wins that have 45% of data lakes organizing my data to get ready for AI; 25% around training and fine-tuning, whether those are sovereign AI models or whether it's an enterprise model that's a distillation of a large foundation model; and 30% in inferencing.
And our view is for AI to be as successful as it is, the inferencing part needs to grow steadily.
Right. So maybe said differently, we're just early. And we might be seeing training happening in the cloud. We're at the early days of inferencing and kind of token growth.
What do you think catalyzes that kind of within the enterprise on-premise? Is it moving away from productivity gains to like creating new insights and business opportunities? Or can that kind of inflection on-prem still happen with just kind of the productivity approach to AI?
I think whether it's on-prem or cloud, the real value is the ability to get both unique insights as well as new ways of working that allow you to do more and bring more innovation, more growth faster.
I think in terms of new insights, we are seeing amazing examples in healthcare and life sciences, where there's everything from drug discovery to disease prediction to absolutely high-precision medicine to better -- much better diagnostic and therapeutic care. And so I think there, you are seeing transformative use cases now.
I think, with the others, there are several examples around ways to bring new capabilities to market, software development, for example, digital twins and immersive digital manufacturing. There is, of course, synthetic semiconductor designs where we are parts of lots of large customers' deployment models. But I think ultimately, for it to really change how businesses operate, it either needs to drive growth or really transform the way work gets done.
Can you maybe -- let's say it this way, I'd love to dig into those 200 wins, the 200 projects, AI projects that you talked about. Obviously, you just helped bucket them for us to understand kind of what you're doing within those.
Can you maybe give a few granular examples of like what I would call Keystone wins -- not the Keystone product, but flagship wins and exactly what the value add is that NetApp is doing underlying that project?
Yes. I think let's talk about data lakes, right? I think there are -- what a data lake is, is a customer says, "I want to bring data from multiple application landscapes into a single environment so that I can then organize my data and apply large language models into that controlled environment," we have really sophisticated tools for unifying unstructured data, structured data on-prem and cloud.
And so we have examples of -- in life sciences of customers that say, "I want to bring research data, clinical data, lab data all together across research teams in multiple geographies." We can do that in a way that nobody else can.
With regard to training, we have examples of large country-level language models where customers say, "Hey, I want to train this model, I want a trusted enterprise vendor. I've got good experience with NetApp technology. It's got the performance and scale and predictability in terms of resilience to support my environment."
And then in inferencing, listen, we hold an enormous amount of the world's unstructured data. And so when somebody else tries to start to talk about inferencing, they say, "Oh, let's copy all of the data into another environment to do inferencing." We said, "Just leave the data where it is, we'll help you do inferencing right where the data is."
And a lot of the innovations we announced at our customer conference was to just say, "Hey, keep your original data where it is, we'll allow you to create a derivative of it for inferencing in place with all of the security permissions, lineage track," which makes it much more -- a much lower bar for customers to adopt.
And I'd be remiss if I didn't kind of dig in with you or at least ask you about the all-flash transition because I believe today, 2/3 of your hybrid cloud business is already all-flash. You've obviously been able to benefit from this with growth and share gains.
Does that 2/3 go to 100? Or like how do we think about all-flash mix going forward over, call it, 1 to 3 years? And what does that do to your growth rate, do you suspect?
Yes. I think two things there. First is two data points. One is, as a percentage of hybrid cloud revenue, all-flash was 2/3. As a percentage of our installed base, it's 46%, and it's been ticking up roughly 1% a quarter, which is an indication of the size and scale of our installed base. And both numerator and denominator are growing in the second, right?
I think that flash will continue to grow as a percentage of the total out-of-the-factory shipments steadily over a period of time. Disk, with the data that we have, we don't see all-flash becoming 100% of the use cases. We see that there's a steady place for hard drive-based storage, especially for workloads that are either sequential workloads or workloads that just need a lot of capacity. I think -- so it will tick up as a percentage out of the factory.
I think in terms of the installed base, you can do the math. It's going to be many, many years of refreshes of hard drives based systems out of the installed base before we even reach 60%.
And I should have asked you this earlier, but your point on the installed base refresh last time being over half a decade ago, what do you think catalyzes that? Is it kind of a greater prevalence of AI? Or is there something else? Is it just the macro getting a little bit more certain to where CIOs can say, "I'm ready to partake in this type of refresh activity"? What is it do you think that catalyzes that refresh?
We are seeing workload-based refreshes going on right now. These are project-driven spend where someone says, "Hey, I've got this data set and this infrastructure, I want to bring it into my AI landscape. I probably need more modern systems." I was here yesterday, we were actually talking to a large financial services client about doing exactly that for fraud analysis and risk mitigation.
I think for a broad-based infrastructure refresh like we saw in 2018 and '19, where the customer said, "Listen, I want to modernize my entire estate," that's going to require a more constructive macro environment, and/or within specific customer circumstances, a more constructive outlook for their business, multi-quarter, multiyear outlook.
Okay. Okay. Perfect. If we kind of summarize all of this and take into account refresh opportunity, all-flash mix, early days of AI, you just -- I would love for you to take your fake magic ball and look out and just say like what do we think this should and/or could mean for NetApp when it comes to growth and margins and free cash? Obviously, we'll touch on Public Cloud in a little -- shortly. But just high level, what does all of this do for business fundamentals at NetApp?
Yes. I think our long-term model was mid- to upper single-digit growth on the top line. We should -- if you look at the year-on-year compares for the second half of the year, excluding the Spot business we divested, you're starting to be in that range -- at the bottom end of that range. And so we feel good about the acceleration of our business in the second half versus first half.
We hope that public sector becomes a more constructive environment next fiscal year. And so that's on the top line. Our goal is to drive mid- to high single-digit growth. We are -- we've got many secular drivers that allow us to participate in that.
Flash, cloud, AI, we're taking share in flash from our competitors, both structured and unstructured data workloads. Our cloud storage business, which is now the preponderant majority of our cloud business, is growing -- has been growing north of 30% year-on-year.
The mix of our business is shifting into higher quality business. Both margins are structurally much higher than they were in the prior model as well as the mix of kind of subscription and consumption-based offerings is higher. And so that's top line and margins.
I think, in terms of operating profile, listen, we've been disciplined operators of the business. Our last reported quarter was north of 31% operating margins and pretty disciplined allocators of capital, where a majority of our capital. Dividends is the first call on capital, and we've returned in the range of 100% of free cash flow to shareholders through dividends and buybacks over the last several years.
And you kind of touched on it, but I want to make sure we hit on the Public Cloud business. Two questions is, what do you believe -- so I think the business in totality grew 18% in the last quarter adjusted for the Spot divestiture. Like what is -- how sustainable is that growth? What is driving that? And then obviously, margins are very strong at 83%. Where do those go?
Yes. We said that -- let me get margins, and then we'll talk about growth.
I think we said that margins would be between 80% and 85%. We raised the range, and we are ticking along nicely as the mix of offering shifts more and more into software and as the depreciation from the original capital investment, particularly in Microsoft Azure, comes off the expense line. And so we see strong trajectory on margins.
Could it go over 85%? It could, right? We're not sort of saying that we will adjust the range upward. But is there something structural that prevents it from ticking upward? No.
I think with regard to what's driving growth is both the overall growth rate of cloud, which has been strong, but also the differentiation and the continued addition of new technology capabilities to our infrastructure.
So we started out with a narrower swim lane. We are now in a much, much bigger set of swim lanes and opportunities with clients and with the hyperscalers. We started out with their public cloud environments. We are now part of sovereign cloud, disconnected cloud, distributed cloud. So we are in a huge range of use cases of those hyperscalers.
We have done well in enterprise workloads where it's purely now scaling the go-to-market routes. And you have started to see us -- you will see us do a lot more with their AI workloads over the next 12 to 18 months. You should look at the Amazon re:Invent announcement that Matt Garman made about the integrations of our technologies with a huge range of AWS' AI apps, and there'll be much more to come. So stay tuned for the conferences in the coming year.
Okay. Cool, cool. We have a handful of minutes. I just want to quickly -- it took me whatever, 10, 11 questions before we hit on memory, but I'd be remiss if we didn't bring it up. Obviously, you know the backdrop better than we do.
Maybe the first question is, historically, actually in storage, you've been able to pass through these higher input costs. Is there anything that would not allow that to happen this time again? And again, the question is, how does that impact kind of demand elasticity as you're thinking about it in the environment today?
There's no reason why customers will not be asked to pick up higher input costs because we have passed that through to them in the past when it goes up, and we've passed the benefits of lower cost to them as well when it went down. With regard to elasticity, customers budget in dollars, and there historically has been very little elasticity positively or negatively due to input costs.
Right. Okay. So maybe before we end, I just kind of want to give you the dance floor because we've talked about a lot. We talked about the market, AI, share gains, technology, memory, cloud.
Just maybe what's the final message you'd leave for everyone if we think about where NetApp is in your journey, but also where you are from a stock perspective? Kind of what's the message that you want to send either what's underappreciated or where are you leaning into? And what's the opportunity for these guys that are sitting in the room with us?
I think, first of all, data is an ever-growing asset to the enterprise. Without data, there's no AI. And so especially unstructured data, which has historically had limited insight derived from it is becoming now a much bigger wellspring of value to clients. We hold a huge amount of the enterprises data in the world.
And we are now, because of our unique capability to do so across multiple cloud environments, very much seen as a data platform provider that can unify all of these estates. We are adding a lot more software functionality that allows us to differentiate in cloud, in cyber, in flash-based storage that gives us confidence that we should be able to grow above the market.
The growing parts of our business are an increasing share of the total, while the declining parts of our business are not only smaller parts of our total business, but also stabilizing in terms of the rate of decrease.
And then I think below that, listen, higher quality revenue, higher margin components of our business, good ability to manage sort of gross profit dollars, disciplined operators of the business, which should give us earnings leverage going forward.
Awesome. We are just out of time. George, thank you very much.
Thank you. Thank you, guys, for coming.
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NetApp — 53rd Annual Nasdaq Investor Conference
📊 Kernbotschaft
- Kurzfassung: NetApp positioniert sich als Datenplattform für Hybrid- und Multi‑Cloud und sieht AI als strukturellen Wachstumshebel. CEO betonte starke operative Margen und zunehmende Anteile von Flash, Cloud und Software.
- Quartalsfarbe: Q2 ex. Spot‑Verkauf +4% YoY; First‑party & Cloud‑Storage +32% YoY; All‑Flash +9% YoY; Produkt‑Bruttomargen über Erwartungen.
🎯 Strategische Highlights
- Differenzierung: Fokus auf Datenvereinheitlichung über ONTAP (NetApp‑Speicherbetriebssystem) und tiefe Integration in AWS, Azure, Google — Hybrid/Multi‑Cloud als Kernvorteil.
- AI‑Go‑To‑Market: ~200 AI‑Wins im Quartal, aufgeteilt in Data‑Lakes (~45%), Training/Fine‑tuning (~25%) und Inferencing (~30%). Betonung auf Inferencing „dort, wo die Daten liegen“.
- Flash‑Migration: 2/3 des Hybrid‑Cloud‑Umsatzes sind All‑Flash; Installed‑Base All‑Flash 46% und steigt ~1%/Quartal — vollständiger Wechsel wird Jahre dauern.
🔭 Neue Informationen
- Guidance‑Farbe: Keine formale Guidancerücknahme; Management bestätigt mittlere bis obere einstellige Langfrist‑Wachstumsrate und wiederholte Zielsetzung für bessere Mix‑ und Margenstruktur.
- Cloudkennzahlen: Public‑Cloud‑Geschäft adjustiert +18% YoY; Cloud‑Bruttomargen range 80–85% (Management nennt 83% als aktuelles Niveau; Potenzial, über 85% zu steigen).
❓ Fragen der Analysten
- Marktdynamik: Diskussion, warum Storage hinter Compute hängt; Management sieht AI‑getriebene Compute‑Vorläufe, Storage‑Refreshes folgen projektgetrieben und später breitflächig.
- US‑Public‑Sector: Anteil low‑double‑digit; 75% davon Fed. Analysten fragten nach Appropriations und Timing — Management war vorsichtig, erwartet Freisetzung von Mitteln bis Frühling, aber Unsicherheit bleibt.
- Input‑Kosten / Memory: Frage zur Weitergabe höherer BOM‑Kosten; Management sieht historisch geringe Nachfrageelasticität und erwartet Pass‑Through möglich.
⚡ Bottom Line
- Implikation: Call liefert operative Bestätigung der strategischen Story (Cloud, Flash, AI) und zeigt klare Margin‑Verbesserungen. Kurzfristig bleiben öffentliche Auftragsflüsse und makrobedingte Refreshes Risikofaktoren; mittelfristig stützt steigender Anteil höherwertiger, wiederkehrender Umsätze die Erwartung mittlerer bis hoher einstelliger Wachstumsraten und weitere Free‑Cash‑Flow‑Rückflüsse an Aktionäre.
NetApp — UBS Global Technology and AI Conference 2025
1. Question Answer
Great. Good afternoon, everyone. Thank you again for joining the UBS Tech Conference. I'm David Vogt. I'm one of the tech analysts here at UBS. And we're excited to have George Kurian from NetApp here, Chief Executive Officer. Before we kick off, Kris has a disclaimer she needs to read for all of us.
Very important information. Today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risks and uncertainty. Actual results may differ materially from statements made today for a variety of reasons as described in our most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. We disclaim any obligation to update information in any forward-looking statement for any reason. Back to you, David.
Thanks, Kris. Thanks again, George, for coming.
Thank you for having me. Thank you for coming.
So we just came off of earnings last week. So I think this is incredibly timely. What I thought we should do is maybe start with kind of just a quick overview of what you saw last quarter. Results were stronger, gross margin strong despite, I think, people's fear about commodity prices, other competitive issues. So maybe we can start there and talk about kind of what you saw in the quarter and how we're thinking about the January quarter and beyond through your fiscal year.
Yes. I think when we entered the quarter and guided the quarter, we said we were concerned about softness in EMEA driven by unsettled government structures in some of the larger countries, overall GDP outlook and then U.S. public sector. As part of the results on the top line, the European team, while GDP continues to be choppy, we have outexecuted really. We've done a super job in Europe.
I think you can see that in the market share data where not only are we #1 in many of those countries, we have opened up share gaps to our competitors quite nicely in some of the bigger markets. So at the halfway point in the year, Europe, we feel better and our outlook in the second half reflects that. U.S. public sector on conversely has performed materially worse than we expected going into the quarter.
The guide for the quarter was cautious, but it reflected the public data that U.S. government spending through the fiscal year was super back-end loaded. And so Q4 of the government calendar, which overlapped with our Q2 was expected to be a bulk spending quarter. And then with the shutdown, that kind of has pushed out. It cannot be pushed out forever, right? So it will come back. I think we are cautious about when it will come back. So Q3 is -- we're cautious about Q3. We're hopeful it's better than Q2, but still pretty cautious. I think with regard to the competitive landscape, listen, our flash business has performed well. Our cloud business continues to run unabated.
And our first-party cloud storage grew 32% year-on-year and gross margins are super strong in the cloud segment at 83%. I think if you look at hybrid cloud, the product gross margin beat was driven by mix better than we expected. The cost structure through our structured pricing agreements with NAND providers were part of our outlook.
Got it. So I want to come back to margin in a second. And maybe just touch on demand drivers for a second. So obviously, state and local was a little bit better, I think, U.S. federal worse. Is that a fair characterization?
I think overall, it's really tough, yes.
Really tough but to your point, you noted that these -- the money is there. People have to invest. So what is sort of the kind of mechanical process to really see that money start to flow into programs and projects that would benefit you? Is it just, "Hey, the person needs to be in the seat, the correct person needs to be in the right seat."
The assets have been sweat so long that they no longer can defer, delay, push out? Like is there anything that you can point to, to help us understand like how we should think about? Obviously, we don't think it's going to come this current quarter, as you pointed out, but as we move through the subsequent quarters next year?
Yes. I think we are speaking to every kind of connected party in Washington. And so far, the thinking is the springtime is when all of the pitchers and catchers get aligned so that you can get back to some degree of normalcy in spending. I think the 2 big buckets are the appropriations need to flow down to the agencies.
I think that's at various stages of kind of the receipts of appropriations being available to the agencies. And then within the agencies themselves, the right priorities in terms of what programs are they going to spend, what IT priorities are they going to spend on. I think both of those need to fall into place.
And does that business coming back, your all-flash business was very strong again. Prior quarter, it was strong ex U.S. federal public sector. Are they heavy consumers of flash at this point in the cycle? Or are they still sort of a mixed customer in terms of buying legacy drive systems? Or is it mostly an all-flash solution that they're looking for at this point?
They look like other customer segments. 2/3 of our business in hybrid cloud is flash. If you do the math on, if U.S. public sector were just flat, not up, right, you can see the acceleration it would have given to our all-flash business.
Got it. Outside of public sector, obviously, we've had reasonably good demand signals from other vendors. I think we had one earlier today, one of your competitors talked about their first-party IP starting to really accelerate. Do you think the market overall is healthy besides just what you're seeing?
Or are you taking material enough share that you're not seeing some of the -- well, let me rephrase that. You're not seeing some of the growth dynamics there. They're talking about acceleration, but they're growing far slower than you. So is that share driven? Is it product mix driven? How do you think about where you're positioned because you've taken a lot of share in the last couple of years?
Broad-based, I think that macro drives business outlook and IT spending. That's been the consistent theme. I think macro is still choppy. When we look at what that means is we have not had a broad-based storage infrastructure refresh since 2019, right? It's not like compute, which saw the new build-outs of GPU. Storage has been muted for a long time.
So what you see in that dynamic is 2 things. One is, hey, the projects that customers are spending on, those get storage spending as part of those projects. And then so you got to win your share of those projects and be in the swim lanes that have spending. And the second is you've got to take share. In the swim lanes that we are focused on that are seeing good traction, I think one is data prep and data infrastructure modernization for AI is showing good strength.
And our leadership in unstructured data gives us a strong entry point into that sales motion. The second is our technology leadership in building cyber resilience directly integrated at the storage layer, unlike our competitors that all rely on third-party applications is giving us the ability to go back and have conversations with our installed base and net new customers that says, hey, do you not want to have your production data sitting on a cyber resilience system. Cloud has been sort of immune from this. So our cloud business is really about completing more certifications for more workloads. That's on fire. It's been rolling for a good strong period of time. Those are the key...
Can I go back to the comment you made about compute seeing a little bit of a cycle recovery. If I look at compute historically pre-AI, storage and compute were generally attached at the hip, if you will. We haven't really seen that. Why do you think that's the case? And would that be additive to your outlook or your expectations, not just next year and the year beyond, if we do see a healthy recovery in traditional storage attached to traditional CPU-based server.
Yes. I think 2 things there. I think the compute build-out has primarily been GPU, right? And GPUs have been built for training LLM. That's been the majority of the investment in GPUs. The training use case, as we have consistently said, does not generate or need a lot of storage. It just uses storage like a memory buffer so that if the language model runs into trouble, it can recover its original position. We have solutions for part of that market, but it's not a giant market.
Right. But I guess maybe what I was trying to ask is we've seen some customers look for more power-efficient compute outside of GPUs. And -- but we haven't seen that translate into traditional storage demand.
I think storage is starting to tick up, right? So just following the earlier point, I think what we're seeing now as the AI market moves from the training part of the LLMs to actually the use of the LLMs to do business activity, you will see data infrastructure getting built out. We said that in the quarter, we had 200 AI wins.
These are GPU-connected storage landscapes. There's 3 types of them. One is a data prep environment, which is essentially where customers want to put all of their data so that the data science team can actually analyze it. The second is training and fine-tuning, this is where either you're training a large language model or you're taking a pretrained model and then optimizing it with your data or synthetic data.
And the third is, hey, inferencing broadly defined. It could be reinforcement learning, it could be RAG, it could be another form of inferencing. We said during the call that it's pretty similar. It's 45, 25, 30 in terms of the mix, 45% data prep, 25% training and 30% inferencing. So if you look at it, the storage build-outs are up from a year ago, and they are like the compute focused on the get ready for using AI part.
So when -- it's a good point. So when you think about -- in the past, I think you've said you want to bring AI to where the data is, not data to the AI, right? It's expensive. So in that framework, that 3-pronged framework that you laid out. So when we think about bringing -- fine-tuning models to the data, like where do you think we are in that cycle when you talk to enterprise customers?
And maybe can you talk to like where you are internally, like I would imagine that you have multiple projects and test cases and are exploring how it benefits NetApp. Like is this a calendar '26 kind of dynamic where we're going to see more use cases and customers really going out in that direction? Or is it more '27, '28 at this point where everything is still training-centric, and we're not really focused on fine-tuning these models and bringing it to where the data is on the enterprise side?
I think the number of kind of AI centers of excellence plus, hey, the number of AI projects has grown, right? You can say we said a year ago, it was 25, then 50, then 100, 150. Now we're at 200, right? So it's going up. So you're seeing more enterprises engage in the activity. With regard to the maturity of the use cases, listen, there's public data around it. We see the same thing.
So in healthcare and life sciences, there are truly transformative things happening, right? I mean, man, things that you never saw in the history of mankind, drug discovery, genomic analysis, large population studies, hybrid infrastructure use cases. I mean this is just unreal all the things that are going on. And just because the data was well organized, you are able to -- we are part of many of those because we can help bring together data sets across a diverse range of environments.
I think if you look in sort of from a horizontal use case, wherever there's software development, yes, that's ticking up. We have it. It's ticking up nicely within our own company. There are fairly standardized back-office use cases, hey, document analysis. It could be check analysis in retail banking. It could be contracts in procurement organization. It could be legal documents in law firms. It's kind of like the same thing. And then there's customer success where people that use our infrastructure, they want to correlate data from multiple parts of their customer success pipeline and do better chatbots...
Does that suggest a longer tail for legacy systems in storage as companies keep storage longer -- like keep data longer, so maybe asymptotically your hybrid system business, that's what, 1/3 of your storage solutions maybe stops declining effectively or the growth meaningfully moderates?
I'm just trying to think of like the longer-term ramifications for all of this incremental use case for data. We're going to create a lot of data. People will probably want to preserve [ said ] data for unknown potential incremental use cases. I mean is that -- should we think about the storage market then being sort of a healthier market over the long term, intermediate term than what we've seen over the last 5 to 10 years? Is that like a reasonable way to think about it?
If the data is seen as the way to get better value out of AI, which is a hypothesis that everybody seems to agree with, but you got to see that put into deployment at customers, that is true. We are seeing that evidence where people who historically, like I was with a large weather forecasting agency that collects an insane amount of satellite imagery and then analyzes it to provide better weather prediction, various kinds of storm analysis.
They used to archive a lot more data on to tape. Now they're keeping it on online storage. And it's for the reasons you mentioned, David. So it's early, but if that is the hypothesis that plays out, then yes, it should follow the trajectory that you had.
So we have to talk about margins. So storage historically has been a market where you've been able to increase prices to offset rising inputs, maybe albeit with a little bit of a lag issue. Do you think we're going to see that same type of cycle from customer behavior where you're going to be able to navigate maybe the higher NAND pricing, higher DRAM prices and other components by raising prices? I mean I think you talked about it on the last call where customers buy dollar amount of storage. I mean maybe can you kind of walk through how we should think about that?
Yes, customers budget in dollars, I think the way it works is IT as a whole gets a pool of funding from the CFO, they divide it up into projects. It could be, hey, I've got a cloud modernization project. I have a higher cyber risk management or, hey, I want to build data infrastructure for AI, right? And then within that, there are buckets for software, infrastructure and storage as a part of the infrastructure bucket. So that's kind of how it broadly gets laid out.
Typically, customers budget in dollars, right? They'll say, "Hey, I got $250,000 or $1 million for my data infrastructure." And what they will ask us to give them is the best solution for that use case. Sometimes it's a flash-based solution, sometimes it's a disk-based solution, sometimes it's the combo. And they might get more footprint out of that if it's a year where NAND or commodities are cheaper and less when the prices are higher.
With regard to our gross margin outlook, we run the business to drive corporate gross profit dollars. That's sort of the piece of the P&L that drives earnings leverage. When you look at the overall P&L, 4 buckets in there. There is support, which is a stable low growth but growing very high-margin business, 92% margins. Cloud enters next year at a much higher number than it started this year because both it has grown in revenue, but also margins are up at 83%.
Our Keystone business, which reports as part of the professional services line is growing. It's a smaller number, but growing at 80% in the first half of the year from a revenue year-on-year perspective. That pushes up the professional services margin line and then comes product gross margins. Within product gross margins, we manage that in multiple ways, right? One, the first thing we focus on is availability and access to innovation.
So we don't want to fall behind competition on either the latest types of silicon or assured access to supply. The second, because we -- and so we work with pretty much everybody in the market share charts. The second is we have structured pricing agreement with them. I think they appreciate the fact that both we are #1 in flash market share, but also we have been a stable -- we don't hockey stick our business up and down. We've been a stable buyer of theirs.
We have in the second half of this year, good line of sight to our kind of supply needs for the rest of the year. And we are in active discussions with them about what next year looks like, and we'll take the appropriate actions. In general, the storage industry is, as you said, David, we pass through higher prices when commodity prices go up, we pass through lower prices when it structurally adjusts downward.
And maybe just to go back to your point about customers have a fixed budget of dollars, and they may get more gigabytes in 1 year, less in the next year. Do customers trade down? So let's say, you were thinking about a higher end, more performative flash solution, maybe they trade down into a more modest cold storage-focused solution if it's adequate to meet that need? Or is it really the demand for that particular use case or workload supersedes that decision and they just buy less of said product for the same dollars?
There's no one consistent answer for most customer -- for all customers. Most customers say, "Hey, I got to serve this use case, give me what [ kit ] actually solves the use case." And then they might say, "Hey, I don't -- I'll just buy more next year, right, to offset the fact that they have less systems. Others might trade down. And so it just depends.
Depends. So the reason I ask is, so is there -- I know you don't break this out, but is there a margin differential across product lines based on performance within your portfolio. So very high-end flash performative, I would imagine, has more robust gross margin, more solution, more software versus maybe a lower-end solution. Is that a good way to frame it?
Yes, I mean, generally, the highest performance systems in any product family have the highest margins. And as you get lower, the capacity overruns the value of the software. And then the -- so margins get lower. I think in our portfolio, as we said, flash has higher margins than disk-based solutions. It's interesting. This quarter, actually, the mix shifted towards higher performance systems, which is what drove the -- so it's really hard to tell. Some clients might say, "Hey, I want to downshift, but it's a big market." You're serving thousands of clients a quarter. And so it's hard to -- for me to give you one answer.
Got it. Maybe on pivoting to public. Obviously, gross margins have been working their way higher, 83%, congratulations on the quarter. How do we think now that we're anniversarying Spot coming up, how do we think about the growth trajectory in those, I guess, discrete items within your public cloud, so first-party storage, et cetera, like is the holistic solution for public cloud kind of a mid-teens growth driver. And the reason why I'm asking is if I look at the profit dollar contribution from public cloud, it's kind of incrementally on par with your traditional business.
Correct.
And so if it's growing 2x, 3x your traditional business, obviously, then we're going to mix higher to mid-80s gross margin solutions. Is that a fair way to frame it?
Yes. I think, first of all, ex Spot, the cloud business performed at 18% for the quarter. The print was 2%, but that was because of the headwind from Spot. I think if you look at first-party cloud storage, which is the natively integrated storage, that is growing much faster. It's at 32% and is an increasingly large share. It's well more than the majority.
It is an increasingly large share of the cloud business. So both of them should provide for -- if we can sustain the performance of the first-party cloud business, which is the anchor tenant of our cloud strategy, which it should help drive the cloud numbers up because it's a bigger share. It's growing faster than the rest of cloud. And listen, from a margin perspective, we just gave the guide of 80% to 85%. So I feel like it would be inappropriate to come and reraise the guide.
No, no, of course. But mix-wise, it's [indiscernible] meaningful tailwind...
Correct, exactly right.
So what -- in this quarter, what was the strength in first -- was there anything you can call out in first-party storage? It was definitely stronger than we expected.
I think it was right on what we wanted to do. So we see good strength in the business. All of the hyperscalers now have mature offerings in first party. We are bringing -- we brought block to Google in addition to Amazon. So we have truly multiprotocol first party. And we've got a broader range of enterprise workloads that we are part of.
And we are bringing more price points, more packaging offers so that customers can buy through more vehicles from the other cloud providers. We also have work going on, and there's more to come to integrate into the migration motions of the cloud providers. So Amazon, for example, uses our tools to migrate enterprise workloads to the cloud so that you can go faster in terms of the ramp of those businesses. But we feel really, really good. Listen, there -- we're just imported on mode. It's just how do you scale a business that's growing fast. And then over the next 12 to 18 months, you'll see a lot more co-innovation around AI. We talked a little bit about it on the call.
Within public cloud.
Correct. Within public cloud around their AI motions. So we talked a little bit of it. I'll just tell you, watch the conferences coming up, reinvent, Pi Day, Google.Next. There was a little bit of that at Microsoft Insight. So there's just a lot more coming in that area.
Outside of the expansion of the relationship on AI with the public cloud parties, is there anything that you need? I mean you mentioned you added Block to your Google solution. Is there anything else that's sort of missing in the portfolio that you look at like we need this and then we have the portfolio or the complete portfolio that we want at this point?
I think on cloud storage, there's really nothing, right? It's just scaling go-to-market. I think when we look longer term, we want to build on our lead with cyber. I think we have been just like when we introduced deduplication on primary storage and everybody said, "Hey, that was on for secondary storage."
We now are -- we've got leadership, thought leadership, technology leadership. We want to expand that part of our capability. And then what we are seeing in AI is people want to do more of the AI work where the data is created rather than copy the data into another environment and do all the work and then recopy it back. And so there's more things we could do there. And so we look at that, building some of that organically. And if there are small tuck-ins to fill that out, we'll look at those opportunities...
I have to ask the final point with all of this tailwind potentially for public cloud, for traditional, for disk, for flash, you talked about margins on supply chain. How do you think about the prospects for incremental capacity coming online? I know you're close to all the memory vendors.
Like in your experience, does higher prices mean more supply effectively? What we always hear is the cure for higher prices is higher prices, right? So then supply comes online. But it doesn't feel like that's the case this cycle when you talk to participants in the supply chain responsible for that capacity.
Yes. I think it's dependent on who is the person suggesting there's more demand, right? I think there are people who do large volume purchases of infrastructure and then stop. And so it's very hard for a technology provider to them to kind of plan for their peak demand. On the other hand, we have been a very steady growing procurer of these memory technologies.
And so when we talk to them, they are like, "Hey, you guys see a higher uplift, okay." And we also are seeing -- because we use merchant silicon, we have been a good partner to many of these vendors to bring their new innovation to market. And so they do work with us on denser silicon, more cost-effective silicon, new types of use cases and so on. And so track record matters.
Got it. So we've been asking everyone today, what do you think the market is missing or a little bit unclear on with regards to your strategy going forward. We've had challenging U.S. Federal. I think everybody understands that. EMEA has been a little bit uneven to be fair but parts of your business are performing exceptionally well given the circumstances. So what do you think the market is missing about the storage industry, the NetApp sort of strategy going forward for the intermediate term, not next quarter, not the following quarter, but longer term?
Yes, I think the sentiment this year is clouded by the fact that we have on our prints, the headwind from the divestiture of Spot that masks some of the strength in the underlying business as well as the exposure to U.S. federal, which -- and U.S. public sector, which should correct itself, right? It's not a permanent structural reduction in a part of the customer segment. I think that masks the underlying strength of our franchise, which is we are growing share in the all-flash market.
We have cloud growing strongly and the declining parts of our business are both smaller and the pace of reductions are less over time. We are a software business. You can see that in the cloud gross margins, you can see that in the overall margin profile of our business. And so gross margins as well as the quality of revenue in addition to the fact that, hey, these headwinds should ameliorate and the core franchises are strong, the quality of revenue in those franchises is very good.
And then I think we have been disciplined operators in terms of operating expense, which says that the incremental dollar of revenue and gross profit converts at a very high clip to earnings. And then we have been disciplined stewards of capital. And so I think that those are the big buckets of things that we talk to our investors.
Great. I think we're out of time. So we're going to end it here. George, thank you for your time. Thank you, everyone.
Thank you very much.
And have a great afternoon.
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NetApp — UBS Global Technology and AI Conference 2025
📣 Kernbotschaft
- Kern: NetApp zeichnet ein zweigeteiltes Bild: starke Marktanteilsgewinne in EMEA, robustes Cloud‑Wachstum (first‑party Cloud‑Storage +32% YoY) und 200 AI‑Wins; dagegen verzögert sich US‑Public‑Sector‑Nachfrage durch Haushalts-/Shutdown‑Effekte. Margen bleiben dank Cloud (≈83% GM) und Services solide.
🎯 Strategische Highlights
- Cloud & First‑Party: Ausbau first‑party Integrationen (Block für Google ergänzt Amazon), Multiprotokoll‑Angebote und mehr Packaging/Go‑to‑Market zur Skalierung.
- AI & Daten: Fokus auf drei AI‑Use‑Cases (Data‑Prep 45%, Training 25%, Inference 30%); Unstructured‑Data‑Leadership als Eintrittspunkt.
- Cyber & Supply: Differenzierte Cyber‑Resilience im Storage‑Layer (nicht nur Drittanbieter) und strukturierte Preis‑/Liefervereinbarungen mit NAND‑Anbietern.
🔭 Neue Informationen
- Update: Kein radikales neues Guidance‑Update; Management betont bessere EMEA‑Dynamik, vorsichtigen Zeitplan für US‑Public‑Sector, H2‑Lieferbarkeit ist laut Management gut sichtbar; Spot‑Divestiture bleibt kurzfristiger Headwind.
❓ Fragen der Analysten
- Öffentliche Hand: Kernfrage war Timing der Nachholung von US‑Bundesausgaben; Management blieb vorsichtig und erwartet graduelle Normalisierung im Frühjahr/Sommer.
- Margen/Supply: Analysten hinterfragten, ob höhere NAND/DRAM‑Preise durchgereicht werden können; Management verweist auf strukt. Pricing‑Abmachungen und Fokus auf Bruttogewinn‑Dollar.
- Cloud/Spot: Diskussion über Spot‑Effekt und Mix: erste Partei wächst stark, Spot‑Divestition dämpft kurzfristig, aber Mix wirkt marginstärkend.
⚡ Bottom Line
- Fazit: Kurzfristig drücken US‑Public‑Sector‑Timing und Spot‑Bereinigung die Zahlen; strukturell aber stärkere Marktanteile, Cloud‑/AI‑Tailwinds und integrierte Cyber‑Funktionen stützen Margen und Wachstumspotenzial. Wichtige Beobachter‑Trigger: H2‑Lieferentwicklung, Public‑Sector‑Appropriations und Cloud‑Wachstumsraten.
NetApp — Q2 2026 Earnings Call
1. Management Discussion
Good day, and welcome to the NetApp Second Quarter of Fiscal Year 2026 Earnings Call. [Operator Instructions] Please note, this event is being recorded. I would now like to turn the conference over to Kris Newton, Vice President, Investor Relations. Please go ahead.
Hi, everyone. Thanks for joining us. With me today are our CEO, George Kurian; and CFO, Wissam Jabre. This call is being webcast live and will be available for replay on our website at netapp.com.
During today's call, we will make forward-looking statements and projections with respect to our financial outlook and future prospects, including, without limitation, our guidance for the third quarter and fiscal year 2026 and our expectations regarding future revenue, profitability and shareholder returns and other growth initiatives and strategies. These statements are subject to various risks and uncertainties, which may cause our actual results to differ materially. For more information, please refer to the documents we file from time to time with the SEC and on our website, including our most recent Form 10-K and Form 10-Q. We disclaim any obligation to update our forward-looking statements and projections.
During the call, all financial measures presented will be non-GAAP unless otherwise indicated. Reconciliations of GAAP to non-GAAP estimates are available on our website. I'll now turn the call over to George.
Thanks, Kris. Good afternoon, everyone. Thank you for joining us. We delivered a strong Q2 with revenue of $1.71 billion, up 3% year-over-year. Excluding the divested spot business, total revenue was up 4%. All Flash and Public Cloud, which address growth markets and carry higher gross margins made up 70% of Q2 revenue. This shift, combined with our continued operational discipline has enabled us to drive profitability metrics higher. .
Our gross margin set a Q2 record and exceeded our guidance range. Both operating margin and EPS surpassed expectations and marked all-time highs. Expected softness in USPS revenue was offset by growth in all other geographies. We saw strong demand for our AI solutions first-party and marketplace cloud storage services and all-flash offerings.
In the age of data and intelligence, customers are choosing NetApp for our unified data platform that delivers exceptional value and operational efficiencies, fueling our success in the face of the ongoing uncertain macro environment. In October, we hosted our annual customer conference, NetApp Insight where we unveiled major advancements to our enterprise-grade data platform, including enhanced AI workload capabilities, stronger cyber resilience and deeper AI integrations and data solutions with our hyperscaler partners.
Customers and partners shared how NetApp is driving their success in the age of data-enabled intelligence. Their feedback and achievements underscore our commitment to innovation and delivering value in a rapidly evolving landscape.
We launched AFX, an ultra-scalable extreme performance disaggregated storage platform certified for NPDS Superpod designed to power demanding AI workloads and AI service providers. AFX seamlessly integrates into an organization's hybrid multi-cloud data estate with the proven enterprise-grade data management and security features of ONTAP.
We also introduced the NetApp AI data engine, an end-to-end AI data service integrated into ONTAP. The AI data engine, referred to as AIDE, simplifies data discovery querying, searching and analysis. It helps operationalize and scale data pipeline for AI with integrated data discovery, curation, policy-driven guardrails and real-time vectorization. This enables fast data access, efficient transformation and trusted governance.
Together, AFX and AIDE transform how enterprise customers achieve positive AI outcomes by accelerating data discovery and simplifying data pipelines while maintaining security, access controls and data integrity. Native integration with leading AI platforms, including Domino, NVIDIA and Informatica enables compatibility with enterprise workflows. Our zero-copy cashing and native cloud connectivity help organizations unify data and apply advanced AI capabilities across any site, cloud or model, speeding time to insight.
We also enhanced our rapidly growing Keystone storage-as-a-service for Enterprise AI offering AFX and AIDE under a single subscription for elastic scaling and usage-based billing, encouraging broader enterprise AI adoption. These innovations build on our growing success in AI workloads.
In Q2, we closed approximately 200 AI infrastructure and data lake modernization deals across diverse geographies, industries and use cases. Our massive installed base of unstructured data, advanced data and meta data movement services, industry-leading data security and unique hybrid multi-cloud capabilities make us the clear choice for enterprise AI.
Here's an example of why we are winning in enterprise AI deployments. A global semiconductor capital equipment manufacturer selected NetApp to unify its enterprise AI data foundation across on-premises and cloud environments. Our hybrid multi-cloud data visibility and secure governance drove confidence in the compliance and operational efficiency of their AI workloads.
We enable them to create a single searchable view of corporate knowledge across millions of documents, e-mails and engineering data sets providing employees with faster, more accurate access to institutional knowledge.
A large amount of AI innovation takes place in the public cloud. ONTAP is the only unified data platform natively integrated in the public cloud, putting us in a unique position to enable customers to leverage any of the major AI models without the complexities of moving data.
In Q2, we expanded our native AI capabilities in Azure and Google Cloud, adding to what is already available in Amazon Web Services, giving customers the flexibility to run AI workloads wherever they choose. Adding to existing multi-protocol support in AWS, we launched support for block storage capabilities in Google Cloud NetApp volumes in Q2. This brings the full power of ONTAP to Google Cloud with high performance, unified storage, integrated data management and protection and a common cloud control plane.
We introduced new capabilities in Azure NetApp files, including single file restore and a flexible service level for independent scaling of throughput and capacity. And in Amazon FSX for NetApp ONTAP, we announced support for Amazon Elastic VMware service, enabling secure efficient migration of VMware workloads to AWS.
By continuously adding new functionalities to our public cloud storage services, we are broadening our addressable market, driving new customer acquisition and positioning ourselves for continued growth. This strategy has yielded rapid expansion in our highly differentiated first-party and marketplace cloud storage services with revenue increasing approximately 32% from Q2 a year ago.
In Q2, a leading cloud-based media production company selected FSXN as its standard for file and block storage. In addition to multiprotocol support FSXN delivered cost savings through storage efficiency, high availability, superior multi-tenancy and intelligent cashing to put data closer to its users. The company believes that FSXN gives it a competitive advantage in optimizing cloud storage and enhancing performance for its customers, these capabilities for a key customer win.
Customers are choosing NetApp to provide a unified cyber resilient and efficient way to manage their entire data estate. Built for the age of data-enabled intelligence, the NetApp Data Platform redefines what a modern enterprise foundation should be: unified enterprise grade, intelligent cloud connected and ecosystem ready.
We help organizations modernize, secure, transform and use AI with confidence. Continued strong customer engagement and interest in our unified and block optimized all-flash storage portfolio delivered 9% year-over-year growth in all-flash array revenue to $1 billion in Q2 or an annualized run rate of $4.1 billion. Exiting the quarter, approximately 46% of installed base systems under active support contracts are All Flash.
NetApp helps customers confidently safeguard their data with built-in security through real-time threat detection, protection and recovery. In Q2, we enhanced the NetApp Data Platform's industry-leading cyber resilience by launching the NetApp ransomware resilience service for both structured and unstructured data. This service is designed to stop cyber threats before they cause extensive damage by proactively detecting data breaches in real-time and providing isolated environments for safe, clean data recovery.
Our industry-leading cyber resilience capabilities are helping us win new customers and displace competitors. In Q2, a major Asian life insurance company chose NetApp for its mission-critical private cloud environment, replacing its long-standing storage vendor. Ransomware protection was a top priority, and our ability to provide strong cyber resiliency for critical workloads was a key factor in the decision to choose NetApp.
We also announced the latest version of storage grid with new capabilities designed to enhance AI initiatives, improve data security and modernize organization's data infrastructure. Many customers begin their AI journey by updating data lake environments and storage grid object storage delivers the optimized performance, intelligent data management and modern cloud integrations needed to manage massive datasets.
In Q2, a leading financial services company selected StorageGRID to modernize its legacy Hadoop environment with capabilities for a hybrid architecture featuring data durability, a global name space, robust security and automated 0 intervention backup and disaster recovery, StorageGRID addressed the company's next-gen AI workload requirements.
In summary, strong execution and operational discipline delivered an outstanding second quarter. Our focus on growing markets, All Flash, Public Cloud and AI continues to yield top line growth. The substantial innovation we introduced this quarter extends our differentiation and help solidify our leadership position as the intelligent data infrastructure company.
Looking ahead, we are focused on leveraging our alignment to customers' top data initiatives and pressing our significant competitive advantage. Despite the unsettled macro environment, and near-term USPS headwinds, we remain confident that our visionary approach to a data-driven future will enable us to outgrow the market and capture additional share.
I'll now turn it over to Wissam.
Thanks, George, and good afternoon, everyone. As George mentioned, in the fiscal second quarter, we delivered strong results, exceeding both the midpoint of the revenue guidance range and the high end of the EPS guidance range. Total revenue for the quarter was $1.71 billion, up 3% year-over-year. Non-GAAP earnings per share was $2.05. Excluding the divested spot business, which generated $23 million of revenue in the year ago quarter, total revenue was up 4% year-over-year.
The effect of foreign currency exchange rates was favorable to revenue growth by approximately 1 percentage point year-on-year, while it was immaterial relative to guidance.
Looking at revenue by segment. Hybrid Cloud revenue of $1.53 billion was up 3% year-over-year driven by product, support and Keystone. Keystone continues to show great progress with growth of 76% year-over-year. Public Cloud revenue of $171 million increased by 2% year-over-year. Excluding Spot, public cloud revenue was up 18% year-over-year, driven by strong demand in first-party and marketplace storage services.
At the end of the second quarter, our deferred revenue balance was $4.45 billion, up 8% year-over-year and 7% year-over-year in constant currency. Remaining performance obligations were $4.9 billion, growing 11% year-over-year. Unbilled RPO, a key indicator of future Keystone revenue, was $456 million, up 39% year-over-year.
Moving to the rest of the income statement. Please note, my comments will be related to non-GAAP results unless stated otherwise. Gross margin for the fiscal second quarter was 72.6%, above our guidance range. Sequentially, gross margin was up 1.5 percentage points. Gross profit was $1.24 billion, up 4% compared to Q2 2025.
Hybrid cloud gross margin was 71.4%, up 1.4 percentage points sequentially due to product gross margin improving by 5.5 percentage points to 59.5%. Our support business continues to be highly profitable at 92.1%. Professional services gross margin was 30.3% improving 40 basis points sequentially, driven by higher Keystone revenue mix.
Public Cloud gross margin was 83%, up nearly 3 percentage points sequentially and over 9 percentage points year-over-year. Operating expenses of $707 million were flat sequentially and down 2% year-over-year despite the unfavorable effect of foreign currency exchange rates. Operating income was $530 million, up 12% compared to Q2 2025.
Operating margin was 31.1%, up 2.4 percentage points year-over-year, driven by higher revenue and gross margin combined with lower operating expenses. Earnings per share was $2.05, growing 10% year-on-year. Both operating margin and EPS exceeded the high end of our guidance ranges.
Our results demonstrate strong execution on key growth opportunities in All Flash, Public Cloud and AI as well as continued focus on operational discipline. Cash flow from operations was $127 million, and free cash flow was $78 million.
During the second quarter, we returned $353 million of capital to our shareholders with $250 million in share repurchases and $103 million paid in dividends of $0.52 per share. Q2 diluted share count of 202 million decreased by 8 million shares or 4% year-over-year. At the end of the quarter, cash and short-term investments were $3 billion and gross debt outstanding was $2.5 billion, resulting in a net cash position of approximately $528 million.
I will now turn to non-GAAP guidance, starting with Q3. We expect revenue of $1.69 billion plus or minus $75 million. At the midpoint, this implies a growth of 3% year-over-year. Excluding the divested Spot business from the year-ago comparison, our revenue guidance implies a 5% growth. We expect Q3 gross margin of 72.3% to 73.3%.
Operating margin is anticipated to be in the range of 30.5% to 31.5%. We expect EPS to be between $2.01 to $2.11, with a midpoint of $2.06.
Turning now to full year 2026. We continue to expect fiscal year 2026 revenue to be between $6.625 billion and $6.875 billion, which at the $6.75 billion midpoint reflects 3% growth year-over-year. Excluding Spot, our revenue guidance implies a growth of 5% year-over-year.
Based on our Q2 performance and the confidence in our outlook for the second half, we are raising gross margin, operating margin and EPS ranges for the fiscal year. We now expect our fiscal year 2026 gross margin to be in the range of 71.7% to 72.7% and are increasing our operating margin to 29.5% to 30.5%.
We expect other income and expenses to be approximately negative $50 million. For the year, we expect the tax rate in the range of 20.2% to 21.2%. We are raising our EPS range to $7.75 to $8.05 with a midpoint of $7.90.
In closing, as we look ahead to the rest of fiscal year 2026, our commitment to executing our strategy remains strong. We are poised to seize the expanding opportunities in all flash, cloud and AI and remain focused on consistently delivering exceptional value to our customers and shareholders.
I'll now turn the call over to Kris for Q&A.
Thanks, Wissam. Operator, let's begin the Q&A.
[Operator Instructions] Your first question comes from the line of Aaron Rakers with Wells Fargo.
2. Question Answer
I guess the first question would be: As we think about the component environment, both from a potential pricing perspective as well as whether or not you might be seeing any kind of constraints, I'm curious on how the company is managing that? Have you leaned in on any kind of strategic purposes? And any thoughts on the duration of those strategic purchases as far as the next couple of quarters? How much visibility do you have on the pricing dynamics underpinning the gross margin outlook?
Aaron, thanks for the question. So on the components, we did mention last quarter that we did lock in some prices, and based on that, we do have visibility for a couple more quarters, I would say, at least until the end of this fiscal year. When you look at where we are, obviously, we did Q2 product margin was slightly better than our long-term model, which is in the mid- to high 50%.
And then when we look at the rest of the year, we expect product margin -- or product gross margin to be relatively stable to where we ended in Q2. Looking ahead, if I think of the component pricing, look, this is an environment that could be volatile, and so we're not going to make a call on that. But what we do is we look at various scenarios.
We have a very capable supply chain team that has been through many of these past cycles of supply, some of the commodities that we buy with rising cost environment, for instance, but we've been able to manage very efficiently over the years; in fact, while also, in some cases, growing EPS. And so we will continue to manage our input costs and maintain our supply continuity.
We haven't seen any disruption so far. We haven't heard of any as such. Now ultimately, our goal is really to focus on our total gross margin. And this comes down to the various components of our revenue and the mix. And so there's the rate there and the mix. If we continue to see current levels, let's say, of some of the commodities, in particular, let's say, I know you probably have in mind that one of the things, for instance, is NAND. If we continue to see similar levels, we'll probably have a bit of a headwind into fiscal '27 from a product gross margin perspective.
But when we look at the mix of the business, going forward, we continue to see high growth in the cloud business, which is now operating between 80% and 85%. I mean Q2, it was at 83% gross margin. We continue to see good growth in Keystone. And so the mix is very much favorable to us.
The couple of -- the last couple of points, I would say, as we think through all of this, we're focused on driving growth in gross profit dollars, which is foundational to the profitability engine of our business. And lastly, if we are faced with higher commodity prices relative to where we are today, we will always consider our pricing. Our commodity prices are typically passed through for us, and we don't have an issue passing them through.
And Wissam, I appreciate that. That's a very thorough answer. Looking back historically, how quickly could you pass those through? Is that within a given quarter? Does it take a couple of quarters to see that flow through? .
Look, this is probably more of a hypothetical, obviously. As I said, where we are today, we have good visibility till the end of the fiscal year. But we don't necessarily a lot of time to pass them through. We can always adjust prices as needed.
Your next question comes from the line of Erik Woodring with Morgan Stanley.
Great. Maybe I'm going to ask a similar question to Aaron and Wissam that is you're effectively at 60% product gross margins? I know you said we should expect them to be relatively unchanged through the rest of the year. First part of that is just, is this a function of mix to All Flash? Is there still pricing tailwinds? Is this kind of BOM cost down? I don't know if you could just maybe contextualize what the real drivers are of that product gross margin expansion?
And then second, I'll just ask both questions at once, is I realize you don't really need to talk to fiscal year '27, it's too early and the commodity cost environment is quite volatile. But are we kind of at peak product gross margins? Can product gross margins expand from here? Like I'd just love to understand how you think about the sustainability of where we are even regardless of the memory cycle?
Yes. Thanks, Eric. Look, the -- what I said, yes, for the rest of the year, we expect product gross margin to be more or less where we are now. We're in the 59%, I think, and change. When we think about the drivers, it's a combination of things, if I sort of look at where we are year-on-year, for instance, cost is now roughly flattish. And so we are seeing differences mostly driven by mix and pricing that's pretty much what drives the margin.
As sort of I look forward, obviously, as you mentioned, it's too early to talk about '27, but I'm going to talk about theoretically how we think of the long-term product margin of our business. We are targeting mid- to high 50% margin. And so that's really -- we are operating a little bit better than that now, but our target is mid- to high 50% because ultimately, to drive better gross margins for the company, it's really the mix that's going to be also a tailwind.
As our fast-growing cloud business continues growing at high -- and delivering higher gross margin than the corporate average, this should help us improve on our margins. I wouldn't put a cap on our product margin because ultimately, we continue to be very operationally disciplined in how we conduct the business. But I hope this answers your question.
Your next question comes from the line of Samik Chatterjee with JPMorgan.
Maybe if I can pivot a bit more to the revenue side. George, you talked about sort of the AI-related transactions or deals that you closed, looks like 200 versus 125 last quarter. Wondering sort of what you're seeing in terms of trends there? It sounds -- it looks like an acceleration on the sort of headline number of deals you're seeing. And is the AFX solution that you launched at INSIGHT, what sort of customer feedback are you getting? And is that playing into those deals that you're now seeing? And I have a quick follow-up after that.
We are seeing a fairly stable mix of transactions. The volume is growing. The mix has stayed roughly the same, which is data prep and data modernization, about 45% of the mix, training and fine-tuning about 25% to 30% of the mix and the rest is kind of RAG and inferencing. I think you can see the pace of kind of wins have grown.
A year ago, it was about 100 -- greater than 100, now it's close to 200 or 200 approximately. So we're seeing the growth in the number of wins and the mix being roughly stable. With regard to the AFX platform, listen, we have had a huge amount of interest in it. It's going through customer qualifications. It's too early to say that it's because of the results in the quarter. It takes a few quarters for a new system and architecture to get qualified, but we're seeing strong early interest in it.
Got it. Got it. And then maybe a quick follow-up for Wissam here. Wissam, when I look at the 3Q revenue guide, it's roughly sort of flat; modestly, maybe down quarter-over-quarter. I realized last year, you had the same seasonality, but for most of the previous years, prior years, you typically sort of have a seasonal growth from Q2 to Q3.
So obviously, it's a dynamic macro and you have sort of public sector headwinds, but anything specifically sort of driving this seasonality to be a bit below average relative to your prior years into Q3?
So Samik, the -- really the couple of reasons are pretty much what you mentioned. There's a bit of a dynamic macro. We're expecting our U.S. public sector business to be slightly below seasonality given, obviously, the most recent shutdown takes a little bit of time for government to reopen. Having said that, we view these as temporary and long term, we expect that business to get back to normal levels.
Your next question comes from the line of David Vogt with UBS.
I'm going to roll them into one. So maybe George and Wissam, when I think about kind of the demand drivers going into the second half of this year, and I think you said you still expect federal to be sub-seasonal. How do we marry that sort of outlook and then going into '27 with kind of how you're thinking about inventory and purchase commitments because your inventory on the balance sheet is still relatively modest? It doesn't seem like you took in a lot of finished goods for my quick look.
I'm just trying to think how we should think about marrying maybe a recovery in some of the verticals like U.S. Federal next year. Hopefully, that's behind us. And how you're thinking about adding purchase commitments and working capital to support the business next year?
I think maybe I can start and then Wissam can add color. I think, first of all, if you look at the second half implied growth rate, it is up if you look at ex Spot relative to the first half. So we are seeing some acceleration despite the U.S. public sector headwinds in the second half of the year. We see the non-U.S. public sector segments had a strong result in Q2.
Our Flash business accelerated from 6% to 9% in the quarter despite a tough compare a year ago. So we feel good about momentum. We are aligned to what customers are spending. Despite the choppy macro, customers are spending on AI projects on data infrastructure modernization to get ready for AI. They are implementing additional cyber resilience protection.
So we feel good about our alignment to customer spending and then I think the third thing is that the faster growing parts of our business are now a bigger part of the overall number. Cloud and flash are now 70% of the overall number. The slower -- the parts of the business that are not growing are both smaller and also stabilizing more. And so that gives us belief that second half, hopefully, once U.S. public sector gets clarified we should have a strong set of results going forward.
Yes. And David, with respect to commitments. Look, as I mentioned, we have good visibility until the end of this fiscal year, and we would be opportunistic as we go forward. We will be obviously looking at fiscal '27. And before we enter the year, we would want to be able to have good visibility and in many cases, secure whatever supply we need. And so we won't hesitate to take the right actions to make sure we protect our business and we have the supply that's needed.
[indiscernible] like couple of quarters or full year kind of purchase commitments given the environment? Like what's your philosophy going into next year?
I would say it all depends on what we're buying and when. And so there isn't really one answer that fits all. We will be very dynamic. We'll make decisions very fast. But as I said in my earlier remarks, the -- we have a very capable supply chain team. We monitor the commodities, and we don't hesitate to take action as needed. We do have a strong balance sheet. And if we need to do -- if we need to take any specific action to protect our supply or to sort of lock in good prices, we won't hesitate to do that.
Your next question comes from the line of Krish Sankar with TD Cowen.
The first question, George, is for you. You kind of spoke about the 200 AI deals that you closed in the quarter. What is the average size of these deals? And also, where are we in the pilot production journey for enterprise adoption of AI? Is there a way to think about that into 2026? And then I have a quick follow-up.
Listen, the deal sizes are all over the map. I think that there are some that are smaller in proof of concept and there are others that are in scale deployments that are much larger. So I would not share a particular number related to the average deal size that would disrupt the answer.
With regard to the broad themes, I think, first of all, data lakes and data prep are usually prior to scale deployments. They are in the get ready to use AI, bring all of my data together. I think fine-tuning and inferencing are at various stages of the kind of proof of concept to production deployment pipeline. I think if you look at the industry, life sciences, financial services, some parts of manufacturing and public sector are areas where we see AI being broadly adopted with the most advanced use cases in life sciences, and I think that the adoption use cases depend on industry.
Got it. And then as a quick follow-up, this is for you, Wissam. You spoke about the first-party hyperscale services demand was very strong last quarter. Can you just quantify how much did that grow last quarter, the services business?
The first-party and marketplace services business grew 32% year-on-year.
Your next question comes from the line of Steven Fox with Fox Advisors.
I just had 1 question. given all the supply shortages that you're talking about, which seems to have accelerated, I guess, in the last several months. And I understand that you've taken some tactical moves to secure supply. Why do we think -- or is there a risk, I guess, that you run into next year sometime not saying first quarter, second quarter, but is there a risk that at some point that the lack of supply hurts overall demand, whether it's because of overall price of product or just your availability to ship?
I'll just clarify the comment by saying we did not suggest that we have any supply shortages. We said that we have secured supply commitments and pricing through the end of the fiscal year and will take appropriate actions to guarantee supply across a broad ecosystem of suppliers through the next fiscal year depending on what we see.
Okay. So that -- you're confident that it's the price -- whatever price you're talking about a year from now, George, is sustainable in the marketplace, I guess?
Listen, there's a lot of puts and takes in the bill of materials in our products. And so -- and we have a broad ecosystem of suppliers. So we work with them, both to look at a variety of different price points and offerings, and we'll have the right mix.
As we said, the historic pattern of this industry is that when component prices, commodity prices go up, there are pricing actions taken to share some of those price increases with customers. And if it reaches that point, we will have -- we have the experience to do that.
Your next question comes from the line of Tim Long with Barclays.
Two, if I could, as well. Hate to kill the commodities here. But just curious, a lot of talk about NAND, but HDDs are tight and going up as well. So is there -- what's the impact on the business of QLC being used more than hybrid or maybe more than TLC? Any moving parts that might actually benefit the move towards All Flash, number one?
And then number two, the cloud revenues have been pretty consistent, high teens ex Spot. George, you mentioned a lot of new offerings on the big cloud players. Could you just talk about that kind of ex Spot growth rate? Do you think that high teens is sustainable or can some of these newer offerings help accelerate that number even though the base is fairly large?
Yes. On the first question, listen, HDD has actually performed well for us this quarter. It performed, in my expectations, better than we had planned. And so we are seeing a broad range of use cases for these products. We don't see that one type of technology replaces the other. There are use cases for TLC, QLC and HDDs, and we are seeing that pattern in our business.
I think with regard to your question on cloud. Listen, I think broadly speaking, we are super positive about the growth of our first-party end marketplace, cloud services business, they have been ticking along nicely north of 30%, representing strong customer demand for our differentiated offerings. I think that the scale of the business, if you look at the Q2 quarter-on-quarter growth, it was the highest quarter-on-quarter incremental revenue in the history of the cloud business, so we feel really strong about that.
And broadly speaking, we have a really good set of tools for enterprise workloads on the cloud. The next big push is to capture the AI and data-intensive workloads on the cloud. And so you'll see us bring innovations in the market. We already talked about some of them, and you'll see a lot more of that over the next 6 to 12 months.
And so super excited. This is really about scaling the go-to-market. It is almost we can bring on as many clients as we want, it's really bringing an effectively scaling go-to-market motion for our cloud offerings.
Your next question comes from the line of Simon Leopold with Raymond James.
Great. I wanted to see how you thought about your opportunities to win business with some of the sovereign or Neo clouds who are not necessarily hyperscale and building their own storage solutions. How do you see that fitting into your strategy? And what kind of opportunities have you seen so far there?
Yes. We are part of a large number of sovereign clouds across the globe for many, many years. With regard to their AI landscape, we have mentioned sovereign AI wins. We have expanded the range of offerings with the AFX solution that allows us to participate in a broader range of footprints within those sovereign AI cloud, and we are bringing more innovation to the market over the next few months, so stay tuned.
And how do you think about the competitive landscape in that application and broadly the AI opportunities?
I think that as those sovereign providers look to serve enterprise clients with AI workloads, all of the value that we have, both in terms of the differentiated capabilities around security, multi-tenancy, data protection, hybrid, landscape play to our advantage. We are seeing some of that momentum with the introduction of the AFX, people have been super interested in our ability to serve those new use cases that those AI cloud providers are trying to go after.
Your next question comes from the line of Jason Ader with William Blair.
I wanted to first ask just on the performance in the quarter. You had a nice roughly $20 million beat and then you reiterated for the year. So I just wanted to understand why you didn't flow through the beat? Is it just a little bit extra conservatism based on public sector or supply chain or any other factors?
Yes. I mean I think we saw, in the quarter, some really strong. We talked about large deals. We had a good set of those that help offset the really steep decline in the U.S. public sector business. We had not anticipated when we guided the quarter that USPS would suffer such a long shutdown.
And I think as we look out to the second half of the year, if you look at the overall guide for the second half of the year, ex Spot, it actually is an acceleration year-on-year from the first half. But clearly, we want to have more line of sight into how U.S. public sector plays out. As Wissam mentioned, it takes a while for the governmental agencies to get back to procurement and spending. And so we're being tad cautious about that. There are no implications from the supply chain in our guidance.
Okay. Great. And then just a quick follow-up on Keystone. I don't think that's come up in the Q&A yet. You've been in this space for a long time, George, I mean, do you feel like we're hitting some type of an inflection in the storage-as-a-service model? Maybe it's not an inflection, maybe it's just sort of every year, it's going to get bigger and sort of be more of a slow a slow burn. But it does seem like that part of the business is incredibly strong, and we've seen strength across other suppliers as well. So do you think that this is just going to be more of the norm in the storage market over the next decade-or-so?
I think this is a new way for customers to find infrastructure I think it is driven both by maturity of the offerings as well as customers' kind of maturity in using these business models coming from the cloud, right? So they've learned how to buy infrastructure consumption model from the cloud. And so we see that growing as a part of the overall business.
Like all things, enterprise infrastructure is a very large market. And so it will grow as a part of that market. We are excited to lean into that trend. I don't think the whole market switches overnight. Nothing ever happens that way, but it'll grow faster than the rest of the enterprise infrastructure buying models.
Your next question comes from the line of Ananda Baruah with Loop Capital.
George was video such a big theme at INSIGHT let me just site have you and take the opportunity to ask you, anything notable or interesting on video that you saw over the last 90 days that you're seeing emerge? And I guess, video specifically, but unstructured generally in your customer base or in some of the proof of concepts. I have a quick follow-up, too, if I could.
Yes. Unstructured is clearly the place that customers are spending time organizing. We talked about one of the use cases where large semiconductor equipment manufacturer brought together new years of documents across a variety of applications to better understand what their engineers and their operations teams were working on so that they could kind of continue to optimize yields and efficiency in their business.
We see that more and more across organizations. I think with video itself, we talked about the content production house that is using AI to build better, more enriched experiences for their digital clients. And so you're seeing that in certain use cases. We are also seeing the use of multimodal applications starting to grow and then video analytics, for example, in weather forecasting, weather analysis, things like that. And so it's growing. I wouldn't say it's been at the dramatic inflection, but multimodal is growing. We are seeing demand from customers for support for more complex multimodal language models, for example.
That's helpful. And just a quick follow-up on memory. The hard drive makers seem, as we go through next year, like they're pretty intent on mixing up pretty quickly from 20 TB drives to 30 TV drives. Is that consistent, relatively speaking, with what your customer base is looking for also? I guess I'm wondering if that's organically in tandem with what your customers also would want. That's it for me.
I think broadly speaking, customers are looking for aerial density improvements from all of the silicon. We work with our supplier ecosystem to qualify different media types and density points, and we'll do the same. We follow customer demand. We look at what the supplier ecosystem is telling us, broadly speaking, performance, cost and density are the key drivers of new silicon adoption.
Your next question comes from the line of Louis Miscioscia with Daiwa Capital Markets America Inc.
George, on the last earnings call, you seem to be a lot more encouraged about AI, and obviously, you have a lot more wins this quarter. And I guess you sort of were asked this question before, but let me just try again. Obviously, there's been a massive growth in many areas, mostly in servers. But storage, in general, hasn't really seen a big, big pickup from AI.
So when do you think inference applications really start to create more data that would then drive material new revenue for you? Do you see it as maybe first half calendar '26, second half? I mean I assume at some point it has to hit.
Yes. I think we've always said compute and network build-out would be both bigger and earlier than the storage build out. I think it is because the trading of large language models and the algorithms that are being used for AI does not require a lot of storage, right? Nobody is creating a second copy of all the Internet data to train open AI.
And so that build out, of course, will be bigger and earlier than storage. I think as we said, storage is 80% of the storage use is actually from inferencing. And so as inferencing becomes a bigger part of the overall AI landscape, you will see more storage consumption. I think we are seeing it in our business also in the data lake, data modernization business where people are building large-scale multi-terabyte repositories to bring all their data together.
I think if you were to look at what we said, we said, hey, the number of proof of concepts would pick up in fiscal year '26; we are seeing that I think with regard to broader enterprise AI adoption, we've always believed it's use case by use case. It's not a horizontal technology that gets deployed. And so it really depends on the ROI from the use cases that we see. There, we are seeing, like we said, health care and life sciences ahead of the market, some of the other ones kind of heavy in proof of concept, but not yet in production.
Your next question comes from the line of Wamsi Mohan with Bank of America.
George, you said at the end of your prepared remarks that you would be capturing share in the market. And I was wondering how much of that is predicated on some of the flexibility you have in pricing given the supply that you have secured versus product portfolio mix capability. How are you thinking about that? And I have a follow-up.
I mean, broadly speaking, Wamsi, in a transaction the majority of the value is in software and the data platform that the company -- that the customer is signing on to, right? They train their teams on the use of the platform. And I think our growing differentiation not only with cloud but cyber and bringing more advanced data management capabilities is the leading indicator. I think when you are trying to displace a competitor, having kind of flexible set of tools, both things like Keystone or subscription-type services and the ability to price aggressively is helpful.
Okay. Okay. And just a follow-up. You just raised your Public Cloud gross margin range and you're already kind of at more than halfway through that range with a slight increase in revenue in the quarter. I'm just kind of wondering, like what's a natural ceiling with for this business that you see? And maybe you can just -- maybe Wissam can just comment on cash flow as well. It was a little bit weak in the quarter, just thinking through sort of trajectory over there, that would be helpful.
Sure, Wamsi. So let me start with the first part of your question. On the cloud gross margin, look, this is the second quarter we're operating within our upgraded target range. We feel comfortable operating within this range. The -- we're seeing -- we've seen the mix in that business shifting a little bit more towards software and as we talked about before, we've had some roll off and depreciation.
Having said that, they could be potentially an upward bias, but we're -- it's too early to talk about that today. I would say we're still comfortable operating in that -- within that sort of 80% to 85% range that we published last quarter.
With respect to the cash flow, it is -- there's a bit of seasonality in our cash flow. And so Q2 is typically lower, in some cases, sometimes the lowest point in the in the year. But also in Q2, we had the last installment of the tax payment, which had to do with the transition tax that was related to the law that was enacted back in 2017, I believe. So those are, I would say, the couple of factors influencing Q2 cash flow.
Your next question comes from the line of [ Param Singh ] with Oppenheimer.
So I really want to dive a little bit more into your AI wins. You talked a little bit about AI differentiation with AFX and what's helping you win versus competitors. Wanted to understand what are you hearing from customers? Technically, do you feel you're there yet? And if you could share what mix of your AI wins are with existing customers as opposed to taking share for -- from new customers?
I think with our AI wins, just like with our All Flash business, we are bringing on a lot of new customers, and that I'm talking about the on-prem business. The cloud business has been a very strong contributor to new clients. As we have shared, roughly half of all our cloud customers are net new to NetApp, right? And that pattern has stayed the same for a very, very long period of time.
So if you talk about the enterprise storage business, the number of new customers that are signing on to us has been strong. A lot of that is because of unified data management, hybrid cloud kind of deployment options and an increasing number of customers coming because of our built-in compliant cyber resilience solutions, and so those are the key sources of wins.
I think with regard for enterprise AI, we feel really, really strong. Yes, we don't have -- we are ahead of all the competition. Most of the competitors have kind of point products. They don't have an integrated stack. They don't have hybrid. They don't have all of those pieces that we have. So we feel good. Clearly, in our installed base, we have an enormous advantage because we hold all the data. And as we talked about at our INSIGHT conference, we can bring AI to your data rather than copy all your data over to AI.
Got it. And before my follow-up, anything -- sorry, just a quick follow-up. Assuming that you keep winning and your revenue trajectory is going to improve on the product side with incremental workloads coming into AI inferencing. Add to that, you have Keystone going faster, easier comps with spot, increasing public cloud mix, wouldn't it be reasonable to assume that off a 5% normalized growth rate this year, you should see an acceleration into next year? Would that be the right way to think about it?
I'd just say, we will guide fiscal year '27 when we guide fiscal year '27. All of the comments you made are accurate in terms of a growing part of our business is coming from faster-growing components of our business like cloud, Keystone, All Flash and AI. And I think that as that mix gets to be a bigger part of our business, you should expect acceleration. But we'll guide fiscal year '27 when we get there.
Your next question comes from the line of Ari Terjanian with Cleveland Research Company.
First, just on the quarter, good to hear the uptick in large deal activity. I know, George, at the start of the year, you referenced some larger deals in the pipeline. What do you think drove some of the larger deal activity this quarter? Was it execution or maybe there's some pull forward ahead of potential shortages?
And then my second question, it seems like OpEx was down year-over-year. It seems like it's been trending that way. How sustainable is that? Is that more timing related of hiring? How should we think about that in the second half and next year?
Yes. I think, first of all, with regard to wins, listen, this is execution, right? We said we had good pipeline, and we are executing to that. I do not think that there are pull-ins due to supply chain, right? I mean, listen, we have never said there's a supply chain issue in our kind of our pipeline.
And so I just -- we'll just say, hey, these are wins, you always get some that get closed earlier than others and some that get closed later. I think that our strength in the business helped offset a significant kind of deterioration in U.S. public sector due to the shutdown. And so we feel good about that. With regard to OpEx, I'll let Wissam comment on it.
Yes. With regards to OpEx, look, this is a matter of timing. We expect it to be potentially slightly higher from here for the second half. We do want to continue to invest in the business. We want to invest in the growth of our business, and so I'll leave it at that.
Your next question comes from the line of Amit Daryanani with Evercore.
This is [ Hannah ] for Amit. I was just wondering for All Flash, the growth accelerated rather well this quarter. Can you just touch on what drove that? And was it pricing, portfolio refresh or was it AI?
I think that from a workload perspective, AI was noticeable. With regard to the mix, listen, I think we have refreshed the full set of systems last year, [ Hannah ]. And so we're seeing the benefit of that as customers have qualified the system and started to use it. And then we saw strong results, especially in the high-performance area, where our offerings are -- did really well in the quarter.
Your final question comes from the line of Asiya Merchant with Citigroup.
Great. Just I was wondering, you answered partly that about the high-performance mix shift. I think there was some mix shift that worked the other way in the prior quarter. So just -- as you look ahead, the guide for the overall gross margin ticking higher here, if you can just kind of lay out how you're thinking about the mix here?
And then what's embedded in terms of Public Cloud revenues because obviously, that's the higher margin. What's embedded in terms of public cloud revenue growth expectations for the third quarter?
Asiya, thanks for the question. Look, we don't guide to that level of granularity. I think I've said enough with respect to product gross margin to sort of give an indication as to how we expect the next couple of quarters to shape up. With respect to Public Cloud, I would expect -- as I said, from a margin perspective, we're comfortable in where we are operating, exiting Q2. And from a revenue perspective, we talked about the growth being very much in line with what we've seen over the past, let's say, couple of quarters. So hopefully, this helps.
All right. Thanks, Asiya. I'm going to turn it over to George for some final remarks.
Thank you, Kris. Strong execution and operational discipline enabled us to deliver an outstanding second quarter. Our focus on AI, all-flash and public cloud continues to yield top line growth in an uncertain macro environment. In the quarter, we introduced substantial innovation to extend our differentiation and further solidify our leadership position. Looking ahead, we remain confident that our visionary approach to a data-driven future will enable us to outgrow the market and capture additional share, driving value for customers, partners and shareholders.
Thank you. Have a great Thanksgiving.
Ladies and gentlemen, this concludes today's call. Thank you all for joining. You may now disconnect.
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NetApp — Q2 2026 Earnings Call
NetApp — Q2 2026 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $1,71 Mrd (+3% YoY; ex‑Spot +4%)
- EPS: $2,05 Non‑GAAP (+10% YoY)
- Bruttomarge: 72,6% (Q2‑Rekord, über Guidance)
- Produktmix: All‑Flash $1,0 Mrd (+9% YoY; Run‑Rate $4,1 Mrd); Public Cloud $171 Mio (+2% YoY; ex‑Spot +18%)
🎯 Was das Management sagt
- AI‑Fokus: Einführung von AFX (extreme‑Performance Storage) und AIDE (AI Data Engine) zur Beschleunigung von Datenpipelines und AI‑Deployments.
- Cloud‑Integration: Native ONTAP‑Erweiterungen für AWS, Azure und GCP; Block‑Support in GCP und neue Azure/FSx‑Funktionen.
- Service‑Modelle: Keystone (Storage‑as‑a‑Service) mit AFX/AIDE unter einer Nutzungstarif‑Option zur Beschleunigung der Akzeptanz.
🔭 Ausblick & Guidance
- Q3: Umsatz $1,69 Mrd ± $75 Mio (Mid ≈ +3% YoY), Bruttomarge 72,3–73,3%, EBIT‑Marge 30,5–31,5%, EPS $2,01–2,11.
- FY‑2026: Umsatz $6,625–6,875 Mrd (Mid $6,75 Mrd, +3% YoY; ex‑Spot +5%), Bruttomarge 71,7–72,7%, EBIT‑Marge 29,5–30,5%, EPS $7,75–8,05 (Mid $7,90).
- Risiken: Kurzfristige US‑Public‑Sector‑Schwäche (USPS) und mögliche Volatilität bei Komponentenpreisen (z.B. NAND); Sichtbarkeit bis Ende Fiskaljahr gesichert.
❓ Fragen der Analysten
- Komponenten: Nachfrage nach Durchreiche von Preissteigerungen; Management hat Preisbindung bis Jahresende, mögliche Headwinds für FY27 wenn NAND steigt.
- AI‑Wins: ~200 AI‑Deals in Q2 (Anstieg); AFX großes Interesse, aber noch in Qualifikations‑/Early‑Adoption‑Phase.
- GTM & Seasonality: Keystone‑Momentum stark (↑76% YoY); Anlegerfragen zur Saisonalität wegen US‑Public‑Sector‑Shutdown und OpEx‑Timing.
⚡ Bottom Line
NetApp lieferte ein besser‑als‑erwartetes Quartal, hob Margen‑ und EPS‑Ranges an und setzt klar auf AI, All‑Flash, Public Cloud und Keystone als Wachstumstreiber. Kurzfristig bleibt Vorsicht wegen US‑Public‑Sector‑Schwäche und Komponenten‑Risiken angebracht. Für Aktionäre: solides Execution‑Signal mit Potenzial für Beschleunigung, aber Risiken im ersten Halbjahr Folgejahres beachten.
NetApp — 2025 INSIGHT™ Customer Conference
1. Management Discussion
Hey, everyone and thank you for joining us for the investor session at NetApp INSIGHT. Hopefully, you were able to attend the keynote this morning or watch it on the webcast. But if not, you can catch it on replay. Lots of exciting announcements for you.
But before we get started, I'm going to read a safe harbor for that. Each of the 2025 INSIGHT Financial Analyst tech sessions may contain forward-looking statements and projections about our strategies, products, including unreleased offerings, future results, performance or achievements, financial and otherwise. These statements and projections reflect management's current expectations, estimates and assumptions based on the information currently available to us and are not guarantees of future performance or products, services or features. The development, release and timing of any feature or functionality for NetApp products and services remain at the sole discretion of NetApp and are subject to change without notice. Actual results may differ materially from our statements or projections for a variety of reasons, including macroeconomic and market conditions, global political conditions and matters specific to the company's business, such as changes in customer demand for storage and data management solutions and acceptance of our products and services.
These and other equally important factors that may affect our future results are described in reports and documents we file from time to time with the SEC, including factors described under the section titled Risk Factors in our most recent filings on Form 10-K and 10-Q available at www.sec.gov. These forward-looking statements made in the presentations are being made as of the time and date of the live presentations. If the presentations are reviewed after the time and date of the live presentation, even if subsequently made available by us, on our website or otherwise, these presentations may not contain current or accurate information. We disclaim any obligation to update or revise any forward-looking statement based on new information, future events or otherwise.
Okay. With that out of the way, we have an exciting agenda for you today. You'll hear first from our CEO, George Kurian, who'll give you a recap of the general session. Then Syam Nair will come and talk about some of the exciting AI innovations that we've made around the NetApp data platform, specifically AFX, which is the disaggregated ONTAP for exabyte scale and the AI data engine, a foundation for Gen and agentic AI. Gagan Gulati will come and talk about cyber resilience. And today, we announced enhanced Ransomware Resilience service. You'll hear from Sandeep Singh around data infrastructure and modernization, how we're helping customers streamline costs and operations.
One of the announcements we made today is the Shift Toolkit, which provides near instantaneous conversion of VM reformatting across hyperscale -- across hypervisors, important in this day where everyone is trying to move around their current hypervisor. And then Pravjit Tiwana will come and talk about cloud transformation. And today, we announced a number of features that will expand our opportunity in the cloud, including block for Google Cloud NetApp Volumes and support for SnapMirror and FlexCache across all hyperscalers. Finally, we've got a really cool customer panel with customers from the 49ers and Levi's Stadium, the NFL and Aston Martin F1 team.
With that, I'm happy to introduce our CEO, George Kurian.
Thank you, Kris. Welcome to all of you. Welcome to NetApp INSIGHT. We have a super exciting agenda over the course of the next few days, talking about how we are continuing the pursuit of our mission, which is to help our clients unlock the power of their data using the widest range of applications possible. We started that journey with network file storage, where work groups wanted to share data. We brought that to enterprise scale with the unified data storage platforms that we introduced many years ago. We brought it to hyperscale scale with our hybrid cloud solutions, our hybrid cloud data fabric. And what all of this was really driven by is the idea that the best return on investment on your data and the infrastructure that holds that data is that you can seamlessly connect it to all of the sources of innovation and services in the world.
And the latest group of those services is really large language models and multimodal models, which is the AI landscape. AI itself relies on good quality data, right? I think you all know that. And the biggest challenge with using AI effectively is how do you actually manage the data, organize it, curate it and feed it into these AI models in a transformed manner, right? And this idea of going from your enterprise data, which is created out of the applications that run your business to AI-based AI-ready data is called a pipeline and a pipeline is essentially a series of steps that we talked about. The challenge with pipelines have been the classic way of building pipelines were created for structured data. This is data that is out of databases or data warehouses where the schema of the data is already well defined, meaning the structured data typically is in some table format. You've got a description of the data in the structure of the table and you've got access controls and governance rules built into the way the table operates, right?
For unstructured data, you don't have a schema. You have to generate a schema and you have to generate that schema using technologies like LLMs. The second is the volume of unstructured data and the change rate of unstructured data is an order of magnitude larger than for structured data. A large database, for example, is a few terabytes. A single media file can be 100 terabytes. And so there's just literally no comparison between structured data and unstructured data for that. And so one of the challenges that clients have is, if they use the classic approach, they have to copy all this data into an application for annotation, then into another application for unification and then another application for transformation. It's insanely expensive and complex. It is extraordinarily hard, if not impossible, to carry forward data security, access controls, lineage, all of the things that you want, which makes traceability very, very hard to do. So let's say you run a model and you have drift in the model's results, you have no way to figure out what changed the source data.
We envision what we call a data platform that is built to accommodate all the types of data in the world, right? And so we see 3 things in there. The first is the idea that you will have multiple data formats on which your applications want to operate. You'll have enterprise data formats. These are your classic file, block and object where traditional enterprise applications want to access data. You'll see GenAI and agentic applications that want to use what's called a vectorized embedding or a tokenized data format. And then the third is, you want to have metadata operations on what's called a canonical data format.
This could be like an iceberg table or it could be a JSON representation of file data. And the data platform needs to support all of them. What we have done, which is unique in the industry, is we are saying, "Hey, you can keep your source data in one place with one kind of a copy. That's the original source data. You don't have to create multiple copies of it but you can present it in different ways to the different applications." So you can present it in a canonical way, for example, in an analytics application that wants to use Spark, you can present it in a vectorized manner for LLMs, you can present it in the classic file, block and object format to a traditional application.
And a lot of our original IP in ONTAP allows us to do this. What this enables you to do is to massively simplify your pipeline, right? You can make the pipeline -- you don't have 6 copies, you have 1 copy, which is the original data. You can maintain security, access controls, lineage, everything is able to be built in as you transform the data. And importantly, you can keep the source data and all its transforms in the same volume so that if you delete the source data, you automatically delete all its transforms.
Or if the source data changes, we have a data change detection engine in ONTAP that allows you to update the catalog of data and say, hey, these models need to be rerun because the data changed, right? So there's lots of intellectual property that we have built for a long time that helps us do that super, super efficiently, way more efficiently than any other solution in the market. Today, you've got a lot of dumb storage systems with a stupid parallel file system on top of it. They go fast but they can't do any of these transforms, right? They will say, oh, for transform, you got to feed it up into another pipeline.
Now think about how much time it takes to extract, let's say, 20 terabytes of data from a storage system, copy it up into an annotation system and rewrite it back into the parallel file system, right? That's the most brain-dead idea I've ever seen. So you know what, we are like saying, "Hey, you want performance, we'll give you performance." And I'll talk about how you do that. But you need the data management because without the data management, you are basically doing batch data copies everywhere. The second element of what we announced was what we think is a new class of data infrastructure, right? Which is, you've seen newer technologies that are essentially what you call memory speed fabrics, where you've got memory speed connectivity across network fabrics. What this allows you to do is, build systems that are highly flexible. You can combine processing, memory persistence or storage in flexible ways.
And so what we've done is we've architected a disaggregated system that combines data access nodes and data retrieval nodes, which are classic storage constructs with data processing and transformation nodes which are GPUs or CPUs within the same trust boundary of data access, right? So what -- how does that work? What that does is, it allows you to do the activities that you need on the data. For example, on unstructured data, we said you need to actually enrich the data so that you can get the metadata, right? It isn't created out of the gate so that you can actually now run AI models against it.
You can run them on the GPUs but it is completely within -- it feels to the data that's resident on the storage like a trusted user is accessing it. So all of your security and access controls, your protection, your guardrails, all of that's carried forward. So that's really the 2 big things, right? We feel like, hey, a lot of the data platforms in the world, like data lakes and warehouses were built for structured data. They're not going to scale for unstructured data. That to really manage unstructured data and, in fact, all forms of data, you need to embed the intelligence right where the data is created.
Like we've done that for security. We did that for storage efficiency. Now we're doing it for data transformation and enrichment. And to do that effectively, we've created a composable system that allows you to mix and match data access and data transformation nodes in one unified system architecture as well as a suite of software services that combines our tech with tech from NVIDIA that allow you to process the data and transform it in place without copies. We're super excited. I was out at the Expo show right after the conference. And I can just tell you how gratifying it is to have 2 or 3 clients walk up to me and say, "Hey, you were listening to my problem. You got the perfect solution." I'm super excited. One was a pharmaceutical company. The other was a manufacturer from Germany that we have worked with for many years. And they said, what's especially unique about NetApp is, you guys keep making ONTAP better and better so that the investment we've made in your tech, now you're making it available in so many new ways.
So thank you for coming. Have an awesome conference.
All right. Thank you, George. Appreciate that. Now I am happy to introduce to you our new Chief Product Officer, Syam Nair. He will tell you a little bit more about what we're doing in AI and give you guys an opportunity to ask questions.
First off, thank you. Thanks for coming. Hopefully, you had a good start today with the conference. Thank you. Look, I -- first, I'm new but I'm super excited. Super excited because 3 things. One, this is the time where customers are really looking at navigating 2 secular trends. Cloud, it still continues to be a journey for most enterprises. AI transformation, everybody talks AI. You hear about it everywhere. But most of the investments today is on the compute side of it. The real value for AI comes from data. Data is growing significantly. And not like the Hadoop days, now we are talking about LLM models, machine-generated data, growing unstructured data. This is actually an explosion where a lot of value sits in the data. It's really, really, really hard to get value out of the data. Okay. Anybody who has worked across the data industry for anything knows that the overall processing of data is where most of the complexity, cost, time spent is, right? We can change the game by bringing in this intelligence that George talked about to the platform.
And intelligence into the platform does mean like think about this, in the future, every unstructured data set is like a database. If you know about iceberg, imagine everything is an iceberg table. You can just query, run search, semantics, data models, vertical models on top of it. Like it's just not a vision. It's something that we are executing towards now with our AI data engine. That's where we have actually built in a metadata engine on the ONTAP platform. We have a vectorization on the ONTAP platform. We have built in guardrails for AI security because a huge challenge for most of the people who are actually trying to get anything out of AI is how do you secure that data? How do you protect the data? These things are built into the platform. And I think it's a unique opportunity for us, unique opportunity to serve our customers who actually have this data set across industries, whether it is media and entertainment, pharmaceutical, manufacturing, across industries, this is the same problem that we get a chance to solve it.
So most of the announcements today for us was actually moving on to the journey. Now one of the other key differentiators is the flexibility we give customers. [indiscernible] really proud to say that nobody else can do this because we have the same platform running across any of the hyperscalers and on-premises. And data grows in hyperscalers and AI factories and on-premises. They are not going to be moved from one place to the other. So keep the data where it is, like technologies like FlexCache that we have built into the ONTAP platform, SnapMirror, data for AI can move to the edge without actually copying the data, like data sprawls. I don't know if you talk to customers, I've talked to several customers who have said, sometimes, no exaggeration, sometimes 60 to 70 copies of data that they don't even know where they are because every departmental data is moved on. Some are moved on to the lakehouse for harmonization, modeling, et cetera. So like we can cut all of this and really bring the data to that. That's the power of AIDE that we are actually building.
I've been part of the data outcome technology for some time. After my operating system career, I was mostly with databases, NoSQL, Big Data. Many of you may know it was a big thing. Hadoop was going to change the world. It did. It did actually create a new set of applications. Cloud changed the world. It did. It did create a new set of applications, new way of managing data. But some of the challenges in terms of getting value out of unstructured data continued. And now is the moment because there is compute. Now is the moment because there is storage capabilities that is intelligent where you can directly get intelligence and analytics out of it. So that's the excitement I have in terms of what we are embarking on. AIDE, AFX, true disaggregated storage. This is where we are actually building disaggregation on top of all the data management capabilities because you disaggregate compute and storage but you need all the data management capabilities. That's the most precious thing for most of the customers.
It's the data. It's the semantics of what is in the data. Each file is just a file without the metadata. Once you look into the metadata, it has lots of precious information. How do you protect your IP? How do you protect the attributes that are in the data? How do you actually make sure that's your key value that you can continue to protect. These are all things that data management, AI security capabilities built into the platform provides. So AFX plus AIDE, the cyber resilience capabilities that we have had, right? Everybody world over, I came from a cybersecurity company before this. Most of the threats in cybersecurity comes from AI. AI-driven threats are growing. I don't know if many of you know this, the average time for a threat to break out is 2 minutes. And many of the people who say, "Oh, once it happens, I can actually figure it out." No, harm is done. You need to protect it before it happens, which means that protection needs to sit where your precious commodity is, where your precious asset is, which is data.
So I think, super excited. The fact that we have AFX from a disaggregated storage standpoint. We have AIDE, which is a data engine built in, the intelligence built in, cybersecurity built in. I think it's a huge growth opportunity for us to build that capability and grow that capability. And then cloud across hyperscalers. Now, again, nobody else has this where all of the hyperscalers have all the functionality. What I was showing at the keynote, I don't know if you got a chance to watch that, where once I copy file, it can show up in every place where I can do read/write but I'm not really copying it across there. I can use FlexCache to bring data where the compute is. That's actually a phenomenal thing.
It was actually built years ago for ONTAP. It was built years ago. It wasn't built for AI. But now is the time where everybody can leverage it because customers are adopting cloud. That's where most of the AI adoption is going. Customer data sits on on-premises because there is a lot of data over the years. This is their IP. So the opportunity for us is big. I look forward to continue to innovate in that space, create new business opportunities for us to grow. I've never been this excited in terms of what we can actually do to delight our customers, continue to keep the trust of our customers, make sure that customers are successful. So super excited to be here. Thank you and [indiscernible]
All right. Let's get some questions going. Ananda, in the back.
2. Question Answer
Yes, great keynote this morning as well. I guess, Ananda Baruah at Loop Capital. How -- could you describe to us how we should expect this to -- like the manifestation of this to begin to show up in the business? Where is that journey today? And is this -- is really what we're talking -- you're talking, you guys are describing, you and George, is it really a share gain story? Or is it a market share story, maybe more appropriately as this whole dynamic gets going?
Yes. I think it is on 4 fronts. One I would say is AI-ready storage, it's still a challenge for most customers. Everybody talks about there are new stacks but customers already have infrastructure that is -- they are leveraging. How do you make those storage AI ready? So that will be a share gain in the context of across blocks, files and objects, we can provide that one platform, reducing the complexity of managing multiple systems. So that is going to be a share gain story for us. The second one is a share gain as well as additional value is going to be cyber protection. I think, look, most of the money is being spent in terms of cyber protection outside of infrastructure. AI gets all the hype but cyber, all the way from zero trust to making sure data security. Data security is one of the biggest problems that is facing the industry today, especially when it comes to AI. When you talk to customers, you find that most customers tend to either open up or close down. There's no middle ground out.
And most of the AI security value they get today are visibility, what is being used. Many of your enterprises would also have the same challenge. We can bring in AI security directly to the storage, directly to the data platform. That should give us an uplift both in terms of storage as well as value add that we are providing customers because customers can now take away additional tools and expenditures they have to rely on the platform. That's the second part of it. Third is going to be the AI data engine. AI data engine is going to reduce the complexity of what customers have to do to get their -- make their data AI-ready.
Look, George talked about how lakehouses and the overall -- if you're familiar with the bronze, gold model of taking -- bronze, silver, gold model of creating data, harmonize it, model it, then create entities and find value on top of it. I think there's a lot of work that customers are spending there that they will see value in not having to do. I'm hoping that will bring us more additional value add in terms of what we're doing. So I would say storage is one but cyber and AI data engine would actually drive more.
Ananda has got a follow-up, then we'll get to Lou.
That's great. Just a quick clarification -- not clarification, just specification. So for cyber, do you think you capture cyber budget from other folks? Is that how you see it? And then, just in your experience, where do you think customers are right now with their proof of concepts and their journey to inference? That's it.
I think 2, both on the cyber and the AI front, I don't envision us being a cybersecurity company. It's more about bringing that value to so that our software, our hardware, our systems are more valuable. So it becomes a premium for what customers have to spend on us, reducing their budget somewhere else. I'm not looking to be a pure cyber play company because it's not the core competency that we are in.
Let me, I guess, tailgate a little bit off of what Anand just said. This is Lou Miscioscia at Daiwa Capital Markets. So on the last earnings call, George talked about 125 AI infrastructure wins. So just trying to understand, when customers have their proof of concepts, they're trying to do something, what's holding things back in the sense -- I mean we do hear about a lot of applications but there's an awful lot of money obviously being spent with this infrastructure. Really like to see and know if enterprises are really starting to move forward in size, which obviously would then justify all the investments that are being made or the justifications for the investments only really with the big cloud and the mega tech companies.
I'm not sure that there is holding back per se. I think the -- most of the spends have been more on the compute side of it, experimentation side of it. I think customers are seeking value in terms of trying to get this value out of data. I think it's more an opportunity for us that we'll continue to see. We are growing really well in object storage because object storage for lakehouses is a key ingredient for AI. And with AFX and AIDE, there's a keen interest from customers wanting the disaggregated storage and having -- being able to build AI engines on top of it. Like just a proof point in terms of just our own AI session, I don't know if it was overflowed but both the room full was overflowed and people are talking about, look, this is what I've been looking to. People have a lot of interest. Customers have a lot of interest to see driving AI value directly out of it. So I think it will grow for us significantly over the next few years.
Kat Campagna from Goldman Sachs. Shifting gears a little bit. I wanted to ask a question about today's announcement with [ GCP ] and the new block storage capabilities that you talked about. Why was this important for your customers? What does this really help? And how does this change the outlook that you have for public cloud growth into next year?
Just really quickly, we do have a cloud expert coming later today but...
Yes. [indiscernible] will talk about it. So a short summary of that is, look, customers, as they're migrating, they're leveraging cloud more and more today than before, right? And customers are seeing the flexibility and scalability in extending to the cloud. And every customer has a cloud choice or multiple cloud choices. The unified platform where customers see the simplicity of being able to leverage both NAS and SAN is important for them when they think about workloads. Virtualization is a good example of workloads that they're moving to the cloud, where having block capabilities actually help us. New AI projects, one of the things that is stopping AI projects is the capital-intensive nature of it. Many of the customers are leveraging new AI projects in the cloud. So having block capabilities actually help there.
All right. We have a question for Wamsi.
Wamsi Mohan, Bank of America. I was wondering if you could just talk about your announcement around the new DGX SuperPOD, like you're qualified for that. And I think back about 6 months ago, you had AFF A90 that was qualified for that. So how are customers looking at this versus the prior? Is it different -- is there any difference in the software offering? Is it purely the scalability across maybe compute and storage that's different? How are you positioning that for the market?
Yes. It is more on the capability of -- there are still workloads that don't need a disaggregated architecture. Like there are also workloads that are very focused on disaggregated architecture, especially where you have to checkpoint when you're doing model training, et cetera. So the AFX and the SuperPOD certification helps us actually get into a market that we weren't there much because AFF could actually help in terms of the inference on. So it's more an expansion. The other thing is it's also a proof point for us in the context of as compute and storage and compute and data -- data platforms are getting segregated, we can actually play a full fidelity role in the NVIDIA ecosystem. So we are working with what I would call as Neoclouds or AI factories that are coming up, being -- trying to be the partner there because we actually have the assets now to be with NVIDIA and go and win those games.
We have a question from the webcast.
This is on behalf of Aaron Rakers at Wells Fargo. Just given AFX is a new and incremental part of the NetApp portfolio, how should we think about sizing the TAM opportunity that new AFX systems and platform address? And I have -- there's a follow-up too.
I don't have -- know if I have an answer for that, Sandeep or...
Yes. I think we'll see if someone later can answer the TAM question. If not, I'll do some research and get back to you, Aaron.
And who are -- in terms of AFX, who do you see as the key competitive platforms? Is it Dell Project Lightning, VAST, WEKA, Pure? Could you kind of expand on that?
Look, I think from my perspective, it is an opportunity for us to gain. I'm not looking at this from a pure competitive standpoint, right? There are competitive products out there but our product because we are building on top of the ONTAP platform, all the data management capabilities that we have as well as the fact that whatever we are building as a platform is available in every cloud, that differentiates us. So it's -- to me, it's not a competitive play. Look, we will be the best platform for customers to solve this. That will actually help us grow.
Yes. Mehdi Hosseini, Susquehanna. Two follow-up. If I just step back and look at the announcement today and look at all the comments you made, would it be fair to say that the vast AI opportunity for NetApp is still focused on enterprises. I understand most of the investments so far has been on compute but many of these investments are also enabling native data, native workloads to benefit from AI. And I didn't hear anything that would give me confidence that you have actually expanded your exposure to hyperscalers and perhaps it is the enterprise given your ONTAP installed base and additional products you introduced today would actually help you with the incremental opportunity on the AI side. Would that be a fair way of summarizing this? And I have a follow-up.
I would say both. I think it is fair that we are strong and we will expand. But when Pravjit comes, he can talk about the number of new logos that we actually have on the cloud, these are not NetApp customers. We are bringing in new customers on first-party NetApp offering in the cloud. And many of those workloads are for high-performance and AI-related workloads. So I think there's a growing trend of using AI within the cloud that will also drive given some of the innovations that we have built.
Okay. I heard you talking about data management. Is this a new focus area, especially with enterprise opportunities related to AI? Are you trying to expand your installed base of storage and add another layer of value-add services?
Yes. It is the -- so if I talk data management in true context, just to be -- so the -- there is the storage-based data management capabilities that were built into ONTAP, that's part of the ONTAP. There are also functionalities in terms of -- where cyber protection is a good example of it where data has policies and that policies travel with data. Now when you think about AI workloads, that's going to be something that is going to actually accelerate adoption of the AI workloads. So when I talk data management, I'm talking about the core data management capabilities, but this data engine and some of the other capabilities that we are running, those are net new, enabling newer workloads, new scenarios for customers. So there's both sides.
Does that mean that you will go back and provide a mix of hardware and software within your product revenue?
I'm sure I'll update. Yes. Not a question for him.
All right. Tim?
Tim Long at Barclays. Just wanted to get back to -- I think you've kind of touched on these a little bit, AFX and AIDE. Talk -- kind of newer solutions, so can you talk a little bit about sales force channel customer education to realize the benefits here? And as a result, does that mean a little bit longer path to revenues than -- or to deployment than some of the existing technologies? And just curious if in one or both of them, do you think there's a little bit more of a software maintenance, software services bent? Or is this more similar to some of the other product innovations?
Is César or Dallas [indiscernible]
No.
No. So I'll touch base on it. I may not be able to answer the whole question. Then, maybe Kris, you can, you may be able to follow up. The -- for us, both cloud and hybrid cloud in the context of it, what we are building as a product capability is going to serve both the customer bases. So that becomes added value for us, like we are working with ANF Azure, [ GCME ] from a Google standpoint as well as AWS to make sure that all of the platform capabilities are running there. As an example, AIDE that we have delivered is built on top of ONTAP. It's actually available as part of a system that we are selling AFX and with NVIDIA nodes. The same software can actually open up entire ONTAP estate, be it on the cloud for customers. So that's going to be additional value add. The exact go-to-market motion and business, I don't have an answer. Kris, you can. Yes.
Yes, we can follow up. And you'll probably should expect to hear more on the earnings call about how we're taking this to market.
All right. Samik?
Samik, JPMorgan. Maybe if I can go back to AFX and sort of you described it in your keynote as like meant for exascale level storage at that point. Maybe more directly, does it really position you differently with some of the new clouds that have been looking at these opportunities? Does the scalability help position you differently? And then a follow-up on the cyber resilience or cybersecurity as well. Like mentally, I'm thinking you're just going to go up against like the companies like Rubrik, Cohesity. But why would the customer then sort of think about allocating some of the budgets that were addressed to those companies over to maybe paying more of a premium for your service?
Okay. I'll cover the product side of it, not exactly the financial aspect of it in terms of -- so the AFX one, yes, it does position us well with some of these -- you think about these AI factories, giga factories that are forming across the world, like sovereign clouds, it does actually position us much better to have a good footprint because now we are providing not just -- I think George used the term dumb storage, it's actually smart storage that can actually help customers drive value out of it. It does position us well. We are working with some of the partners in terms of how we become part of this ecosystem. It's in early stages of it but technologically, it positions us well.
Cyber, I think it's a two-pronged thing. Look, we want to be the best cyber -- not just from a resilience and data protection standpoint but from an AI security standpoint built into the platform. which should make our platform much more easier to use, reducing the complexity for customers, much more secure, gaining trust. That itself is an added advantage to us from a platform. And then what we want to work with is, we want to work with the ecosystem vendors, like there are others out there to be able to leverage our APIs. So we want to work with open ecosystem, with the partners. So we're not looking at from a product positioning standpoint, this to be an alternative. How exactly the dollars move around, I think we'll have to figure it out. But I think technologically, it will make us much more advanced and ready to be the platform of choice for most of these workloads in the future.
All right. Steve.
Steve Fox with Fox Advisors. I guess I'm still a little bit confused on just the competitive advantages that you're laying out because you've had the advantage with ONTAP. You've had multicloud and on-premises. So like what is different or what came together in terms of these product announcements today that sort of you're bringing together and [indiscernible]
Thanks for that question. I'll clarify. The disaggregation allows our customers to scale performance and capacity independently, which was a challenge and many workloads, not just AI, many workloads need it. Media and entertainment is a really good example of it where there is lots of [indiscernible] and they want performance from a different standpoint. So that actually opens us for multiple new workloads where we have been playing but we become a major player in that space. That's #1. The AIDE in itself is, look, today, customers do get value out of it because it's complex. The pipeline that George showed, if you were at the keynote, that's real. That's actually from a particular customer and many customers and I've been in many of those shoes. It's really hard to move data, multiple data copies and transformations happen to really make it meaningful. AIDE takes that away and that is now available across the platform everywhere.
So for customers, I think the differentiating factor is, if the data is in the cloud or on-premises, immediately, all of this data is accessible for AI without having to do that complex processing, complex set of pipeline that is needed. And that's a huge opportunity because it reduces cost for customers. We provide more value. So it reduces the complexity. And it also like actually helps them transform their AI projects much more faster. Like industry analysts have been talking about that, it depends on who you listen to, 40% to 60% or 87% of the AI projects in reality in enterprises are not succeeding. And most of them are not succeeding because the data isn't ready. The infrastructure is not connected for AI. These 2 innovations that we showcased today and that we are delivering actually connects customer storage and their data, especially their unstructured data estate to AI so that they can drive value. So I think it's a huge innovation from that standpoint for us.
All right, Frederick, in the back.
Frederick Gooding with William Blair. There was a nice slide in the keynote earlier talking about the combination of data management services, the metadata engine and then also unified data storage. I'm curious, do you see any of those specific segments driving either more interest, customer demand or as like a higher competitive advantage? Or do you think it's more of the fact that all these are integrated within a platform together and that is really -- sets you apart from anybody else?
Look, it's -- I could have, with all of the innovations, could have gone and claimed we are the new database. I'm not trying to do and claim something that it is not. What I really, really want to make sure that everybody, all our customers understand is the amount of work that it takes to get value out of this is simplified now because we are able to do it on the platform. It's additional compute, it's innovation, it's on the platform. So I would expect it to drive both, which is to make us the platform choice, also drive more value towards our platform because now you don't need to do all the other aspects of it. So it's not -- it is going to be a competitive advantage purely with the competitors we have. But it is also going to be a competitive advantage in terms of winning workloads because there are many other steps that can be eliminated for the customers. Does that answer the question?
All right. Ananda?
Okay. Quick follow-up. To your comments about starting to have conversations with the Neoclouds, do you know if there's any distinction to make within those conversations between training opportunity and inferencing opportunity?
Yes, there is. I think -- and this is something from a product standpoint, we are also looking at in terms of many of the major needs that is actually driving some of these data center and Neocloud investments are training opportunities. And in many of this training, the consistency of the data can be eventually consistent. If you think about the old database world, there is the atomic consistency and the eventual consistency. So how you checkpoint, if you go into the -- how you checkpoint, et cetera, can -- it's a little bit more relaxed. The ONTAP platform is actually built for full consistency. Like this is about consistent data. So we are also looking at where needed, tune it or provide that offering so that customers can leverage those eventual consistency, a different checkpoint need.
Over time, I think as years go by, maybe quarters go by, I would -- my sense is and I think this is what the industry expects is, more and more of this will move towards inference. It's only so much you want to train models. And these models are changing on a -- every other day models are changing and there's a lot of money with the big players actually training models. So it's going to be more inference. We want to be and we are ready for that world where customers want to infer on the data that they have. So that's -- so it's a two-pronged one but I'm seeing more opportunity on the inference side of it rather than the training.
All right. Any more questions from anyone?
So I have one question for you because it's a question I get from these guys all the time and I'm surprised it hasn't come up. But as you mentioned earlier, we see a lot of investment of AI on the compute side. And we all know that data is important to make AI valuable. Why haven't we seen a commensurate investment in storage so far? And what do you think would drive that?
I think it is a -- it's just timing. One, in the context of -- look, if you look at -- I don't know which analyst, AI-defined storage and AI is at the peak of the hype cycle, right? As more and more production workloads go into -- start executing and become live, you will see -- we'll see a lot more importance of data and storage. And it is not going to be purely a capacity game. It's going to be about that balance between performance and capacity. I would expect to start seeing that. And this is why the timing is right for us at NetApp in terms of what we are delivering. Look, we -- this is the right time to actually have AFX, AIDE. And we -- like Sandeep is here, my colleague, we are going to go after customers and talk to customers and showcase this value and get great wins. So I'm super excited. It is going to happen.
All right. Well, that's a great note to end on. Thank you very much for your time.
Thank you. Thank you, everybody.
All right. So thanks, everyone, for your questions. So our next presenter is new to you. He's not presented to the financial community before. He's -- but he's been with NetApp for several years now, 3, several, that's right. Okay. So Gagan Gulati, he heads up our value services and he's here to talk and focus primarily on cyber resilience. So with that, I'll introduce him and then let him say a few remarks and then you guys can open up with questions.
All right. Perfect. My name is Gagan Gulati. I'm the SVP and GM for our Data Services group. And as Kris mentioned, today, I'm going to talk mostly about -- today, I'm going to talk mostly -- oh, there is a mic outside. Okay. Today, I'm going to talk mostly about cyber resilience and the -- and what we're doing there. I want to talk about a few things that we are introducing and working on. First is Secure by design. NetApp, we believe, is the most secure storage on the planet. And we have been working extensively to keep it that way. In the Secure by design category, I wanted -- we announced a bunch of new capabilities around post-quantum cryptography. So that's pretty cool and our customers are loving it already.
Second big thing, over the last couple of years, we have worked extensively on a piece of capability that's built into ONTAP called ARP or Autonomous Ransomware Protection with AI models built in. It provides our customers with real-time built-in capability for anomaly detection and it can, with 99% plus accuracy, detect ransomware attacks and then take snapshots as need be and then inform -- alert the security operations team about these alerts. It's been a functionality that's -- and capability that's growing rapidly. It's the fastest-growing feature that has been consumed by our customers today. And what we have delivered recently and we announced is that this ARP AI capability is now available for all of NetApp data estate, whether it's for the file workloads, block workloads, including cloud. So we have also announced this capability working with AWS for FSx and we're bringing it everywhere. So the ARP AI portfolio continues to grow and it is helping our customers secure their data estate against the biggest problem they have today, which is cyberattacks. That's #2.
Third, ransomware resilience. So we are bringing to light a brand-new service, a value service on top of our ONTAP platform that we call as the Ransomware Resilience service. This Ransomware Resilience service, we are introducing 2 big capabilities today. Again, the first in the industry to deliver what we call as data breach detection capability. Most of you guys know that when it comes to cyberattacks, the world is moving or the attackers are moving towards what they call as double extortion attacks. They will first make a copy of your data, export it. And then they will encrypt the data and then charge you ransom for both of them, one for decrypting the key, right and one for the data that's exported and they'll say, oh, we'll give it back but they may never give it back, right and use it and harvest it later.
So what we are announcing today is the ability for our Ransomware Resilience service to help our customers with this capability that we can actually go and detect data breach attacks. And we, of course, do it in real time, not after. We do it as it is happening. As we detect these attacks, we will generate alerts. We work with our own UEBA or user entity behavior analytics tools. We work with our partner companies who do network firewalls. And we, of course, integrate with the likes of Cisco Splunk, with which -- with whom we are announcing a pretty big capability, where we are working with Cisco Splunk SIEM and also their SOAR capabilities, which is security orchestration and response capabilities, so there is bidirectional work. So that's a amazing set of capabilities that we are announcing today with Ransomware Resilience. That's #1.
The second big capability we are announcing that our customers have been asking us for is what we call as the isolated recovery environments. As you know, when these attacks happen, there is no guarantee that when you're using -- when you are recovering from them, the backup copy from which you are recovering is safe. Studies show that 75% of customers who have a ransomware attack end up getting attacked again. And 1/3 of them actually by the same attacker. Why? Because when you recover these -- recover from these attacks, the copy that you're using is already malware infected because the attackers have affected -- attack -- they have affected not only your primary copy but also your backup copy.
So what we are delivering today is this ability to be able to recover from these attacks with confidence because we take the -- we run all kinds of malware detection, virus detection, all of our strength of data science on these backup copies and snapshots to make sure that when we recover them in an isolated environment, these snapshots and these backups are safe and these are not infected. So that's the second big capability we are delivering as part of the Ransomware Resilience service.
Now shifting focus away from capabilities to where we are taking our premium value services. We are -- these capabilities are, of course, made part -- available as part of our ONTAP licensee, ONTAP One licensees but also something that we make available to our customers to purchase through marketplace. And that's one of the areas we are very focused on to make it easy for our customers, our partners, to purchase these directly from the marketplace, hyperscaler marketplaces like AWS, Azure and Google. And what we're also announcing today and tomorrow is this new Ransomware Resilience service. We want all our customers to use it and we are announcing a trial, 6 months trial of this service for free for all of our customers up to a particular limit. And we hope that all our customers utilize the power of Ransomware Resilience against their NetApp data estate with this capability.
So with that, I'm going to stop and take questions from you. Thank you.
Frederick Gooding with William Blair. I'm curious how should we think about this ongoing convergence between storage, DSPM and like backup and recovery, you guys just announcing the isolated environments. I'm curious, like do you think it's more of, all right, we need to consolidate everything together like on top of the storage environment, we need the recovery, we need the backup, we need the data classification? Or is it more building interoperability with all those different types of capabilities?
It's a great question. So look, I mean, security is best done in depth, right? What I mean by that is every customer of ours, when they have to protect themselves against these cyberattacks, right, they start from the top, network security, perimeter security, so you have a bunch of firewall implementations that you have to have to make sure that you are protecting against network attacks. You also have to make sure that you have identity security so that compromised -- at end of the day, it's the compromised users and those identities that get used everywhere, right? And #3, then is about data security because end of the day, it's about those crown jewels. And this data sits on storage, right? And storage, therefore, becomes the last line of defense when everything goes wrong. But it doesn't mean that you only implement that at a storage level. You just can't have data protection done at storage level, security at storage level. You have to make sure that you are securing all different layers of the stack, if you want to call that. So that's #1.
#2 is -- it -- and it takes a village, right? To the example you gave, data classification, super important to get right. So you know what's sensitive and what's not sensitive. What's sensitive is what you want to prioritize and go protect first. At NetApp, we offer a capability called NetApp classification that makes -- that we -- that allows our customers to classify data. But at the same time, we work with various different classification vendors, DSPM vendors today to make sure that they can efficiently run data classification and security from an example of a DSPM or similar other examples like DLP, on top of the data that is available on NetApp storage. Of course, they can do it in the most generic way like NFS protocols, just files or they can utilize the best of what NetApp offers in terms of our own data management capabilities and they can integrate directly with us. So DSPM, DLP vendors, that's just one part of the picture.
The second part of the picture, of course, is data protection vendors. And the entire ecosystem, whether it's the likes of Rubrik, CommVault, Cohesity and others, right? So they -- at the same time, same story there. We want to make sure that our customers get the best data protection, the best cyber resilience. So we work very closely with data protection vendors and ISVs as well to make sure that the whole partnership utilizes the best of data management from NetApp so that the customers get the best defense against such attacks. So it's going to be -- it's a -- we, of course, want to make sure that we offer the best we can offer to our customers. But at the same time, we have an entire partner ecosystem that make -- together, we help our customers secure their data and keep them resilient.
So maybe just going back to -- and you referenced this a bit -- Samik, JPMorgan. If you can talk about, firstly, what's the current solution that enterprises are using? And when you sort of think about competitors in this field, who are you going to look to really displace on that front? When you're charging it as more of a premium service, how do you sort of envision that going? And then would you -- would this -- you said sort of you want to do it more in depth and probably the competition is where it's more going with the breadth rather than the depth on that front. But would you evaluate in the future like going and doing this on a different storage platform or a third-party vendor storage platform? Obviously, that won't give you the depth that you're looking for but is that something that gets you more into that pure-play competing in that area.
That's a great question. Look, #1, we -- our first and biggest job is to drive preference for NetApp storage. So it's -- for us, it's about making sure that our customers who have their most crown -- biggest crown jewels, their biggest workloads running on NetApp storage are safe. So we are basically, therefore, building both of the platform to allow for the -- our entire ecosystem to integrate with us. But at the same time, building vertical products, like you said, to make sure that we give our customers the ability to do it in the best possible way because we -- our products like Ransomware Resilience service is going to always use the latest and greatest of what we can offer from ONTAP layer and then, of course, go and deliver a new set of capabilities that we, of course, want our partners to integrate with over a period of time as well. End of the day, it's a dual job in that sense. So that's part one.
Second, about the breadth play. We are very focused on helping our customers with where they want us to help them. We have certain products in our portfolio that go beyond just the data available in NetApp storage. For example, our observability solution, which is DII, that helps our customers with observing and monitoring their entire stack because that makes sense over there, right? And it's just not focused only on NetApp storage. We -- of course, as part of the road map, we depend on what our customers tell us and ask us to do and we will continue to evaluate. But again, our preference is making sure -- our first rule of the game is to help sure -- make sure that we keep our customers' data on NetApp safe and secure.
Tim Long at Barclays. Two as well, if I could. First, just curious if you could talk a little bit about like the solution you gave the example of working with Cisco and Splunk and some firewall. Just talk a little bit about kind of what's the NetApp IP in this solution and what's the partner IP in the solution? And then shifting to the -- you may have answered part of this, but shifting to the -- shifting over to the hyperscale storefront model. Is this kind of the first major add-on of security to that offering and was there kind of an ask for this? And similar to other cloud offerings, was there a level of co-development with the hyperscale partners.
Okay. Sounds good. So let's start with the first part, which is the partnership we have with Cisco Splunk and what are we doing there. See, end of the day, when you look at the security tooling like what Cisco Splunk offers. It's about ensuring that the infrastructure players like us delivered the right set of alerts into the SIM and source solutions so that the security operations operator on the other side is able to take action, right? So the IP here is basically detecting these anomalies that there is an attack going on in real time. It is built into ONTAP and then making sure that we deliver extremely high-quality alerts into the scene, right? So that's the first of our IP. Just to kind of cover that conversation fully, ARP/AI, the capability we're talking about, has been independently tested by multiple different security labs across the globe.
SE Labs that's based out of London announced us as the winner this year for enterprise data protection category for -- and gave us a AAA rating at first count -- at the first testing count. So it's absolutely amazing. This capability is top notch. So that's part of our IP.
Of course, when we deliver these alerts into Cisco Splunk similarly in other similar solutions like Microsoft Sentinel and others. It's not just about the alert, it's about sending a lot more data along with the alert to make sure that the security operator on the other side is able to take action, right? And so that's basically all part of that IP.
Of course, security operator on the other side can then come back and start working with the storage admins to see where the -- what needs to happen next. As part of the latest integration that we did with Cisco Splunk. We've actually went the next step with data breach detection, which is not only do we send the alert over to Cisco Splunk. We also now allow the security operator to block the user from going and making -- causing further damage, right? So we allow -- this capability is now built into Cisco Splunk. So that's part two of the security innovation and IP that we are sending, which is who is this actual user, who's the user, who's making -- who's exfiltrating data, right? And then working closely with the Splunk team to make sure that the security operator can block the user right away and therefore, not cause further damage. So that's an example of the IP that we create and then, of course, we work with the entire ecosecurity ecosystem wherever we can to deliver the capability that our customers demand of us actually at this point.
Coming to working with the hyperscalers. Absolutely, right? So not only -- so all of these services like the ransomware resilience service or the NetApp backup and recovery service, which is well used by our customers. These services are SaaS services, right? And the control plane is hosted in hyperscalers, and they're available through the marketplace. So of course, we work very closely with our hyperscaler friends to make sure that these services run the most optimally. And at the same time, when our customers purchase these services through marketplace, whether go through the pay go model or a private offer model or whatever models their hyperscalers enable, we take part in that. We make sure that we make it available to our customers with all the innovations that those guys are driving a lot more from coating and pricing perspective and ensuring that the customers can, therefore, utilize their existing hyperscaler commits using these services.
So that's a lot of the work we do with our hyperscaler marketplace teams there. And last not we -- of course, these services not only run against our storage that's in customers' data centers, but also our customer that -- the story is that we have natively built in all 3 hyperscaler clouds and our CVO offering. So these services basically -- of course, we innovate with our hyperscaler partners there as well.
Wamsi Mohan, Bank of America. So right up the top, you mentioned something about designing for Quantum -- and I was just curious, like, are you actually finding customers at this point worried about this? How true of a worry is it at the moment? And is this sort of a future proofing? And what exactly are you doing here to achieve that?
Fantastic question. Look the threat essentially or the risk that our customers want to mitigate today is basically harvest now and decrypt later, right? That's as simple as that, which is I have -- if I can go and steal your data now, even if it's encrypted with today's algorithms, it's all right. Later, I'm going to come and decrypt it when I have quantum computing because now you can actually go and decrypt all of this data and charge a lot more essentially. That's basically the threat. And we hear about quantum computing coming up and improving. It's not viable yet, as you all know, but it's going to happen.
So what's happening right now, therefore, is multiple different government agencies, of course, are starting to put in new standards for computing and -- or in cryptography. For example, AES 256 is an example of an encryption technology that we just have built in now at rest, and we encourage our customers to start using that instead of a previous encryption algorithm, which is not quantum safe, right? And as more and more standards come into play, our job is to ensure that our operating system ONTAP is fully capable of encrypting customers' data with that algorithm of their choice, right, and continue to basically grow into that journey. So that's our job.
Our job is to make sure that ONTAP is always at the pinnacle in terms of the standards, in terms of the encryption algorithms that we have to make available to our customers. And therefore, that's what we do. And our customers job is to make sure that they utilize those encryption algorithms on their journey. And to answer your other part, our customers demanding this? Absolutely yes. right? And that's why we -- all of these innovations coming in because some of the biggest customers, financial institutions, specifically and others, those are the ones who are demanding that we continue to improve, and we will always be, I believe, ahead of the game as the most secure storage.
Frederick Gooding, William Blair. I'm curious in terms of how important securing metadata is? And then also, if we look out over the next 3 to 5 years as AI becomes now more important, more integrated within the enterprise. And Kris might tell me to shut up here. But I guess where do you share the future gaps that are within the NetApp portfolio in terms of securing in what you guys are maybe looking at down the road?
Well, definitely not the future gaps, but maybe some opportunities to continue to enhance our platform.
I believe that -- we've already talked about AI data engine.
Yes. Okay. That got announced this morning.
Yes. We announced it earlier this morning, and we just ran a session before this about AI data engine. I mean, look, like you said, right, the AI journey is just starting. I mean customers are moving from AI pilots -- enterprise AI pilots, I mean, enterprise customers towards taking these projects to completion. And we all know, we've all been in the industry long enough to know that overall, the AI-ready data doesn't exist, and I think that's where most of our customers are and what they're trying to do right now is to start just cataloging data, which is basically starting to put the whole metadata together for all of their data so that it's easy for our -- they can make it easy for their data scientists and engineers to utilize it.
Of course, Metadata, you can actually infer a lot from Metadata about the actual data, whether it's file name to the various attributes who's changing it, what have you done with it, the tags, et cetera. So there's a lot you can inform from metadata. And the metadata store, there for the catalog, needs to have the same level of security that the actual data has, right? So you have to make sure that your metadata store, your catalog has to be safe. It has to be -- it has to -- to make sure that only the right people can get access to it, not just -- not at the level of users, like which user can access what part of the metadata to find and access the data they want, but the actual metadata store that's on NetApp storage, we have to make sure that it's as secure or probably even more secure than the actual data is. So that's part of our job. And it's not like a gap. It's something that we actually do today. What we ship today is part of the functionality. So of course, we'll keep improving as customers tell us more. But for us, that metadata is actually end of the day nothing but data, right? It's customers' data that we have to just secure as well as we secure the actual data.
All right. Well, I'll ask one last question because I think while you've been focused on cyber resiliency here because we've had some cool announcements today, I think we have a number of premium value services available today through the marketplace. And this audience probably is less familiar with them. So it might be good to explain what they are, how they work in customer environments and how we deliver them.
Oh, that's perfect. So yes, so there's a lot -- so what -- so when you talk about premium value services, we are delivering end-to-end orchestrated SaaS-based services to our customers in 3 big categories. And all of these services are available to our customers through marketplace or a typical licensing model as well. The first one is around cyber resilience, that the one I talked about. And we delivered 3 big services, Ransomware resilient service that I mentioned already, with a lot of great capability that we are working towards. Number two is our unified backup and recovery service. This service is used by hundreds of our customers to go and back up their data and then recover that when need be. This service has been in existence for a few years, and it's available through marketplace, and it's a well -- very well used service. The third big service in the cyber resilience portfolio is our disaster recovery service, which helps our customers protect their VMware-based workloads, so they can have orchestrated disaster recovery from on-premises data centers to on-premises data centers.
And we are the first ones who actually have made it available such that they can do a DR of their VMware-based workloads from on-premises to AWS. So you could have a workload running on premises. And if your DR strategy says that I want to actually have my second secondary site running in AWS, no problem. We actually work with our AWS team, and we were the first, ISV if you want to call it, to have -- make this functionality available to our customers. So that's the third big piece of the puzzle in cyber resiliency that orchestrated end-to-end services that we make available to our customers. So that's the first pillar.
The second big pillar for us, of course, is AI. What we announced today with AI data engine. And that is also going to be available to our customers through marketplace. So that's second big pillar, and we are working towards that.
The third big pillar for us is what we call as governance. And what we have available today there is a very well-used service called DII. And this service is also, again, available to our customers through marketplace so that they can use this SaaS-based services for observing their entire environment. And I think to the question that was asked earlier, this service goes beyond just NetApp storage and gives us -- our customers the monitoring and observability capabilities for their entire environment. So 3 big buckets of marketplace-based SaaS services. in cyber resilience, in AI and also, last but not the least, in the field of governance, and we're starting with storage governance and infrastructure governance and over a period of time, we'll do more. So those are the 3 big pillars that we have over there.
All right. Any final questions in the audience? Well, I appreciate your time very much today. Thank you so much for your debut voyage with us. All right.
Okay. So our next speaker. You guys have all heard from before Sandeep Singh. He is the SVP of Enterprise Storage. So all of your flash block and probably AI questions. We'll send them his way.
All right. Hello, everybody. As Kris mentioned, I'm the SVP and General Manager for enterprise storage. I've been part of NetApp for 3 years, and my background is predominantly in enterprise storage. I was part of a startup a long time ago called 3PAR and I led product there from pre-revenue to well over $1 billion post acquisition by Hewlett-Packard at the times. I was also part of Pure Storage for almost 5 years, helping Pure scale from less than $50 million in revenue to well over $1 billion. And then prior to joining NetApp, I was leading product at HPE Storage. Look, across the board, when we speak to customers and over the last 3 years, I've just had the tremendous opportunity to speak to hundreds and hundreds of customers globally. And they have struggled with having to support just a plethora of workloads. AI is now the newest latest greatest addition to that. But when you think about workloads in a typical modern enterprise, you're going to find high-performance files, whether that's AI or, for example, EDA workload or media and entertainment type of workloads. You're going to find virtualization, you're going to find databases, containers. You're going to find much more of the capacity flash more general purpose and test dev type of workloads. You're also going to find secondary workloads, whether it's backup or CyberVault those types of scenarios.
And customers have to struggle with how do I ultimately provide the best infrastructure to support the plethora of these workloads. Their data is also spread across on-prem and public cloud. And they want that flexibility to be able to get the right balance of workloads across on-premises and cloud and be able to do that seamlessly. So when we hear about customers and their challenges, one of the critical challenges to that is just ever present is complexity. And as soon as you double-click into that, that complexity just exponentially expands with all of the infrastructure silos. That's part 1. Part 2 associated with that is that everyone in IT has talent shortages as well as talent and skilled gaps. The number 3 is they want to be able to seamlessly leverage the agility of public cloud and be able to have that flexibility of on-prem and cloud. Number four, what Gagan was just talking about in terms of cybersecurity. Ultimately, the last line of defense becomes storage as that last line of defense. And it becomes incumbent on the IT leaders to have the most secure storage. But that is a top C-suite priority across the board.
And of course, what you've heard a lot about today, everyone is looking at how do they sees an AI advantage? And how does that become a game changer for them. Common thread across all of this is fundamentally data. The data fuels the overall workloads for our customers and data is the fuel for AI. So when we look at the opportunity and how we can be that strategic partner to customers, it begins with the storage infrastructure, but very quickly it is about data. And this is where fundamentally what we have done over the decades is invested in building a data platform for customers having that right foundation that data platform is so critical. They need to be thoughtful and mindful of building a unified data foundation to be able to get rid of the infrastructure silos. When they have infrastructure silos, complexity abounds. There's the inconsistent management, there's inconsistent automation. There's inconsistent data security models and the weakest link becomes the exposure window. There's inconsistent operational recovery workflows and then overall in consistent experience across the board.
So first step really becomes building that unified data foundation, and this is where we have built this unified enterprise-grade data platform. So the customers can collapse silos. They get consistent management, consistent automation. This way, they don't have to worry about the talent gaps and having to reautomate. They get one consistent experience for the data security model. They get consistent operational recovery workflows, and they get consistent on-prem and cloud experience. That becomes a step 1.
What we've also done is we have a fully refreshed comprehensive industry-leading end-to-end overall portfolio of our data storage products. It spans the high-performance flash and capacity flash and hybrid flash, so that customers can leverage that no matter what the use case, what the price point, what the performance levels and be able to leverage it for the breadth of these application workloads that are about empowering their internal innovators. We are a top leader in flash across the board.
Our portfolio is also fully interoperable. So what that means is they're collapsing silos, they're also seamlessly able to get the lowest cost of data over the life cycle. In the data world, there's such a thing as hot application data and then cold data. And we give customers that complete flexibility with this automated granular tiering built in, where the cold data can be automatically tiered on-prem to on-prem as well as on-prem to cloud as well. And what -- everything that Gagan was just talking about, where we have the data management tied into the application workloads. So this is where -- whether you're running virtualization or database applications and you want to get application consistent backup copies and maintain those library point-in-time copies for recovery that is application consistent, so you can sleep better at night. That is built in.
That's through our Snap center customers love that capability across the board. We also invest in full integration into the top workloads so that customers, including the administrators at the workload level are just able to seamlessly consume the underlying infrastructure end-to-end. And then with our announcements today on AI and how we are unlocking the value with the combination of NetApp AFX. It's enterprise-grade disaggregated storage that just delivers extreme performance, massive linear scale, and it is NVIDIA Superpod certified, including with DGX GB300.
That enables customers for deploying their AI factories built on NetApp AFX. And then the AI data engine that pairs with AFX that enables customers to be able to deploy a full AI data pipeline that is secure and that is efficient. It comes with the integrated data discovery, data curation, data guardrails as well as the full vectorization and the vector embeddings for Gen AI applications, all built in. It makes it super simple for customers to be able to go and build an end-to-end AI data pipeline. And what we have also done is we full well recognize that enterprises are going to have AI at different levels of maturity within their organizations.
Some are in POC stages, some will be in deployment stages. We're simplifying this end-to-end. All of this value of NetApp AFX, combined with NetApp AI data engine, we're also making this available as a service with NetApp Keystone. So whether the customers are in POC stage or production deployment stage, they get that complete flexibility of being able to adopt all of the net enterprise AI value that we're unveiling and they get to do that as a service and then be able to scale seamlessly as their AI initiatives grow.
With that, I will open it up.
Ananda, in the back.
Yes, Ananda Baruah, Loop Capital. That was a lot of great detail. As folks begin to deploy AI applications or features, AI features inside of existing applications. So moving proof of concepts into production and actually, if they even have to do this for proof of concepts like let us know. Do you see them doing incremental spend, storage spend along that journey for those AI applications? Or do you see them phasing in the AI applications and making purchasing decisions along refresh cycle lines? And then I have a quick follow-up, too.
Yes. Look, in terms of the AI spend, it's fast evolving. The overall AI technology is fast evolving. Organizations on how they are deploying it is also fast evolving. A lot of the enterprises are forming AI centers of excellence, where they will formalize the best practices. They will also have shared infrastructure as part of that center of excellence. So for some, it's a matter of adding AI for others, it's a matter of building out net new AI initiatives. What our vision is and the -- what we are enabling for our customers is that AI should not be another silo because silos continue to propagate the complexity and customers need not only the performance and scale for AI. They need all of the enterprise-grade capabilities. They need all of that flexibility of hybrid and multi-cloud. And of course, security has to be just built in. So what we've enabled customers to do is basically be able to leverage it and be able to leverage it as just another workload along with everything else there. So they may start as part of building out dedicated infrastructure very quickly, it becomes part of the overall infrastructure.
And just as a quick follow-up, you actually begin to touch on it. So the point about increased complexity, I just want to ask and if the answer is no, please say no because -- but is there anything about AI in the complexity conversation that pushes organizational -- the organizational data management paradigm over any sort of tipping point such that the addition of the AI to the paradigm almost necessitates something like simplification. And just because you're here, I thought to ask the question, but I don't want to leave the witness and that's it.
Look, in the AI world, first of all, you have to recognize that within an organization, you have multiple different personas that are part of that journey. You've got the data engineer, you've got the data scientists, you've got the AI developers. You have the IT teams that are beginning to be part of that conversation. And then clearly, there's AI frameworks and tools and infrastructure that is even outside the enterprise. Obviously, there is a ton in the public cloud there, and you now have newer AI factories that are emerging as well. So ultimately, for customers, what they have to think about is, firstly, how do I actually get the data AI ready. That's really that first step of the journey because data becomes the fuel for AI and for enterprises, unlike the consumer AI for enterprises really AI needs to be informed with the context of their data. So that's kind of the important first step for getting their data AI ready.
The next question really becomes in terms of how do I get my data from where it is to where the GPUs live and be able to do that while preserving all of the security permissions without propagating a plethora of copies because as soon as you make copies, you lose the data lineage and you've also lost the context of security there. So we have technologies, for example, our FlexCache technology and/or our SnapMirror technology that enables customers to just seamlessly be able to make their data accessible to AI and do that in the context of preserving all of their security permissions without making copies there. Then when you think about the overall data pipeline that customers ultimately at the data scientist level are having to go and stitch together.
That becomes essentially this notion of there are multiple fragmented tool sets and along those tools, there are multiple copies that are being generated. Often, we hear about this challenge that I articulate as data bloat where customers are complaining about my data is multiplying 10x or 20x especially during that overall vectorization process. What that means fundamentally is if that problem isn't solved for them it becomes incredibly costly for them to go and deploy AI at scale. What we have done is simplify this end-to-end AI data pipeline with that AI data engine.
And we have built in our own technology to go and build a super efficient overall vector embeddings to help customers avoid the data bloat challenge. We've also partnered closely with NVIDIA in integrating in their overall NIMs technology into this AI data engine. So -- and one last step, we're also investing in the integration with our public cloud partners. And so that the customers' data, not only can we make it seamlessly accessible into the cloud, but we can seamlessly integrate it and stitch it in to all of the AI frameworks and tools that are being invested in the public cloud. So that's how we're looking at this in terms of just simplifying this end-to-end.
You also heard George on the keynote stage, talk about ultimately this whole notion of metadata fabric and a knowledge graph because when you fast-forward AI. Ultimately, when you think about enterprise data, today, you've got basically a lot more of the LLM powered use cases, but tomorrow, the evolution is taking us to overall Agentic AI. And this whole notion of an enterprise's data set, curated, classified, protected and then made accessible through a knowledge graph become so critical for customers to then truly unlocking the power of agentic AI.
Lou?
Louis Miscioscia, Daiwa Capital Markets. Well, I haven't heard the words 3 part David's got quite a while. So there we go. But I see though, you seem like you've been with some great storage companies, so you have probably insight that many others might not. So what could NetApp do better given obviously that we always hear about the strength of the uniform operating system. But what could NetApp do better in the sense of why isn't it up, maybe not gain share fast enough in comparison to the other competitors being HPE, Pure or some of the other players out there?
Look, first of all, it starts with building a unified data foundation, and that experience is unmatched by a bar none in the industry. ONTAP is a gift that keeps giving. ONTAP has been matured over decades. And the level of power of unifying application workloads and serving that with a unified data plane coupled with a unified control plane is an unmatched experience across the industry. No one is able to deliver that. When others talk about unifying, they still have infrastructure silos. And that infrastructure silo means you might get some value for a given application workload, but you're still siloed within the boundaries of that given application workload.
As you go from either blocks to file to object, you end up segregated and that complete flexibility of a unified data foundation is that step #1. Step #2, Look, nobody in the industry has had the foresight and/or the level of integration that NetApp has done with our hyperscaler partners. This is giving customers this flexibility of I can rightsize, I can shift the workloads with that having to go and re-architect their application workloads. That's amazing for our customers and having that complete flexibility. And thirdly, when it comes down to when you think forward-looking, even present now, top of mind is cybersecurity and security being built in, right?
No one is able to match that game-changing technologies that Gagan was describing, it begins with that real-time ransom or detection where we can detect a ransomware attack within seconds to minutes unlike otherwise where it would typically happen in backup or secondary workloads, which is hours to days later. This means basically is very little amount of data is impacted before that attack is detected. We notify it in the scene. But then more importantly, we're able to go and create these temper-proof snapshots for rapid recovery, right? And everything that we were just talking about AI.
So when you think about, basically, look, we have a fully refreshed portfolio. We have a comprehensive unified enterprise-grade data platform. And we're evolving AI from another silo into just another application workload and giving customers that complete flexibility of not only just performance and scale, right? You've heard a lot from others in the industry about performance and scale. This is about delivering AI with performance and scale with enterprise-grade capabilities with overall the most secure storage and having that full hybrid multi-cloud.
Just a little bit of a follow-up. And if you want, you could brag a little bit. Which competitors would you think are the easiest ones to compete with and which are the ones that are a little more difficult?
Look, I won't go into specific competitors here, right? Fundamentally, it comes down to the IT leaders once they have this recognition of, I don't need to just refresh, I need to modernize because I need to be cyber resilient, I need to have my data AI-ready, I need to be able to enable the outcomes that are being demanded internal by internal customers across the board. As soon as that realization happens, very quickly, it comes back down to what is that right data foundation. And we're right there for our customers to be able to help them see and showcase how we can be that strategic partners to customers to overall modernize that their end-to-end infrastructure. So we look for how do we solve the customers burning pain points and how we can address them. And so long as we are doing them incredibly well and differentiated manner. That is what we're looking for.
All right. Then we'll get to you, Mehdi.
Steve Fox of Fox Advisors. I guess there's been a lot of talk from the company in the last few quarters about just having enterprises doing a lot of testing on new workloads, et cetera. You've laid out a path for how these workloads could be monetized a lot better. But I'm trying to understand the bottleneck here. Like when is NetApp going to start winning. Like is it one workload at an enterprise customer 5? Is it that they see that they try to pipeline it and they can't, like how is this going to play out so that you guys are ultimately successful?
Look, I would say, overall, we are a top leader in Flash. You've seen our continued growth in overall flash storage. That's just an overall trend as customers are continuing to modernize across the board when we look at the deployments that customers have on NetApp. You will find virtualization, database workloads, high-performance file workloads, secondary workloads. Those are so prevalent across our customer base. And our customer base spans all the way from the top most strategic, the largest of the largest enterprises, enterprises overall as well as a lot of the corporate and commercial accounts, and we span the gamut across the geos. And so we see the overall customers continuing to go and consolidate and unify their application workloads. And that's not only across on-prem, it's across on-prem and cloud.
I think your question is like how do we get into a customer? Like is it a single workload. There's a specific pain point that we address and then expand from there?
Yes. Look, from that perspective, there's multiple ways of addressing and how we land in customer account. But when you think about the journey for getting the data, AI ready and accelerating their AI initiatives, it begins with helping customers build a unified data foundation. The way they take advantage of that, that can be by landing a file workload, that can be with landing a block workload, that can be with landing an object workload, many of those application workloads that I talked about. That begins that journey for them. It evolves into customers then seamlessly extending to cloud or extending on-prem to as a service with our Keystone Storage as a Service offering. And then that evolves into essentially becoming cyber resilient all of the capabilities that are built in as well as the ransomware resilient service that Gagan was talking about. And then the final step turns into getting their data AI ready. It's not necessarily a sequential journey. But these are different paths, ultimately for onboarding and onto the NetApp data platform.
Mehdi Hosseini, Susquehanna. If I just as a follow-up to that and rephrasing the question. You're working on unified data lake, a unified data -- enterprise-grade storage, unified data foundation, unified data lake. There's a lot of stuff that you're doing and you're working with customers and the fact that FY '25 was a strong year for all-flash array gives you a tough compare. So perhaps all of these unification and new approaches and problem solving would manifest itself to some traction in FY '27 without asking you a specific financial question. I just -- we've been hearing of all these problem solving. We just -- we're kind of -- not desperately. We're trying to figure out how this puzzle is coming together. And it seems to me that it was more of a '27, so we're in the sixth inning.
Look, I won't comment on the financial side of it. Sam is here. Kris is here. They are much better equipped than I. What I can say is that we are laser focused on making sure: one, we fundamentally understand what are the burning pain points for our customers across the board; two, that we have and continue to enhance, but we have the best differentiated unified enterprise-grade data platform as that foundation for our customers; and thirdly, then just giving them all of the necessary capabilities, whether it's as a service offering on-prem or in the cloud or it is the necessary software capabilities or workload type capabilities to not only just accelerate and continue to simplify their existing workloads, but ultimately go and deploy AI.
I don't think competitors are doing any -- it's not like competitors are ahead of you. We're all in it together. But I think if I just like trying to think about what has happened over the past 12 months. And all the efforts you put in, we're in the sixth or maybe seventh inning in that journey, all the good things that you have done is now like -- it's not like we're still in the dark room trying to figure out where the door to the AI stardom is. We're getting close. Would you agree with that assessment?
I would say, look, I don't know about the innings, but I would say, look, the AI journey, especially enterprise AI. That journey is just getting started, right? We see forward-looking just tremendous opportunity of working with customers on their enterprise AI journey, and we're super excited about the innovations that we're bringing to market on that front.
All right. We have one final question from Samik.
Samik from JPMorgan. In terms of the conversations that you're having with customers related to AI, how much of a credit do you get if you are the installed supplier already? And is it like a fresh bakeoff between all the vendors on a feature by feature or do you get a credit for being the installed base? Just trying to figure out is having a large installed base of benefit in terms of when that bake-off happens. And then just given the AFX product just launched your experience with AI and sort of those conversations with customers, how much of a sort of time line do you think AFX takes in terms of customer education and adoption. How do you think about that?
Yes. Look, overall, when we think about AI, first of all, this is just a fast evolving space. The technology is evolving and the customer use cases continue to evolve -- what you used to hear a lot about in terms of the use case was that model training use case. But when you look at the enterprises, they very quickly realized, first of all, I can't spend hundreds of millions of dollars to go train the models. Secondly, with use cases that are shifting to inferencing and with the emergence of overall reasoning language models and test time compute scaling. The predominant use case in the enterprise will become a lot more about the inferencing use case overall.
So when we're speaking with customers, and we're -- we have, what, over 100 exabytes plus worth of overall customer data globally that we store. That gives us a -- that's a tremendous asset across the board because when you think about the challenges of when you have your data and if you're fundamentally making another copy and then continue to multiply it. Not only are you getting this data flow challenge, all of the security context is also being lost in all of those transformations. And this is where we see a tremendous opportunity. This is where we've had a number of customer conversations who have gone down the path with some upstarts where they've gone and looked at the performance and scale because that's all they had.
But they've been asking us where they need help is not just the performance and scale, but it needs to come along with having all the enterprise-grade capabilities having all of the hybrid cloud workflows because AI is inherently a hybrid workflow end-to-end for them and then having all of the security built in. So that is where we see a tremendous opportunity where we can help customers end the silos, and we can end the compromises for them. And they need to end those compromised in order to go deploy AI in production at scale for themselves.
All right. Thanks again, Sandeep. Really appreciate it. Now we have Pravjit Tiwana. He is the SVP of Cloud Storage and Services. So lots of exciting announcements there today and just ongoing interesting and great part of the business.
So with that, I'll hand it over.
Hi, everyone. As Kris introduced, I run Cloud Storage as well as open source technology stack at NetApp. When I say open source stack, I'm talking about our Instaclustr offerings. I can talk a little bit of 2 minutes brief into like all the portfolio we have and the kind of announcements which we are doing this week. In a nutshell, right, like our cloud storage and services portfolio include 3 things. On the very first is our first-party cloud storage offering. First party cloud storage of thing is where we are natively integrated into all the hyperscalers, all the 3 major hyperscalers, right? It's not like we have bolted on or something. This is like co-development, co-engineered capabilities, which we provide to our customers.
So right like we have integrated the engineering stack as well as a everything from billing to GTM to all those kind of capabilities, it provides unique differentiations, which are not otherwise possible if you're just porting it as -- simply just a marketplace offering or something, right.
And then the second aspect of our portfolio is our what we call as cloud volume ONTAP, that is basically a swiss army knife of all the ONTAP capabilities, which we provide in all 3 hyperscaler services. So first-party cloud storage is all about fully managed, no ops, right, like we manage it on behalf of the customer. CBO gives capability to customers where they can fine tune every single dial for their install of ONTAP in cloud, right, in all 3 hyperscalers.
It's very commonly used for like extension of your hybrid storage and those kind of capabilities, right? And the third aspect of it is what we have in our open source offerings like we provide managed Kafka to Postgres to Apache Cassandra to ClickHouse to Opensearch, all those as a managed offering for all the open source stack, right? Like the idea there being is right, like it provides you a true open stack to begin with and it also enables you to true multi-cloud, right? Like you can move your workload if you're running an open source stack from 1 hyperscaler to on-prem or to another hyperscalers, all those kind of things.
So those are the 3 main building blocks of our -- a lot of things go under them, a lot of capabilities get built on them. As far as focus is concerned, right, like our focus recently has been on a few aspects, right? The first and foremost is to bring AI to the data. So we are the only cloud storage vendor out there who are natively integrated into all the hyperscalers, AI and analytics stack, right?
Like if you see on the AWS side, we are integrated with Bedrock, Q and all those capabilities. You don't have to move the data out to some S3 or anything or any object store. You can run your AI stack, right then and there, same way. And Azure, we are connected with their stack, around all the Azure AI search, AI studio, analytics and so on. Similarly, this week, you saw Google announcing Gemini enterprise. Same way we are integrated into Gemini enterprise side of the things also. Our second focus area is to bring all the ONTAP richness, which we have built over the last 30 years, be it in performance, security, cost optimization, all those kind of things over to cloud. So if we see, we have built tons and tons of capabilities this year across all 3 hyperscalers to bring that richness to our cloud offerings.
The third is like right, like in the end, customers buy us for workloads, which are basically our way of saying that, hey, those are the outcomes for which they buy our products. So we have -- we are not just only focused on the AI as a workload, but like especially we have grown by leaps and bounce in EDA, HPC, SAP, databases, VMware, those are the like some workloads where we have built rich capabilities so that there is no aspect of it which customer is missing.
Finally, we are also talking about, right, making how to make our offerings more and good for like especially for developers. So this year -- this week, we also announced Visual Studio code extensions. So now you can use basically chat kind of interface to do all the things which you do in hyperscaler, right? Like you can say, hey, provision by storage or do -- delete my volume, all those kind of capabilities, just as a chat interface, right from the IDE itself.
In fullness of time, we plan to extend into other IDEs, but we started with Visual Studio. I'll just -- before taking questions, I'll just talk about a few numbers. Our cloud storage has been growing by almost 50% year-over-year. We are now 2.2 exabytes of storage in our open source Instaclustr offering, we do more than 20,000 to 21,000 managed units now on behalf of our customers. We have over 5,000 paying enterprise customers and growing at a very substantial rate year-over-year. One good thing about is like right, like our offerings in cloud. They are not just like only the ONTAP customers from on-prem who are migrating over to -- yes, there is a portion of that. But significantly, almost 2/3 of them are the new customers who are starting to use NetApp for the first type. So a lot of like -- I'm happy to take any questions about our capabilities, numbers, where we are heading, AI, anything -- no, the usage numbers, not the financial numbers. usage numbers I can talk about.
All right. Questions? Everyone's tired. Okay, Samik?
So maybe -- and maybe it's slightly numbers oriented, but I'll sort of frame it this way. The first-party services, storage services grew really, as you said, like 50% plus or 30%, 40% the numbers are really strong. The rest of the business, which tends to have a lower growth rate on it seem like, overall, from our perspective looking in, the services that you provide outside of first-party stores seems to have a lower attach in terms of what enterprises are adopting on a public cloud. Maybe just get into some of the details there in terms of why outside of the first-party storage, there seems to be a lower growth rate for the other businesses? And is it something that needs to be addressed over time.
We are talking about our cloud businesses like CBO or are you comparing it with our on-prem businesses?
Cloud business, so DII and some of the other business.
Yes. So I don't have the size numbers top of my mind for DII. But on Instaclustr, we are seeing this almost similar kind of growth which we are seeing in our first-party cloud storage and the growth is -- it depends upon the hyperscalers, right? But the growth for our CBO product, which is like self-managed ONTAP is also in the similar lines. They might not be like exactly percentage to percentage MAX, but the growth rates are pretty substantial, which are -- we've had in the industry.
I'll just jump in and get you off the hot seat. Don't forget, we have a lot of services that we end of life demonetized, and we began that about 1.5 years ago. So there are some headwinds that you're seeing there. Almost through it, though. By the time we lap the spot divestiture, I think you'll see a cleaner cloud number on the report.
Tim Long at Barclays. Two, if I could. First, a few of the offerings kind of filled out where now you have every offering to GCP, Azure, AWS. So could you just talk about like filling in those holes, how meaningful do you think that would be to usage? And then the second, just curious with this -- you talked about 2/3s of the new customers are new to NetApp. What does that motion like? I mean, obviously, you're getting help from the hyperscalers pulling them in. But what's kind of their decision tree that they go through. There's probably a lot simpler decision if they're ONTAP on-prem. But how is that whole decision is at a little bit different?
No, thank you. I think let's start with your first question around right, like filling the capability gaps of completing our metrics and cloud, right, like what we have heard a lot from our customers is especially around workload consolidation, right? So the unified block and file offering which we provide, which is -- which is available in on-prem, but now also available in our cloud sources that is one of the unique differentiators why customers start using our capabilities because now earlier if you remember, we started our journey with file storage in our 3 hyperscalers, but now we have brought File Plus Block and customers want to use their workloads in a unified way, right? Like you don't want -- they don't want to use one vendor for something, another for another, it simplifies things, right? And I think the other aspect is, right, like if you see 30 years' history of NetApp, right, like we have built array of data management capabilities, right, like it's things like Snapshot, SnapMirror, all those. Those capabilities are now becoming really, really useful for our cloud customers also right? Like if you are, say, in FSxN,right, like you want to do multi-AZ or multi-region kind of a set up right, like you can then use it with SnapMirror and set it up those lines.
So the second aspect of it is, right, like filling the gap aspects of all things around getting the switch data management capabilities, which we have. The third aspect is, right, like if you see -- over the years, we have built a lot of capabilities, especially in our price and performance optimization, right, like deduplication, right, compaction, compression, all those -- we have brought all those capabilities into the cloud also, right? Like I was looking into the numbers, right, like if you're using our block storage, say, in the cloud, you get almost 4 to 5x data efficiency because of the capabilities which we have built over the year, which brings a unique differentiation, right?
Then the performance work which we have done around, be it around very high AIOps and so on, right, like that also is now available in the cloud, right? And the more important thing is, right, like if you're a customer who are using NetApp or anything on-prem, right? Like if you even move to any of our cloud offerings, like be it AWS, Google or Azure, you don't have to refactor your applications, right? You don't have to rewrite those, right?
All those things fill in the gaps and provide up much differentiated offering than others. And there was a second part of your question.
Was the decision tree for the....
Yes, yes. We also have been understanding and learning this thing over the years as the services has been growing, right? One thing is becoming little clear to us, right like hey, customers don't choose based on just on like, hey, what is the logo of the vendor who is providing it, right? They look deeply into right, like what problems of theirs are being solved, right? So from that perspective, right, like as I was saying, right, like tens of years of data management capabilities, which we have built, they really resonate with our customers, right? Like same way, all the things which we have done around ONTAP innovation over the years and bringing them to cloud, that also resonates with our customers, like same way, all the things which we have done around ONTAP innovation over the years and bringing them to cloud, that also resonates with our customers. Unified is one of our -- one of the most differentiating aspect which we have with file, and whenever either an app developer or IT admin or those people are looking into that, they always look into those capabilities to figure out. And the fact that we are natively available inside console, the SDKs, the APIs, the CLS, all those aspects of our hyperscalers, it becomes easy to find and discover also. And when once you start building an app or whatever you are building, you find the richness of our capabilities and that attract them to start using us more and more.
And roughly, it's 55% of our new logos are -- of our logos are new to NetApp in cloud.
All right. More questions?
We also announced this week a few of the capabilities I can talk about from GCNV block to our data migration capabilities and also all the AI integrations, which we have now with each hyperscaler, these are unique and differentiated from all aspects.
It would be great to cover those and really talk about like why does that matter to customers?
Yes. I think the -- so let's talk about the AI part first. Why we took this unique approach is because customers are telling all the time that they -- the biggest problem they are having with building their AI flows is, when they have to copy the data over to multiple places. It breaks the whole security, cost, all those aspects. So from that perspective, that's why we went ahead and did native integrations with hyperscaler AI stacks. So -- and we had these capabilities like SnapMirror and FlexCache available in on-prem, now also available across all 3 hyperscalers, which make it really, really easy for our customers.
Same way on the Instaclustr side of the things, our customers told us that, hey, they want a real alternative in open-source world for the complete Gen AI infrastructure. So that's why if you see in our Instaclustr offering, we have capabilities like from post test-based, vector DB, to complete OpenSearch, to soon to be coming NCP gateway. So the idea being that, hey, you don't have to stitch all those pieces together. You can orchestrate it from a one layer. You can move it between on-prem and cloud. So that capability of, hey, you have a real multi-cloud play, you don't have a vendor lock-in, and it is open, it is cost optimized. All those things basically is exciting for our customers. That's on the AI side of the things.
And the block side, as I was saying, the biggest differentiator has been the unified, the data management capabilities, price performance optimizations and familiarity with using our stack on-prem and bringing into the cloud.
We also announced this week a capability called data migrator. What we have seen is that even if we have beautiful castle in our hyperscaler where we still need a free way to get people to that castle. So that's why we build a NetApp data migrator where you can pick up any of the NFS or SMB file shares and basically can get your data into the cloud. We are the only vendor who are providing it without any cost and with a high consistency in terms of checksums and those kind of capabilities.
All right. Ananda?
Yes, Ananda Baruah with Loop Capital. Do you see any potential for -- as -- for an AI -- sort of an on-prem AI catalyst for any aspect of the cloud business? And as a specific, for instance, as corporate customers begin to look to do more, say, model training on the cloud before they pull it back on-prem to go live in production, something like that, I guess, would be, for instance, but that or anything like that as a potential cloud catalyst that we all might see show up in the business?
To be honest, AI is not possible without cloud. But AI is also one of the truly hybrid workflows out there. It's hybrid, it's multi-cloud. So we are seeing a lot of these patterns. We are seeing a pattern where somebody just uses only in cloud, they will either hook up to their FSxN to say, Bedrock or Q or something, or similar things in Azure and Google. Then there are like, hey, who start their training into enterprise and then they take the whole next set of -- from inferencing and all those, and they take it to the cloud. And then there are some who are in between. So I think the journey is still early, for many enterprises to have production grade AI applications, but we are seeing all flavors of them, and that's where we are uniquely shining.
All right. Say it into the mic.
Yes, yes. Quick follow-up on this. That was helpful. I think Sandeep talked about neo cloud opportunity or something beginning to pop up in the neo clouds? And I guess the question is, as we're seeing more of your hyperscale partners move workloads into the neo clouds. And it seems like it's happening at scale. It's going to happen at bigger scale, it seems like in the coming years. Does -- do you have opportunity there with those AI workloads that go into the neo clouds from the hyperscalers?
No, that's a good question. We are also right -- there are two aspects here. One is the neo cloud and another is sovereign clouds. Let me quickly answer the sovereign one because that's an easy one to say, because even by analyst estimates and all, 70% or more of the sovereign workloads are running in the cloud. And we are good there because we are available in all 130-plus regions. There is no actually storage vendor or any vendor who is available in that many regions, not even hyperscalers because we are a sum total of all 3 hyperscalers. And we are also available in all gov clouds, the European sovereign region, all those top secret clouds, all those places we are. So for our sovereign, we are very, very well covered.
When it comes to neo cloud, so one of the unique things which we have built over the years is, right, like we have our hardware-based offerings inside hyperscalers, but we also have software defined storage layers, what we have done with AWS as well as what we are doing with Google and eventually with Microsoft also. Those are the capabilities which are very capable to be applied to any kind of cloud, be it neo cloud or hyperscale cloud.
And where we will bring the unique differentiation is because we are already have first-party storage services inside the hyperscalers. We can federate a lot of those workloads to work between neo clouds and the hyperscale cloud. So we are looking into, as Sandeep said, we are looking and evaluating all those opportunities and seeing, what customers really want. We don't want to build something because it's cool to build that. We really want to have like work backward from what customers are asking it, work with customers to build those kind of capabilities.
Wamsi Mohan, Bank of America. I guess a couple of quick ones. One is how do you decide around investing for the cloud opportunity in the sense that you obviously started at Azure and you all mentioned the hardware component over there? But it sounded like maybe you will have a software-only component over there as well. So, a, just in terms of where you are today, do you need to invest more in some of the other hyperscalers away from Azure or not? And, b, like as you look at what customers are using NetApp for in the cloud, do you see some use cases which are favoring one hyperscaler versus another from that end?
I think I will clarify one thing about our -- even like when we deployed hardware into the hyperscalers, the control plane aspect of ours was jointly co-engineered between us and hyperscalers. It's not just that they are using it just as a hardware array, but it's a full blown control plane, which we have built. And that's where most of our IP and like making it cloud agnostic and all those kind of things have gone. So yes, it means -- but there are certain use cases where software defined, like if you are running really, really intensive workloads, like our hardware-based solutions, which are embedded inside the hyperscaler work fine. But there are a lot of like Kubernetes kind of and those kind of workloads, where it just naturally makes sense to have a software-defined kind of a storage offering.
So those customer asks are basically defining why we are taking the both approach. For customers, we will make it seamless based on their workload. They don't have to do this whole math behind, this versus that. We want to basically map your workload to the right storage solution for you. Do that hard work for you so that it is price, performance, security, efficiency, all those things they get out of it. So that is how we are making these decisions of, hey, how do we grow this thing.
And I think your second question was, hey, are you seeing some unique patterns in one hyperscaler versus other? In general, the growth in certain workloads is very consistent across hyperscalers, especially EDA, HPC kind of workloads or SAP or databases or even virtualized environments. Those we see very consistently across. But then there is like a little bit of like AI and persona of customers is a little different in each cloud. Azure is more enterprise-centric, AWS has both, a lot of start-up ecosystems also, and Google is probably in somewhere in between. So we do see that.
But on AI side, especially what we are doing with the Gemini enterprise or what we are doing with Bedrock and Q or what we are doing with Azure and like there are a lot of subtleties which has started to come here and customers often use that. That's why I was saying before, AI is probably the most multi-cloud and hybrid workload out there. And for less of time, we do expect, customers will use all of these clouds based on what AI problem they are trying to solve. So that way, our integrations are working out very well for them there.
Any more questions? All right, Steve?
Just a quick one. So you mentioned how there's net new customers to NetApp. What happens to those customers in terms of them expanding across the offering beyond cloud? How do you grow those customers once you have them on the cloud services?
Yes. So I think there are multiple ways to look into this thing. We have built a lot of value-added services, which they start using over the time, they probably start with just provisioning of volume, but in fullness of time, they use security product offerings. We enter into software protection, which is also available in all the 3 clouds of ours. Our other value-added services, like backup as a service or disaster recovery as a service and so on. That's one dimension of that with how they start using our products and keep on growing.
And now what Sandeep was talking about AIDE and all, I don't know, Sandeep spoke or Gagan spoke about it, but one of them must have spoken about it. Those kind of capabilities from cataloging to vectorization, to all those Meta engine kind of things where also we -- from our ecosystem. So that way it works out.
But we have also seen other ways also, like some customers started using us in cloud. And then we met their on-prem requirements also. So we do see that cross-flow between both of them. So that way, once the customer gets the value of using our services, then they start using it in many different dimensions and aspects of it. And we also continue to learn from them what new capabilities to build and work backward from that.
All right. Well, I have one question that I get a lot. So I'll ask it of you. How do customers choose to use NetApp in the cloud, right? There's so many storage offerings, how does NetApp become the decision choice?
Yes. There are -- like there's not a single answer for this thing because it depends upon many customers. Some customers are very familiar with NetApp because remember, we have been 30 years from, some of them are just doing -- they know us from on-prem and when they start their cloud journey, they start using it. Good thing is like 90% to 95% organizations out there today are using cloud in some fashion. Overall, it's a pretty big market. So that's one which they do.
The second is, we are natively integrated into hyperscalers, consoles, SDKs, APIs and so on. So doing a POC, doing a discovery is a really, really frictionless experience for them, and it is integrated into their billing and metering and all those kind of capabilities from the hyperscaler itself. So they don't have to redo the whole thing. So that's one aspect -- another aspect of it.
And then third is, what makes first-party cloud storage also uniquely differentiated is, we use the hyperscaler GTM motion is not different, these are hyperscalers offerings. So the GTM it in that manner, we go through their wholesales, marketing, all those kind of capabilities jointly. So there are multiple avenues. And now recently, we have started focusing a lot on developer personal also, so developers are finding us inside digital studio, core marketplaces and those kind of things. So there are multiple places where the journey starts.
All right. I'll give the audience one final chance. Nope? All right. Well, thank you very much.
All right. Thank you, everyone.
All right. Well, now is the session I've been waiting for the most because this is the coolest customer panel that we've ever had. You'll recognize the organizations that were about to come up on stage and join me.
So with that, I'll ask Aston Martin F1 team, NFL and 49ers and Levi's Stadium to come on up. Have a seat, make yourselves comfortable.
So thank you guys so much for being here. I think to -- since everyone knows what your organizations do, but no one probably knows who you are or what role IT plays in your organizations? Maybe that's a good place to start. So I'll hand it over to you, Aaron.
Sure. Aaron Amendolia, I'm the Deputy CIO at the NFL. So my direct responsibilities include our infrastructure, cloud and on-prem, our innovation hub, where we kind of incubate and try out new technology with R&D, either for the game or for the business itself and as well as our run our events technology. So Super Bowl draft, the international games that we have and a bit of our strategy and finance planning around technology.
So IT is an important partner within the league. We're there to help both goals of the game itself as well as run the business. We're a regular business with the same departments that every other business has and licensing agreements and contracts and things that every other business does, all need technology.
I am Fabrizio, I'm CEO of Aston Martin Formula 1. Similar story. I mean, the -- meanwhile, the prominence of IT in terms of infrastructure, software development, AI, storage, especially in an engineering world like Formula 1 is extremely prominent. We got -- in a couple of days, we are in Austin, then we go to Mexico. So it also -- there is a huge element of international network and data storage and events to manage. We've got the huge capability that we use from NetApp as one of our key partner and helps a lot over the last years to improve the engineering part and how we manage truck and events. And obviously, there are typical IT topics which are more or less the same, cybersecurity is one of them, license management, HPC, cooling system and the staff that are, more or less, everybody is dealing with.
I'm Costa Kladianos, I'm the EVP of Technology for the 49ers and Levi's Stadium. So our teams basically oversees all the technology components of the stadium, of the team and the events around it. So we'll be working very closely. We already work closely with the NFL, but especially this year as we host the Super Bowl, a little small event that we're going to host in the Valley there.
All the pressure is on Costa. He has to keep the lights on.
Exactly. But I mean being with the 49ers, there's a little extra spotlight on us because we are in Silicon Valley. So we really pride ourselves on being leading edge in technology, creating some incredible value and being an example for other sports and entertainment organizations with what we can do. We have amazing tech partners. We're in the hub of innovation. So we really try and take it to the next level with how we can use technology in sports and entertainment.
All right. Well, so you guys are obviously all NetApp customers. Maybe you could talk a little bit about what you're using NetApp for, and what role it plays in your environment?
Yes, I can start. NetApp has been with us a long time. And when we choose NetApp, we choose it because of the cases, like a comprehensive system approach, right? So we have a hybrid cloud. And because we are a media company, you figure a typical NFL game is 1.4 terabytes of video captured. And then we have different workflows that need that video. So in the immediate game, our officiating workflows, our workflows around media production, those are all high I/O, low latency workflows. And as we try to incorporate new technology into those like AI and computer vision and other things, we need those at high performance.
But then we're playing another 280-something games throughout the year and storing those 1.4 terabytes of video forever. And then all the other type of media that's clipped around the game. On top of that, we take data into from sensors, that the players wear, a new skeletal tracking system with 32 cameras around the ring of each stadium and we have to time slice and synchronize all these sources of data together and do them in a performant way, do it on-prem and in the cloud.
So you want a comprehensive system as you're managing this both for archive off into the back end at the highest kind of efficiency, cost ratio and then to the high performance on the front end where our applications list. And then we're also moving it between clouds because we do have multiple clouds between AWS, Microsoft and others.
So really, you need one system approach versus having multiple other systems through other providers, and they're not working well together.
A similar situation. We are also in Formula 1, I think problem statement in sport is pretty similar. Obviously, on our side, there is a huge amount of -- so there's a huge density of data in terms of telemetry. We got telemetry from the car, from the engine. We've got data coming also from the video streams. We've got strategy data, we've got -- at the factory, we've got PLM, CFD simulation, wing terminal data, dyno. The amount of data that this creates and the latency and the density and the algorithm that we apply on top of statistical AI became de facto, the differentiator between the teams. So the investment in that area became bigger and bigger.
And at one point, you start to win, lose if you don't get that kind of technology. And it is de facto standard Formula 1 in all teams. I mean, in my previous experience, I was with another team, ended up, it is the standard course of -- that kind of problem statement and then you have the races, which are similar to the event you are mentioning. And at one point, you have to displace this all around the world, and you got all the connection of the network. You have the control of an engineers in Silverstone, where we have our factory, and this requires that kind of storage system that kind of intelligence on the storage, the kind of metadata management that makes you win or lose.
I mean, from our side, we have a few different buckets, which is critical to us. I mean from a foundational approach in the off-season, we did some extensive renovations the Levi's Stadium. We put -- and one of those was putting in the world's largest outdoor 4K video boards. That creates a huge amount of data. And that data has to be available quick when we're looking at the multimedia component. So we had a 10-year-old system, and we needed something better. So we went out, and we needed the best in the business. We cannot afford to go and try things or give someone a chance. I mean this is something we have 70,000 people there on a game day. We have millions watching around the world. So we have one chance to get it right.
So we had to go with NetApp as we move that data across the network and display it on the video boards and create that experience for our fans. With 70,000 people, you can imagine the amount of data that we get. We have 10 years of it being in Levi's for over 10 years now. And we do a lot with that. We have an executive huddle where it shows us in real time what's going on in the stadium from, when you park your car, to getting through the ticket canopies, to concession stands, to even how much utilities we are using in the stadium. So it's an incredible amount of data that goes through and being in real time, we need that fast.
And we need it to be reliable as well because we have, again, 10 to 12 games a year, and another 10 to 12 concerts or more. So we don't have the luxury of some other sports where they have 200, 300 events. We have to get it right at that time or we lose an incredible chance to excite our fans and a revenue-producing opportunity. So that's why it's extremely critical that we have the right data at the right time and have it reliable.
And then as we look forward, being at Levi's Stadium, I mentioned it earlier, we have to be at the leading edge of technology, not only for our fans, for our partners, even for our team because the ultimate goal is, of course, to win a Super Bowl.
So we -- I'd like to call it the intelligence stadium. So how can we use the latest and greatest technology. Obviously, AI, machine learning, and data to be able to now start getting predictive of what we want to do. So we're great at iterating in real time. But how amazing would it be if we created a full frictionless experience. So from when you're at your coach at home, you know when to leave, when to get to the stadium, where to park, without those delays because that's your first impression when you get there. We want you to arrive happy and leave happy unless we lose.
But then we also want to make sure that we have the right amount of inventory in stock. So not too many hot dogs, not too little, that beer on tap because I mean, that's critical for us. We don't want to create waste at all. And then utilities. I talk about that, but we use an incredible amount of electricity and water in our stadium. And it's important for us to be good climate citizens. So to be efficient there, will not only save us money, but it's green and it helps protecting environment, and set an example for others. So I mean, these are some examples that we use it.
And then going forward on the football operations side, they have an incredible amount of data to use, and they use it very quickly. So we need to have the best powering, the best foundation to be able to deliver that so that they only have to worry about getting wins. The fans only have to worry about enjoying the game. And it works like a referee, they're best when it's not noticed.
All right. Got some questions with Lou.
Okay. For the -- Louis Miscioscia, Daiwa Capital Markets. For the football players, can you have any comments or help for the New York Jets? You talked about obviously a huge amount of data. Just trying it being created on a daily basis. So is your purchases of storage linear to that? And if not, what are you doing in order to try to manage your data? So you just don't have a massively increasing, even though, obviously, we all, NetApp would enjoy, I think, a massively increasing budget, but just trying to understand how you manage the growth?
Yes, I wish it was linear on the lead side in the sense that, yes, we know -- it depends on which video format is capturing by the broadcasters plus us. We set a video center plus us, and we shared a video to all clubs. So league is replicating video that's used for game preparation, right? So that's pretty linear.
But then we add new technology. So the 32 camera ring, I talked about, that went in just this year into all stadiums. There's only in 6 stadiums for POC last year and previous years it was just R&D. We don't know that it was going to be successful or not. So now you're trying to make a storage purchase on. We have 6 cameras that do ball measurement that are 8K and the remaining are all 4K cameras. These are huge data streams coming in.
So you're not going to make that purchase and advance that until you're sure that technology works. And that flexibility is very important to us because then we have to show the ROI or value return for that. So not only are we taking all this data in and haven't had the connectivity for it, then we have to use it and store it. And that's the question there, is that technology going to drive that cost consideration for the storage in the back end. Now we've found value in this, and we find value in multiple buckets when we do projects like this, and that was using computer vision and AI to measure the ball, right, for first outs. But that's just the first part.
We're also measuring all the players' skeletal movements. And so we're saying, okay, is that a new asset? Does that create new revenue streams? Or does it help another goal of a company, which is to speed up the game or improve the game itself, assist with officiating, right? So that's a really big goal of ours.
Or does it help with efficiency? Does it create new efficiencies that either lower other costs or eliminate manual tasks. So those are all the factors we're going into, where we make these investments into the infrastructure to store that vast amount of data. But it is kind of like a pop cycle where we might sit for a couple of years on what we've established. And then the new technology comes out, a new need comes out and it pops. It just really increases the amount of storage we need.
I mean on our end, we try and forecast when we were originally looking at what we need. What we currently need, what we thought our growth is going to be. But technology, like Aaron said, it's not linear. It's goes like this, like this. So you don't know when the next Storage Hog has come in or whatnot. And we'd like to use the hybrid approach, but I mean it's always good because we can add what we need when necessary. So Rob is always happy to take my call to add storage. So it's important us to understand what we need, but knowing that we're going to have to grow later.
So we can't have a closed system. It has to be something that will grow. And there's always workloads that are better for cloud. There's always going to be workloads that are better for on-prem. So we have to make sure that we find that balance and we use the best use cases for each and have that ability to scale in the future because you can forecast, but we never know what's going to happen tomorrow, right?
We are never throwing anything away, right? I mean, literally, our player health and safety algorithms that we're developing are going back over historic footage that we've captured in NFL from over 100 years and tried to compare safety and injury and all these different stats with new algorithms and AI as emerges. So we go back and use the data we thought we archived off forever all the time.
All right. Wamsi and then I will get to the guys in the back.
This is Wamsi Mohan from Bank of America. I guess from each of you to the degree that it's different. I was wondering, as you think about high-performance storage versus cold storage, I mean, it sounds like for some applications for you, certainly, what you're capturing, reviewing quickly and streaming out, maybe you need like high-performance flash for that, other things might be cold storage. So can you give us some sense of how your environment looks split between maybe what you would call as hot/warm or cold storage across your installed base?
And secondarily, as you see the pricing of -- I mean, people talk about HDD shortages and memory shortages, and so how much does that concern you? How do you think about planning for that? And how do you manage those cost escalations in your negotiations with NetApp?
You have more sensors and you run at a faster pace than anything we do, right?
Yes. First of all, on the different level of storage and I mean, in Formula 1, we tend to have like a moving window that is dependent -- the length is dependent on the technology improvement that we have, for example, of 2026. We have upcoming structural changes of all the routes, the car, the fuel, the engine, the tires. So that one, in principle, decide how much data you want to store on the fast and how much you want to kind of pull it on cold store or sometimes we use even old backup system that we can retrieve only when we need it.
The magic is try to understand this together with the engineers, and we have also to adapt to the strategy continuous before -- what you were saying before. So take a decision now, reviewing almost monthly base and then come back to an alternative solution. And for us, the financial negotiation is easier because NetApp is not only sponsor for us, it is one of our partners. We work hands in hands. And we're very close together. We have direct link to senior management. And they want us to getting better in the engineering and win. So we are on the same journey. Let's say, it's less complicated than a classical approach to what most probably your use case is.
Yes. I'd say we have a mix of all-flash arrays as well as storage gateways for the back-end archive. Now these are going to change based on workload, right? And I think part of the strategy is making sure that our storage engineers understand what to manage, what workload where. So you're profiling your workloads for your environment, and then you're also trying to understand how hybrid cloud fits into that and what workloads are happening in the cloud. And sometimes that's with a partner. So more and more you see like you may not control all your cloud environments, you're sending data or sharing data and video and content across to another partner who's in AWS. And you still have to get something back from them. We are taking video back from them after they enhance. And sometimes it goes directly onto on-prem storage and sometimes it's going over to our cloud.
So it gets pretty complicated this management scenario. But really, it's by profiling, what our workloads are, figuring out what's the right performance characteristics of that and then making sure we're managing our storage efficiently because we're not going to sell high-performance storage with things that should be in archive and often other places.
Yes. And similar for us, our engineers are calculating what they need for coal, what they need for hot. In terms of -- but in terms of the cost, I think it's -- again, it's a drop in the bucket adding storage and working with it compared to the investment that we have with the players in the field in the stadium and the revenue that we get back. And I mean, if something were to go wrong on a game day that lost revenue is -- would massively outweigh anything that we need to -- that we need to spend on the back end for shortage. So we -- in that case, we tend to be value high availability environment redundant and secure. And that's more important to us than the cost when you look at the relative risks on the other side.
Right? So the answer as to all things in IT, it really depends how much...
Yes. Exactly. That and reboot.
It depends.
is it plugged in. All right. So Frederick Gooding have questions.
Frederick Gooding, William Blair. Well, actually, first question would be, where can I get one of those jackets?
Yes.
It's actually down there...
There's a gift shop.
There's a gift shop. We'll make sure you exit through the gift shop.
Appreciate it. But now Important question. I'm curious, I've heard the word unified so many times today. So I would love to hear from an actual NetApp customer in terms of how AI ready do you feel like your internal data state is in terms of how you unified that is across the organization and how you expect NetApp to maintain that unification, the data state, if it's not -- if it is fully there already? If it's not there, how you expect NetApp to help you achieve that?
And I'm going to tack on to your question because it's one that I had is all day today, we've heard about the importance of breaking down silos to make sure that your data is AI ready, right? So how do you think about that? And how is that impacting your underlying infrastructure?
AI ready and the journey of AI, Formula 1 is an engineering business. And to a significant extent, we started the AI journey when it was even not called AI or was not known as AI. Formula 1 tend -- already in the past, they tend to manage a huge amount of data sets in engineering way, with a lot of statistic analysis and creating models on top of it. So what the machine learning approach gave to Formula 1 team in engineering terms, is something that is already present. You have an intrinsical engineering problem, it intrinsically structured already to be analyzed in a statistical way. So this before AI.
When the amount of computation power allowed us to enter a very sophisticated multi-dimension machine learning, the readiness was already there because the data was intrinsically that kind of data. So the journey is complex, but for the nature of the business in engineering, we were on the front line from the beginning on a partner like NetApp is for us, was the only way and is in fact the only way because you have to crunch data sets. So there are immense not then much the amount of data, and there are different streaming feeds.
And so is what's inside the data are. So there is an element of information about one engineering problem that could have 20 dimensions. So it spans through multidimensional spaces and the sweet spot of the car in terms of sedan could be an area that you even didn't think about. So this kind of analysis, we were doing this all across the last decade. And de facto, NetApp was the only way to do it because the amount of data you have to crunch at the speed and not to be, let's say, limited by the storage factor was critical. So that's the reason why in Formula 1 is a de facto standard, and it will standard more than -- almost 10 years ago. I'm not sure about NFL, you can answer, but it was kind of never a discussion if we make sense.
We've been doing machine learning a long time with the sensors and some of the other aspects of optical tracking that we've been doing, for many years. But I feel like this is always like a trick question. You say, how do you know your AI ready? Well, you know when you're not because something fails or doesn't work. You don't really know when you're AI ready for everything can possibly come. And we spent -- a lot of like of the media workflows are very specialized in the past. So whether you were working for football purposes with media or you are working in our NFL network, and producing for games or you're working with NFL films and trying to produce a long-form content. There was like a whole specialized workflow around metadata around that. And it was very manually and manually tagged, right? And then they have these vast deep archives behind it.
So when someone in the social teams department want to post to all the different channels or someone in our marketing department or someone wanted to create something with partners for PR purposes, they were going to be specialized roles and saying, go and source me up, clips around Tom Brady and all the Super Bowl win he's had. All right. Well, now multimodal AI comes in. And now we no longer need to use metadata tagging potentially to find and source video. Not only that, it is richer and faster. I can go search for show me Tom Brady with no helmet on with the Pepsi sign behind them because that's our sponsor, had a post-game trophy ceremony, right? That was something you couldn't really easily metadata tagged for before.
Okay. So now the social department can go and find these things on their own, but all of that is stored in these specialized stores that's behind where all the media workers are. So now it's been -- not so much that we have the wrong storage or the wrong architecture. In fact, we have the right choices there, but it's exposing it at the right layers to these applications to be able to use it and access it. And now you have to watch that.
Okay. Now I have all these other new stakeholders coming in and hitting a storage area that was scaled for one department's use, right, kind of contain. Now I'm exposing it. Oh, I also want my fans to be able to hit that and use multimodal AI to source up clips from our historic archive. Okay. Now we're going to place that so it can take a public workload.
So some of this has been we're going to expose things that were once cordoned off and specialized at different layers across the company, and we have to look at our architecture and make sure it scales right. I think that's the importance of having kind of one partner cohesive system across so that it can scale versus we bought the cheapest storage for each of these places because that happens in a lot of media companies. We buy whatever is cheap this year. We go and we dump a whole bunch of video on it, and it's just the people in the video department know how to pull out. No, we need something that can instantly pull up video across the organization.
Yes. And I think it's an important question that you asked in terms of data hygiene because if we look at even a year ago, it was thought that, okay, you can just dump anything into the system and the AI will figure it out, and it'll give you an answer you want. And what we've seen is that there's a tremendous amount of bias in there. So you have to have -- just like we've had a machine learning era, just in any area, you have to have clean data in there to give you the right results.
And what we do in our organization is we have a group called the Intelligence Stadium Committee. So it's a bunch of decision makers and subject matter experts in each different department. And we all sit around once a month, we have a group channel. We all have ad hoc conversations where we look at what are the prioritization of the organization, what data do you have and what are you trying to accomplish? And then taking this understanding, we look at, okay, can we apply AI machine learning, any tools that get into that? And work to enable your business. So then it doesn't just look like it's an IT project coming through for AI for AI's sake because we know AI gets thrown around everywhere rightly or wrongly.
So we actually want to have good use cases. We want to have the right data behind it, and we want to have that data integrity checks because AI still does have a tendency to hallucinate, and we want to make sure that we have the right people checking to make sure that we have the right results. So data hygiene is incredibly important. And it's not a case of being AI ready or have -- it's an always an iterative process where we're always looking at it, always improving, always trying to find the mistakes. Because once you take your eye off the ball there, that's when you have -- that's when you get errors into the system, and that's where everything breaks down.
All right. Ananda?
Ananda Baruah, Loop Capital. Thanks for doing this panel. This is a pretty cool panel. Each of you have spoken about how critical video is to your respective businesses. And so the question is, is there something about the heavy use of video that makes NetApp particularly attractive to you guys?
Yes. I mean, for us, when we talk about the 4K video boards, that's a lot of data. When we talk about 8K now, when we talk about the resolution that the players need when they're scouting or practices or things like that. That's a lot of data that's needed quickly. And we look at NetApp, I actually -- DreamWorks uses them. So if it's good enough for them, it's good enough for us to have some heavy workload. So it's important that, that data is quick that data is reliable. And they were really -- when we went out and did our research, I mean, they're the only ones who can handle the workloads that we do because the NFL has always been video-heavy sports league. It's built on that more than a lot of the other leagues. And then what we just do in stadium with video for our fans. It's an incredible amount going incredibly quickly. So we have to have something reliable and highly available.
Yes. So like the officiating department, for example, is going to scrub through video. So they're going to -- high frame rate video. They're going to take it and they're going to move the dial to go and slow motion back and forth front, in reverse, right? And what's important for them is that it's not dropping a frame, it's not skipping. It's not a jerky movement. And they're doing that to make a decision for the game that's live, right? That's a replay moment. They want to make that decision in the AMGC in New York and seconds count in this matter. So any sort of performance issues with the video is going to be a problem for us and then also actually the reliability and robustness that it's there.
I think one of the things that's -- we can all sit up here, we're all NetApp is a sponsor of the league. But NetApp was a sponsor league in the past. And then there was a point where NetApp is no longer a sponsor and now NetApp is back. We do not stop using NetApp in that interim period. So I think that's more important than NetApp being a sponsor of the league is we had other storage vendors come to us and say, we'd like to be a sponsor, take our storage. And we said, no, we're happy with what we have and it's performing. And now we're really happy that NetApp's back and we get to tell the story together and I get to bother them for the product and engineering, which is really what I want to do, right? I want to have that product deeply ingrained and partnered with us.
But what we've seen is that quality and then we add then we add in the protection of the cybersecurity layer. So we're very happy with the ransomware protection and other features while it's still performing. I think other platforms don't give you all those things. You feel like you're picking fast, cheap and performance, and you're getting all 3, right? And that old adage is you only get two of that, type of equation.
We've got a similar situation also in motor racing. But it's an evolution of the last 10 years, come across together with the amount of cameras that were put everywhere on the cars, a different perspective, obviously, tracker, one on helicopter. And there is an amount of information there. The other one which is pretty relevant for motor sports is also all audio channels, which are also very important between drivers and engineers. And that kind of information is not classical vector information you got in engineering. So you need to do some massage, you need to do some analysis on the data. And they come on that quantity, so big.
So you need to extract the information that you're searching for, and it's an area where, again, NetApp is not -- I mean, it's de facto the only way to do it for us. And there were similar conversions also in Formula 1, there are other companies, but they never -- they would have never even passed level 1 of a 10 conversation. So it is so much the amount of decision that you need to take based on that kind of engineering data, video streams, GPS streams, got lots of data getting enriched by the position, [indiscernible].
If you compromise there and you try to save some capital investment, which you could and then finance department is happy, you pay a lot and other teams not doing it. And at one point, you see -- it's something that you may not see directly in the car performance. But after a while, you start to feel it and then you start to feel the difference with the other teams. And it is pretty clear that, that's something that you can't compromise if it makes sense, something similar that you would say. Yes, you can save here and there, are you really saving? It's a good question. And it's more or less the same answer across the whole Formula 1 and across other sports.
So there is a story behind that, that in this kind of cutting-edge scenarios, which are sports scenario, a very sophisticated meanwhile, lots of cameras, lots of events, geographically located everywhere connected with central teams in different cities like U.S.A, in New York, we've got lots of center U.K. If don't have that kind of infrastructure, you start to pay a lot for something that you think you're saving, but saving is in principal something that making lose the sport. And in sports, it is about winning. There is no -- I mean, the return on investment in sport is something different than from a normal financial business or a commercial business.
So if you don't know winning, if you're second, that's the first to lose. So you start -- that's a quote from famous Formula 1 person. He just say that you don't compromise there. You compromise somewhere else. You can compromise in IT, in lots of other departments and areas. There are 2 or 3, you can't compromise cyber, you can't compromise. You compromise there, you risk your own business, storage, you don't compromise de facto.
All right. Tim?
It's Tim Long. Maybe quick for each of you. A lot of new product announcements up and down the businesses for NetApp today. Just curious for each of you, did anything resonate as something that fills a need or something that you're excited about adding to the portfolio? And if not, anything in the last year or 2 that did fit that bill of something that really address the key pain point that you really wanted to deploy quickly?
I mean, for us, I'm excited to kind of go through them because there's a lot out there, and it's fantastic. And I was meeting with some of the leadership this morning, and it's like, okay, how are we going to put this in here, >what can we use? And how can we kind of do it -- again, to hit our business goals and create some value? So we're definitely going to be taking the time with the announcement this morning, extremely exciting and see how we can incorporate them into our business and start working.
I mean, our goals are: excite our fans; and win Super Bowls, two very easily said goals, but not as easily done, but let's see how we can use these and it's exciting that there are innovations coming every year. There are iterations, and we are moving forward, which is something that we wanted. We wanted more than just a storage company. We wanted someone who's going to work with us and start using this and start generating some value. So very excited to dive into it. I can't -- don't know anything specific that we want to do yet. I know when I'm back here next year or sooner, I'll tell you how successful they were. And I'm sure they will be successful, hopefully, with a ring on, but we'll see.
I mean the one that was announced in the keynote NVIDIA was interesting. The two companies are part of a journey that's happening all around the world, in different business, in different areas but with a very consistent approach and pattern. Both companies find themselves in a situation where there was an evolution, NVIDIA, we all know the story that started doing something different. So it's -- at one point, the capacity of the competition on the GPU side, and for NetApp, the capacity of the storage reached the threshold or a kind of point on the return that all of a sudden, they created new business on top of what storage was before.
Because storage is something that is in computer science and in IT, was more than 40 years. At one point, however, on top of the storage itself, it's -- like for NVIDIA, on top of the graphic card itself, which was a complete different business. Something new happened and something emerged out of the storage, out of the GPU. And I think the two companies together can create something that can emerge in a very interesting way in the AI space because we know very well, AI is extremely intensive from storage and extremely intensive from the GPU perspective.
And for the engineering problem statement that we have in motor sport, it's complex, complexity of fluid dynamics, for aerodynamics, research for engine, research for gearbox, research for tires, or for strategy. They do require an incredible amount of data and an incredible amount of computation. I think that collaboration today was presented may emerge something very interesting in the next 5 years. And for us, in terms of motor sport or something, we're extremely looking at. And like I said, 12 months, it'll be interesting to meet again, and there could be some use cases, very interesting.
Yes. Maybe I can help you with our problem. So today, we are talking about the massive amount of data we have in different areas from different sources that needs to be synchronized to the high-quality video. Some of that video is public that you see in the broadcast from these other cameras we've talked about. And then we're going to create derivative products of that. So what I mean is we were talking today with an engineering team that goes across the whole organization about a central data hub. So when I hear all the announcements today, I'm trying to think and all your analyst brains help them together here with me, and we'll compare the answers, you give me the ChatGPT or Gemini or something.
What -- how do I put this technology together to accomplish this goal? Taking all of these data sources in sensors, cameras, we actually have human to also still score the game too because the computers haven't yet figured out who has credit on the sack and it's probably coming. But then we have to put this into one place, and then it's being used in other use cases. So we talked about player health and safety before they're going back post-game looking at that data, looking at the skeletal model data, they're actually adding a muscular structure to the skeletal data, literally is a skeletal model. They are using another algorithm to add a muscular structure, and then they're comparing it to the real video from all the different angles we have, right?
And we're saying, okay, that's really cool for player health and safety. Does that maybe have a use in the future in AR/VR and gaming, right? And I want to put all that data and all that source in a place that can be access once because the current problem I have is we're storing places in so many different areas, and we're duplicating, right? We're duplicating to go across to a partner who's developed this technology, but I want to expose it to them and not let them take our data out of our data centers and out of our cloud.
And that's what we're looking at NetApp for in these cases is, okay, these are going to be all AI-driven use cases, these are all machine learning, other types of technologies, but I want to centralize them and have them be exposed for both internal and B2B types of purposes. And eventually, then may be downstream to B2C. So that's what I'm listening for in these keynotes and in these announcements, and I'm going to have to see how these things play out, but definitely appreciate all your input on what we might build out of this.
All right. We have time for one last question. It goes to Mike.
Thanks again for being on the panel. This is Mike Cadiz from Citi. So in the multi-cloud environment that we're in, how do you decide between first-party marketplace NetApp offerings versus the competing hyperscaler. It could be very well NetApp and if so, why?
I mean in Formula 1...
We got users here...
I mean, we are -- consistent governance and controls is one thing, right? So you're not -- like I was saying all these other buckets before. Well, if you want to have consistent governance and control, you have to have one platform or at least one logical rule set that can apply across all these different environments.
I mean, there was a similar question before. This is something that we even don't have the luxury to have the question. The problem statement is so complex from the data density from the speed of data, from the need to extract engineering data that as by now, and there are 11 teams next season, 10 teams currently, plus the FIA, plus the whole Formula 1 endeavor. We are this week in Austin, and in a couple of weeks, we'll be back in Vegas. All of them using the same technology. I think the fact that we are talking about a company, again, I mentioned another company before that find the right way in the last 30 years across something that was exploding all around the world.
I mean I was working in financial industry. It started to become very complex in the 2000s, the amount of data that was coming from all the market and financial industry was a bit ahead of the game. And at one point, some companies got it right. And it's in terms of how they add their production, how they have the distribution, the sales approach, the way they do the contracts and 30 years down the line, they create in our area, the fact, the monopoly. So that it's so important that problem statement, you can solve it like this.
And it's not that we didn't look to other solutions. I'm not sure how much you did, but at one point, the decision comes pretty straightforward, and you look at the alternatives and you look at problem statements you got from businesses and say, okay you can look at different investment schema, leasing scheme and so on. We got all the [indiscernible] for us, plus they're right partners, so it's even more, and we're pretty confident or pretty relaxed with the -- to be honest, managing IT department, I have other problems. And this is an area that for me is consistently performing over more than a decade.
And I'm confident the company has the right management, the right approach. They did it right, did it right again. They're doing it right now with AI. So it's a pattern. They're managing right to their business and the results are there in the market, I would say. So just how it evolves after you were discussing this 25 years ago, we would have a completely different conversation. This is the same for operating system for CPUs, for RISC and CISC. So these kind of things at one point they converge. And at the current state, they done it right and we're very, very happy.
Yes. I mean, for us, it's -- I mean, we have the luxury of the being an NFL team, being in Silicon Valley. So we don't have to just take anyone who comes along, you want to be a partner. So we looked at everything. We looked at the competitors, and this was the best of the best for us. And when we're looking at a cloud hyperscaler environment, since we have that hybrid environment of on-prem, we wanted to make sure, obviously, security being the most important, the high availability, it has to work so we wanted to stay consistent. And that's what we found with the best, the less -- that can break the less that can -- less chance of breaches where we want to do because it has to all work and it has to all work easily for us.
And again, I'll go back to that early point. We were lucky enough to have our pick and go out there and say, who's the best of the best, who fits into what we're trying to do, not just a case where I've been in other organizations where partnerships say, here, these guys are -- want to be our partners, go take them. It wasn't this case. It's like let's go the best and let's create authentic experiences, let's use them. And then that creates a real partnership and then we can work together as actual partners.
We never underestimate the friction of reskilling. So when you have your engineering team, and they have something precision working right, we're not going to go and move things across multiple clouds and change back ends and switches and controls just to get either something cheaper or do something because it's not supportive. We're going to ignore that option because we don't want to have an environment that has risk that we didn't understand it. So therefore, it failed on game day, right?
All right. Well, Aaron, Fabrizio, Costa, thank you guys so much. This is so fascinating. I could keep you up here for like another hour, but I know you have things to do. So I really appreciate your time and thank you.
Thank you very much.
Thank you. Thank you. Best customers panel ever, hands down.
All right. We're definitely ending today's session on a high with some great real-world stories about the value of the NetApp data platform and the importance of having consistency of your data across hybrid multi-cloud environments. I know you guys have heard it from me for a long time. I'm glad that someone else said it.
For everyone on the webcast, and for those of you here in the room, there's another general session that will be available for streaming tomorrow morning from 9:00 to 10:30 Pacific. If you missed this morning's general session, you can catch the replay. All of that is available. Links are available from the IR website as well as from the Insight website, which is search, NetApp INSIGHT, you'll get all the links.
And I thank everyone for joining us here in-person and on the webcast. Thanks, everyone. Have a great day.
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NetApp — 2025 INSIGHT™ Customer Conference
🎯 Kernbotschaft
- Kernaussage: NetApp positioniert ONTAP als zentrale AI‑ready Datenplattform: AFX (disaggregiertes Exabyte‑Storage) und AIDE (AI‑Data‑Engine) sollen In‑Place‑Transformationen und Vektorisierung erlauben, Kopien reduzieren und Sicherheit/Lineage erhalten — ergänzt durch Cloud‑Integrationen und erweiterte Cyber‑Resilience‑Services.
🚀 Strategische Highlights
- Plattform: Einmalige Quellkopie bleibt erhalten, unterschiedliche Formate (Files/Blocks/Objekt, Vektoren, canonical metadata) werden per Präsentation bedient – weniger Datenkopien, bessere Nachvollziehbarkeit.
- Produkte: AFX = disaggregiertes Storage für hohe Performance/Skalierung; AIDE = Metadaten‑/Vektorisierungs‑Engine; enge NVIDIA‑Kooperation (DGX SuperPOD‑Zertifizierung) für AI‑Workloads.
- Sicherheit & Cloud: ARP (Autonomous Ransomware Protection) ausgeweitet, neues Ransomware‑Resilience‑Service mit Data‑Breach‑Detection und isolierten Recovery‑Umgebungen; FlexCache/SnapMirror/Hyperscaler‑Features und GCP Block‑Support angekündigt.
🔭 Neue Informationen
- Neu: Konkrete Launches: AFX, AIDE, DGX‑SuperPOD‑Qualifikation, Ransomware‑Resilience (Live‑Breach‑Erkennung + isoliertes Recovery), Shift Toolkit für VM‑Konvertierung, GCP‑Block‑Support, Erweiterungen via Marketplace (inkl. 6‑Monate Trial).
❓ Fragen der Analysten
- TAM & Markt: Analysten forderten TAM‑Sizing für AFX; Management hat das nicht konkretisiert und die Frage auf später vertagt.
- Adoption & GTM: Fragen zu Sales‑Motion, Partnervertrieb und Zeitachse von PoC→Produktiv; Management kündigte detailliertere Go‑to‑Market‑Infos für Earnings/Follow‑up an.
- Budgetverschiebungen: Analysten fragten, ob NetApp Teile von Cyber‑ oder Backup‑Budgets abziehen kann; Management sieht Opportunitäten, will aber mit Partnern kooperieren statt reinen Cyber‑Play zu werden.
⚡ Bottom Line
- Fazit: Die Ankündigungen schärfen NetApps Profil hin zu AI‑Datenmanagement, disaggregiertem High‑Performance‑Storage und integrierter Cyber‑Resilience. Potenzial für Marktanteilsgewinne und höhere Serviceanteile besteht, hängt aber von Umsetzung, Sales‑Motion und schnellen, messbaren Kundenreferenzen ab—Investoren sollten Adoption, erste AFX/AIDE‑Wins und Marketplace‑Uptake eng verfolgen.
NetApp — CEO Spotlight Series
1. Question Answer
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And with that, I would like to turn the call over to Samik Chatterjee to begin. Please go ahead.
Yes. Thank you, Harry, and thank you, everyone, for joining. This webinar is part of our CEO Spotlight Series that we've been doing this year. And we have the pleasure of hosting George Kurian from NetApp for this session. I do want to thank George as well as NetApp team for making this possible.
I was just going through George's sort of background related to NetApp and George as much as I knew that you've been the CEO of the company since 2015, I definitely didn't know that you were part of Cisco before that, which is another company we cover. But for the people in the audience who are not -- let's [host] with it, George has been the CEO since 2015 after joining NetApp in 2011. And prior to that, he was at Cisco and prior to that at McKinsey and Company, I believe.
So George, a long time at the role here, and we'll get into some of those questions about sort of the longer-term view about the industry. But before I do, we also have Kris from Investor Relations here. And Kris, thank you for taking the time. And I'll hand it over to you to go through the safe harbor before I kick it off with questions. Thank you.
Thanks, and thanks for having us. Today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in our most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. We disclaim any obligation to update information in any forward-looking statement for any reason. Back to you, Samik.
Thank you. Okay, George, so maybe just starting with that longer-term picture. Now you've been in the CEO role for 10 years plus, I guess, what are the primary changes you've seen in the industry as well as what -- how have the customer preferences changed that NetApp has had to navigate over this sort of last decade?
Yes. First of all, Samik, thank you for having me and to the listeners, thanks for joining. Over the last 10 years, there have been sort of 3 or 4 things that I would say continue to be consistent. The first is ongoing changes in the market. I think the most pronounced change over the last 10 years has been the growth of public cloud and cloud as an infrastructure pattern. We have been able to be fortunate to uniquely in the market, capitalize on the transition to public cloud. Public cloud has also driven the importance of OpEx buying as a growing pattern within the enterprise data center where people want to harmonize their operating models between public cloud and on-prem.
The second has been sort of ongoing technology trends, which is people want to use the latest technology like flash or higher-performance networking, there's a lot of new networking things like RDMA over Ethernet and other things. And so that's an ongoing set of capabilities that we see that we continue to take advantage of.
We got to #1 in all-flash as a result of our strength. I think the third operationally within the client base is that more and more clients are being challenged to do more with less, especially around infrastructure. And so it has driven in addition to the push -- emerging push on AI, it has really driven the idea of unifying your data, unifying your infrastructure model into a more consistent pattern.
Two other things that we've seen is the large multiline sort of integrated system vendors, these could be Dell or HP or IBM has lost share in the market. This continues the pattern for the 50-year history of the storage industry.
First, it was IBM that was in the 1990s dominant and then lost share. Then Dell and HP have each done large-scale acquisitions and have lost share. And so that continues. And then interestingly, hyper-converged was a trend that was supposed to be a big deal and would take over the data center. It has its place in the smaller data centers, it has really not taken over the large enterprise data center. So that's really the big themes.
And AI, if I look forward over the next 10 years, the ability to extract knowledge from your data assets is probably the most profoundly important theme that we see in our clients.
Okay. Great. So that's on the industry front. Maybe if I take that same question and sort of lay it -- in terms of operationally. Like what were the primary -- maybe over the last decade, what were the primary aspects you focused on in the company in terms of operational transformation? And have those delivered the results that you expected as well?
Yes. Maybe I'll talk about it in 3 ways. One is portfolio. Second is go-to-market. Third is kind of financial and operating performance.
I think on the portfolio side, listen, we continue to pivot to the growth areas of the market and do that by shifting resources from mature parts to the growth part.
So I think we talk about the fact that there are 4 drivers that we're focused on, flash, cloud, block and AI. And so from a portfolio perspective, we're pivoting there.
Flash was a much, much, much smaller percentage of our revenues. When I started, it's now 2/3 of our hybrid cloud revenue. The Keystone program, which is to really deliver a consumption model has grown strongly across revenue, TCV, unbilled RPO pretty much all the metrics. Cloud is 10% of our revenue, public cloud and is growing at a fast clip. It grew 33% last quarter and is very margin accretive to the overall business. And that's really the short summary of the portfolio, right, pivot to where you see growth areas of the market and do so within the disciplined operating model.
On go-to-market, we decided to sharpen our focus on the biggest markets. Fairly early in my tenure, we pulled out of about 19 countries and use distributors to go to market. Perhaps most importantly, we struck a joint venture with Lenovo that provides us access to the China market without the operating cost structure that's required to participate in a large market like that.
And then from an operating expense perspective, listen, we have been disciplined operators of the business. We compare and contrast the first quarter as CEO, our operating margin was around 7%. I think you see the most recent quarter was north of 25%. And so those would be the 3 buckets. From a capital return perspective, we had just started a buyback and dividend program in 2013. I became CEO in 2015. We have sustained that and expanded that over the last few years. So that's sort of the 4 buckets on transformation.
There is always things that you want to do better, right? You got the #1 in flash. We feel like we should expand our lead from that position. I think on cloud, we feel good about the fact that we've got the big 3 hyperscalers. There are others we want to do more with. And so you always have the aspiration to keep pushing.
No, fair. And that I was going to bring up the margin aspect and the transformation on the margin front in a bit. So we can talk about that as well. On the portfolio side, NetApp was named again as a leader in the Gartner's Magic Quadrant for enterprise storage platforms. I mean as we look at that leadership that you have today, really the question is, again, sort of going back to the operating discipline where like you've been growing expense probably half the rate of your revenue, which basically means you've been growing at that level of low single-digit piece.
How do you envision maintaining this leadership and that expense profile is more mirroring sort of that low single-digit at profile at this point. And we are seeing more, more and more companies sort of having to spend more to keep up with the rapid technology transformations. How do you envision maintaining your leadership in that framework?
Yes. I think the foundations are: one, you have a disciplined culture. I think that we have a real focus on, are we moving our resources to the parts of the market that are growing. And then strategically, we have done one thing that is technically very hard to do, but has extraordinary leverage, right, which is we have one operating system and one platform that allows us to have enormous leverage in our business.
There is literally a single code line, one software code line that supports our systems that supports our Keystone and that supports our penetration into all the public clouds. Not only does that give us operating leverage, but it also gives us enormous innovation capacity because you innovate once it's available everywhere. And so that's our advantage. And we've seen -- we've worked really hard to sustain that advantage with a single code line and all of that discipline.
Got it. If I move to sort of a different question, but more on the top line growth over the years. I mean the way I think we perceive it and investors perceive it is that the growth in data for customers has been consistent over the years, and that's a secular driver for the -- for your business. However, that's been a very consistent -- the increase in data has been pretty consistent. And the expectation typically has been that, that would lead to more consistent top line performance from the likes of NetApp.
Relative to that, when we look at some of the top line performance that you've had, like years like 2016, you had a 10% decline. In 2022, you had a 10% increase. What drives the volatility in sort of your performance on a year-to-date basis, even though the secular driver seems to be much more consistent and predictable from what the enterprises are seeing in terms of data growth or their storage need growth?
It's a good question. While data growth is consistent, customers often buy periodically, especially when there are moments to take advantage of opportunities, right? So the first Trump administration's policy on benefiting investment and some tax advantages drove a lot of buying in the early 2018, 2019 time frame. 2022 was a year where clients were catching up from deferred upgrades from COVID as well as some of the constraints that the supply chain had.
Conversely, there have been periods like 2016 and 2020, where buying has been more constrained. I would point out that we focus on 2 things. One is, we have a large part of our business that's more recurring revenues that supports the cost structure of the business. And then the second is we continue to expand the range of customers we serve and the different set of use cases in the customer so that even if there is kind of volatility in some parts of the customer, we can get access to others.
Okay. Got it. Got it. And then another sort of question on the way NetApp operates. I mean the value of the storage platforms is in the software or a large part of the value is there. But then you mentioned like there's a sizable amount of recurring revenue from the way you look at things based on that software capabilities.
But at the same time, you don't appear to be using or relying as much on subscriptions with your enterprise customers in terms of your preferred go-to-market motion, particularly for the hybrid cloud portfolio. Like what drives that decision to sort of look at the ongoing business with the enterprises as recurring revenue, which you have visibility to, but not really push them towards a subscription model?
Our approach is to meet the customers where they are and to have the broadest range of options available to them. We have several elements of our business that are recurring. So support, which is about 40% of our business is actually a recurring revenue stream. When a customer buys equipment even in a capital expenditure model, about 40% of that still goes into a recurring model.
The second is cloud is all recurring, and our Keystone model is more of a recurring subscription and consumption model. So we offer and push people, hey, we have these models, do you want to buy them? At the end of the day, our view is if you force customers into a particular model, they may not go with you. They may choose an alternate vendor. And so we continue to see subscription as a percentage of recurring revenue as a percentage of our total business go up, but we also want to meet the client where they are. And many clients have a strong preference to buy a certain way.
Okay. Okay. Block storage market, you entered the market in terms of having very specific products for that use case pretty recently. What should we think about as the measure of success for NetApp in that market? And are customers choosing to stay with your unified storage? Or are you finding them sort of some of them moving over to adopting specific block storage products in your portfolio?
We have had block storage for a very long time at NetApp. We have north of 20,000 customers who use block storage with NetApp. They, as you noted, buy it as part of a unified configuration, meaning they want to have one system architecture in a cluster, some of that to support file-based storage, some of that to support object-based storage and some of that to deploy block storage. We are, by far, the leader in unified storage.
There are, however, customers where they just want a block-only offering. These could be either smaller customers that don't have such a sophisticated set of data needs. It could be departmental environments and larger customers, which look similar to a smaller customer or in the very, very large customers where they have file teams and block teams in their infrastructure organizations that are separate. So we introduced a set of block only or block optimized products. Those -- the success of those products comes from growth in our all-flash business. And so -- because those are all-flash configurations, the block-only products.
Got it. I mean, maybe another way to ask it is, are you seeing your deal sizes with existing customers go higher because they're adopting these block specific products, which they didn't do before? Or it's it just a migration for these customers from instead of adopting the unified product to moving to block?
We are seeing new wallet in existing customers and also new clients like mid-market clients that never bought NetApp before starting to choose us.
Got it. Great. And then going back to the -- your #1 position in flash and you've gained considerable share overall of the market as well in the last few years. And some of that has been C-Series. You also have the ASA series. How should we think about runway in terms of market share gains. Like if you take these 2 specific products separately, how should we think about how much more runway do you have in terms of market share gains?
Listen, I think that the market share data that IDC published has us in the 25% range. So I tell our teams that 75% to go, right, in the all-flash market. Because your aspiration is to have dominant share. So there's plenty of market share gains to be had.
Our aspiration when we build our financial plans is to grow at or above the market so that we maintain or grow share, right? That's sort of the benchmark that we hold ourselves to. We really want to be gaining share. We believe we can. The C-Series and the ASA products complete the set of things that we need to address the flash market. It allows us to have price points that we couldn't have before when we only had the A-Series in the unified product portfolio.
And then as we just discussed, a block optimized offering. I think the portfolio is in a good place. We have some exciting announcements to come on the AI front at our Insight User Conference. And I think that we feel confident about driving share gains in the flash market.
And maybe, George, just to look at it from another way, you brought up an interesting point, which is 75% more to go. Like how many of your customers adopt only one storage vendor versus how many of your customers do you find typically working with 2 or more storage companies?
I think what we have seen with the growing pressure on operating expenses in most of our clients, the need to have speed, agility and security. The idea of having so many different vendors for storage is actually shrinking. They really feel like, hey, if I want leverage on my storage vendor, I can go to cloud.
Cloud is my negotiation point with the on-premises infrastructure vendors. And so the pattern of I need multiple vendors for addressing my control and vendor control is starting to dissipate. We see most clients having 2 vendors and some who want just the simplification going to one vendor. And so we feel like there's an opportunity for us and maybe one other to sort of grow share in the market.
And then staying with this market share thread. When I think about -- you mentioned this early on in terms of the integrated players giving up share to companies that are more focused like yours. I mean when you think about the share gains in the coming years, are there specific customer verticals that we should think of that's more likely where maybe it's more mid-market driven that we should think about the share gains? Or in terms of competitive companies, we should be thinking more of that coming from like a Dell or HP. How would you encourage investors to think about where some of the share gains come from in the coming years?
I think we are focused on the biggest geographies in the world. I think that someone like a Dell or HP has distribution reach advantages over us in the smaller markets of the world, like in Africa or some parts of Latin America. Our view was the strategy that Napoleon pursued, right, is when you fight a much bigger army, you kill the middle. And when the middle collapses, the sides have to fold into the middle and you can kill the whole army.
So we concentrated our coverage in the biggest markets in the world. And we have seen that opportunity, right? I think we have taken share. We are #1 in 8 or 9 of the top 12 countries in Europe. We've taken over #1 in India, we are -- we took over #1 in Australia. So we're really focused on our go-to-market.
I think with regard to the -- where should we gain more share, U.S. obviously is the biggest market. And so we really want to gain more share here.
The second is with regard to price bands, our portfolio has historically been strong in price band 7, 8 and 9 with the C-Series and ASA, we brought more capability into price bands, 5 and 6. So we feel like there's more room to grow in those 2 price bands. I think those would be sort of the quick summary of where we continue to take share.
With regard to the players in the market, listen, there's lots of kind of legacy players for whom storage is not a focus, innovation is not a focus, ability to attract, talent is not a focus, right? These could include the big share donor, which has been Dell but also IBM, Hitachi, HP, there's lots of opportunities to compete.
So maybe moving to the all-flash growth that you've seen, you've been reporting double-digit growth over the last year. Except the last quarter, when we did see some moderation there, and you explained that to be driven by the public cloud vertical. Should we assume that excluding public sector -- sorry, public sector, I meant, public sector, excluding public sector the double-digit momentum in all-flash is unchanged for NetApp and that you can sustain a double digit rate if public sector spending comes back to a normal space?
I would just say without giving you all the numbers, if you were to do the math, if public sector had been flat, our flash number would have been significantly higher than where it was. And so without giving you all the specifics, yes, we would have -- we feel very, very confident that we would have been able to have a much higher number in flash.
Okay. I'll take this one question that's come in, which is related to, again, the all-flash market. So the question from the investor is that, NAND prices have increased and some of that has helped the suppliers that NAND suppliers itself in the industry, how should we think about how protected NetApp is from spot pricing of NAND? Or will the increase in NAND pricing drive some level of moderation in all-flash market growth?
Yes. I think sort of probably 3 or 4 things in that area. One is we offer a broad range of products, both flash and disk-based storage. Our view is that for certain classes of workloads, disk makes, hard drives make a lot more sense, secondary storage, archive, even for media streaming, you really don't need all-flash. And so the price of flash has to be very close to the price of disk, which it isn't, right?
And so that's the first thing. There are workloads for which disk is much better, right? The second is with regard to the flash pricing itself, vendors typically have passed through the pricing to customers when prices go up. And pass through the benefits when prices go down. As a reminder, only 30% -- roughly 30% of our total costs in a system that a customer buys is really NAND, right? There's a lot of software and support and other things that go into the system cost.
And so the last thing is we work with our NAND suppliers to insulate ourselves at least for a period of time from spot prices. There are long-term agreements we structure, we get multiple vendors to compete for our business. And one of the advantages when you are #1 in the flash market is more vendors want to be part of your bandwagon, right, more NAND vendors. So there are lots of ways that we try to manage through that.
Okay. Moving to public cloud, and maybe outline for us what is your vision for NetApp's position in the public cloud storage market where you're a leader but you've also sort of tried to be in FinOps before you decided to exit using the spot -- get out -- exit the spot business. I mean, how do you envision sort of NetApp look like in the public cloud in a few years from today and beyond sort of first-party storage, what are the other drivers there that we need to think of?
I think that our primary focus is to scale our first-party and marketplace cloud storage services and to build a competitive moat around that, we build that moat in 2 or 3 ways. One way is to -- now that our infrastructure is in all the public clouds, our storage infrastructure is there. It is to add value in terms of additional software capabilities that allows us to differentiate our technology.
So for example, Autonomous Ransomware Protection, compliance capabilities, multi-cloud, Multi-AZ capabilities. So there's an ongoing set of software capabilities that we bring to that platform. And the second is to integrate that platform into the software applications that the cloud providers have. This makes procurement a lot more easy for customers, right?
So customers may not buy storage, they may buy a SageMaker environment or they may buy a Vertex environment for AI. And in this way, we can get consumed when they provision a Vertex or a SageMaker where they may not know what the storage is. And so that part of the journey has started. We needed to instantiate our infrastructure in all of these cloud providers. And now we're working with them to, hey, I can make your application so much better using our storage alongside your stuff. And so you'll see us make announcements of that over the course of the next 12 months, right? And we're super excited about that.
And then the third is technology is great. Go-to-market is equally important to build a competitive moat. And we have a lot of engagements with the hyperscaler sales teams. We are starting to work with their professional services teams around Client Migrations, Customer Success, Client Expansion and Industry Solutions. So there's lots of stuff to do, and we're excited and we continue to do that work.
And maybe this is a good opportunity for me to ask you one of the questions that came in from investors on this front. just in terms of how to think about how competitive the market is for talent related to cloud services itself. And when we look at some of the newer competition that's coming into the industry, like the VAST and Weka's of the world and their willing intent to sort of try to encroach on your leadership in the cloud services side. What are you finding in terms of your ability to sort of [rehire] and retain talent relative to cloud services specialization?
Yes. I think that we have a super strong talent pool. I think that we have continued to evolve our talent pool as the business has evolved. So we had a group of people who started our journey in cloud. They were not the right people to scale our journey in cloud. We have really good talent to do that.
I think that NetApp's culture has been a strong point for us over 30 years, that we allow people to innovate, to experiment without fear of failure. We have people from diverse backgrounds. We have a lot of talent from the hyperscalers at NetApp because many of them started working on the other side of the fence and then said, hey, I have more opportunity to make impact coming here.
You saw the announcements of our Chief Product Officer, who was the person that built the Salesforce Genie platform was the Chief Technology Officer at Zscaler. We had a new CFO who came to us from Western Digital. So we feel good about our ability to get the talent we need for the journey -- the phase of the journey that we're in.
Yes, sounds fair. Before I move to AI questions, AI-specific questions, one more that's come in from an investor. And the question is, can George comment on whether the Big Beautiful Bill and the ability to depreciate CapEx fully in 1 year for tax purposes will drive any additional customer IT spend?
We are waiting to see what the impact of the Big Beautiful Bill will be in our customers. I think there's always sort of 3 things that drive customer behavior. The first is their view of macro, which drives their overall posture on spending. And so IT is a part of that, right? And so that's the first.
The second is, can they get competitive advantage? Or do they fear having the opposite happen to them if they don't make an investment. So I think that AI is the new thing. Cloud was the thing a few years ago, continues to be an important part of the consideration. Cyber is important. And so we are positioned alongside those growth drivers. And then we're waiting to see what all the impacts are as people understand it, what that posture is.
Okay. Great. Okay. So let's maybe move to AI. Maybe starting with sort of what you're seeing from your enterprise customers and more specifically in terms of what their requirements are as they're thinking about sort of their -- how their AI infrastructure will look? What are you hearing from them in terms of what their storage needs might be? What drives your confidence that you have the right portfolio to address that?
Yes. I think broadly speaking, in the AI journey, the first phase of the AI journey, which is still ongoing, was primarily about, I want to get core technology built, right? This was in the AI, in the Generative AI world, really the large language models. And that work is ongoing. And that's where the bulk of the AI investments have been made.
The second phase of the journey was I want to integrate AI into the consumer applications, right? This is, hey, I'm going to make AI smart search like Google, I'm going to integrate that with AI capabilities and maps and so on. And it's similar to how iPhones happened, right? iPhones happened in the consumer market and then came to the enterprise. What we see going on in the enterprise is really nobody is trying to build a foundation model. That's way too expensive and frankly, no advantage.
I think now what we see is the application of pretrained AI models with companies' data. And there's a variety of things they need to do to make that happen. That whole idea is called inferencing. And there's underlying terms like RAG and this is a Graph RAG and all this stuff. But just think about that as inferencing.
In inferencing, having high-quality, well-organized, unified data is super important. If you look at Predictive AI, it really worked on structured data like databases or tables and things like that. Generative AI works on unstructured data, documents, videos, audio. And then Agentic AI works on unified, structured and unstructured working together so that you could have a complete view of a business problem.
We feel really good about our position in the AI market for 2 reasons. One is we hold a huge amount of the data that customers need to apply to their AI models, right? Because that's generated through their operational applications. So for example, you go to a hospital, we hold all the medical images, and we are the platform for Epic, for example. And so when a customer says, hey, I want to use GenAI or some advanced multimodal application to look at which patient has cancer or which patient has COVID. We are the incumbent.
The second, as you will see, we have a whole range of super exciting announcements at our Insight Conference, which will give our clients the ability to extract a lot of knowledge from their data that sits on us. And so I would just tell you, come to Insight, we're going to shock the world.
Okay. Maybe just another one. I mean, we are early in this cycle, but what we've seen till date is related to AI, storage has seen less of an up demand or uplift relative to any particular compared to compute, right, which has seen much more of an uplift. I mean part of that would be that some of your enterprises might be starting their journey on AI in the public cloud.
So one, like how do you think about the magnitude of benefit? And the timing of the benefit from AI to NetApp as well? Like do you expect that you're benefiting right now or more early on, the benefit is on the public cloud storage piece of your business related to maybe hybrid cloud and the on-prem infrastructure benefits later? And how do you think about the magnitude on each of them? Like where will enterprises eventually land more in terms of their AI infrastructure focus?
Yes. I think, first of all, the predominant build-outs of AI have really been for training, right? I think if you look at the vast amount of compute, it's really for training foundation models, for improving the ability of foundation models, to do multimodal and a whole range of other things. I think in aggregate, however, there will be more growth in compute than storage. I don't know whether what the long term, meaning 5 to 10 years out view. But if you look at a 5-year out view for a mature business, right, like our FlexPod converged infrastructure business, which is more for enterprise applications, is typically a 50-50 split between compute network and storage, where storage is 50% of the spend, right?
But that's in the mature enterprise application space. I don't know what the sort of the long tail will look like. I think with regard to storage for enterprise AI, we want to capture it in both places. We want to capture it in cloud. We want to capture it on-prem. You're correct that some of the data science experiments are happening in public cloud, where the data science team doesn't know the IT team, they want to start on the public cloud.
We have seen some of our public cloud solutions being used for AI. We have customers that spoke at our conference last year. There'll be more at our conference this year that talk about that. We also have clients in our enterprise business. We talked about 125 wins this year for Q1 compared to 50 wins last year, where it's split between data lakes, which is really how do you unify your data before you do inferencing. We had some sovereign wins for training or fine-tuning foundation models, and we had inferencing. And it was, I would just say, roughly 1/3, 1/3, 1/3.
Okay. Okay. Got it. One of your competitors, I guess, we can sort of say, Dell has been talking a lot about parallel file systems, and they've talked about it in the context of Project Lightning that they're working on. Can you just sort of make -- I just want to make sure we understand sort of where NetApp stands on that front? Why are parallel file systems important? And what is NetApp's offering on that front?
Yes. I think that the idea that AI has is to speed up access to data so that you can feed it to the GPUs, you parallelize access to the data. And where you -- in the disk drive, hard drive world, you had a construct called a parallel file system that essentially had a series of independent storage nodes connected into each of them paired to a compute node and this file system striped across all of them. It is a very complex technology.
You have a lot of work to be done to load balance it, fail over when the system gets into trouble and you have to troubleshoot, it is supremely complex. And as a result, parallel file systems have stayed a very small part of the total market. It's typically been in the high -- sort of the legacy high-performance computing world, the labs in higher education, a few supercomputing environments.
As flash has grown, what you can see is sort of a much more advantageous sort of next-gen architecture is what's called disaggregated storage, where you have the same idea of multiple compute nodes that can access in parallel storage and the storage is connected across a really high-performance network fabric to those compute nodes.
And so what it does is it gives you very, very close to the performance of your -- of a parallel file system, but vastly simpler and vastly more efficient. And so I would just tell you, come to Insight. We'll talk about our approach to providing very high scale distributed systems to clients.
Yes. Got it. And yes, I think definitely looking forward to Insights and the announcements there. Maybe just delving a bit deeper into sort of what the inferencing infrastructure for some of these enterprise companies look like. I mean there's always the concern that as they ramp, as enterprise companies ramp their infrastructure when they start planning around the inferencing workloads, they typically do budget in dollars and that starts to cannibalize some of the traditional storage spend.
So one, maybe if you can share any other thoughts. You talked about the data lake sort of is the stage there. Most enterprises are in terms of working on data lakes. But sort of where do you see the real sort of inflection in terms of storage needs coming from? And then secondarily, as we see that inflection, do you see a pullback in some of the traditional storage use cases just because of the priority towards AI?
Yes. I think the trade-offs that clients make are always driven by their business priorities. I think that in general, what our approach has been is, hey, it doesn't need to be an either/or. You -- just like in cloud, people had on-premises and cloud, and they used to have 2 different silos, and we unified them into one architecture so that you could leverage the investments around people and technology and make your operating environment more efficient, meaning less spend and more agile, meaning more flexibility, right?
We are doing the same thing for AI, where we are saying, hey, to use AI with your -- the data that is continuing to grow in your operational environment, we will help you bridge that and make it much, much more efficient. So that's our pitch to clients. Hey, you don't need to have 2 different spends. You can take one and make it much more efficient.
Data growth comes from 2 or 3 areas. One is if a customer has truly distributed data and organizations that are just not able to work together, they usually create a data science or data analytics and AI team. And those people bring data together. It's a copy of the data, but they bring it to what's called a data lake. And a data lake essentially is the idea that you can bring multiple types of data into a single environment.
You can do it with NetApp storage without having to build a data lake. You can just do it on the storage itself by marking which data you need. But if your data is not organized, you want to create a second copy. So that's one. Second is, at the time of inferencing, you have to take your core documents or videos or audio and you have to create what's called a vector and a graph, which is basically a way that a large language model can understand that data.
And in some cases, this -- you're not going to do that for all of your data. You're going to do that for a subset. So let's say it's 20% of your data. That -- when you vectorize the data, the volume is typically -- our best estimate of doing it most efficiently is 5x growth. So that 20%, you will grow it. And you may not keep it forever, but you will keep it for as long as you're running the inferencing.
And then the last phase, which is still early is, hey, when people generate data, how much data will they generate? It's too early for me to speculate. In general, if you look at human behavior in the past, if there's a free resource, they tend to fill it up. And so marketing will create 20 copies of slideware that they need, right, just so that they can compare it and present it. So, yes.
Okay. Maybe the last question on the business side, just in terms of revenue drivers. Can you talk about the advantage in AI of already having a large installed base? Because I think on the unstructured data side, you and Dell have a large installed base already, but you're trying to do both, which is, one, sort of your installed base is an advantage, but you're also trying to win share by displacing some of the -- by winning with customers that are part of the Dell's installed base.
So how much of an advantage is it having a large installed base? And how sticky are customers on that front? Are customers in AI trying to use their primary storage supplier across their AI use cases? Or do you see opportunities to displace some of your competition on that front?
I think the displacing competition is really around their operating environment, right, meaning the applications that are driving the creation of the data. And I think there, we have several advantages to go after Dell or anybody else, right?
And so that's the primary displacement mechanism. In terms of the AI side, it's new wallet that we or Dell might compete in our installed base, right, or their installed base. I think there, it's so much easier for a customer to be able to bring AI capabilities, meaning all the software capabilities we're working on to their existing data estate rather than lift and shift and copy it over.
I would say that when you have a database or what's called structured data, it's easier to do that because it's much smaller volumes. A giant database is probably 10 terabytes. If you go and look at a giant file, it could be multiple times that. So the volume of data you have to move around is much, much larger in unstructured data. And therefore, it's much easier if you can do it like we are going to show to bring AI to your data rather than copy your data to your AI.
Got it. Okay. Maybe now moving to -- actually, before I do that, let me take this investor question. The question is pretty short, but I'll let you sort of talk about the partnership here. The question reads, does NetApp work with Nutanix? But -- so maybe just sort of outline the partnership you have there? How material do you think it will be?
We have common customers with Nutanix. And I would just say stay tuned for upcoming announcements. Nothing to say at this point. But our approach is to work with all the hypervisor vendors north of us, right? So we already work with Proxmox, VMware, Hyper-V, Red Hat, OpenShift. There's a long list. And so our approach is to work with everybody. And so if we don't have something today, stay tuned.
Okay. Okay. Moving to margins. So I was looking back at the sort of last decade and so gross margins have gone from, I think, 61% to 71%, largely over this time period that you've been CEO. But maybe talk about as you sort of look forward, what do you think are the long-term margins that the company should be hitting maybe both on the gross margin side and more specifically in the operating margin as well, where you consistently continue to sort of make progress pretty rapidly on that front.
I think the broad shifts -- maybe I can just go through the elements of gross margin. I think our cloud business, which is growing significantly faster than our on-premises business, it's 10%, but it's growing at 33% CAGR in Q1, right? So it's a fast growing number, operates at -- it grew at 33% year-on-year in Q1. It is the first party, right?
The cloud business overall reached north of 80% margin. And we said that our target range would be 80% to 85%. So the mix of that business continues to push upward in terms of software. The depreciation that of the hardware that we put into Microsoft data centers continues to come off the P&L. And so we feel good about the trajectory of that business to get to the top end of the target range. I think the most important thing for us to do there is to grow it, right?
The second element, professional services, it's a small number, but the growth in professional services is through Keystone. Keystone clients go through a trajectory that starts with lower margins, but as they go through their tenure, that goes up and to the right. And so you should see that business as Keystone grows as a percentage of the professional services business, the margin should move up over time.
Support is a big number. It's growing in the low single digits. Its margins are north of 90%, 92.3%, I think, was the latest number, and it should continue to stay there. In terms of the product gross margins in the hybrid cloud business, our target range was mid- to upper 50s. And our view of that is that it continues to shift towards flash, which is a higher margin than this. And we are continuing to add more software value into that portfolio. So that's kind of the puts and takes on gross margin.
Operating expense is a piece of the equation that we manage in a disciplined fashion. We have typically managed it to grow at half the rate of revenue growth. And so I think that gives you the puts and takes on gross margin and operating margin. What we operate the business as at is to really drive gross profit dollars because we have, as you can see, been super disciplined on OpEx. And so if you can drive gross profit dollars, the incremental dollars convert to income and cash flow at a very high clip.
Okay. Last one from my side. Just M&A and rank order, maybe sort of give us the rank order in terms of where M&A sits in your priorities? And when I particularly look at the number of new companies trying to enter the market here, how do you think about the likelihood that there's a wave of consolidation in the near future to sort of return this industry to sort of where its usual sort of 3 or 4 sort of large participants?
Yes. I think overall, we have a -- when we look at capital allocation, we said we -- dividends are the first call on capital returns. We typically run that about 40% of the total number. And then we split 30% of the total cash generation. And then the remainder, we split between returns to shareholders through buybacks or targeted M&A.
Over the last few years, we have not done M&A. We've really focused on returning all of free cash flow to shareholders. Sometimes we have done more than 100%, sometimes it's around 100%. But generally, we've returned all of free cash flow to shareholders. I think that when we look at the market, the on-premises storage market, I think that it's a mature market with a lower growth rate and customers wanting to consolidate how many vendors because they just want simplification, they need to unify their data. And so that customer behavior generally tends to market consolidation over time.
Okay. Okay. All right. Great. I'll wrap it up there. This is great to get your insights in terms of the industry as well as NetApp. So thank you for the time. Kris, thank you as well, and thank you to the audience for tuning in as well.
Harry, you should be okay to wrap up the call here. Thank you, George.
Thank you, Samik. Thank you for having me.
No. Thank you.
Thank you, everyone. This concludes today's webinar, and you may now disconnect from the call.
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NetApp — CEO Spotlight Series
📊 Kernbotschaft
- Marktbild: NetApp sieht Public Cloud, Flash und Künstliche Intelligenz (KI) als die treibenden Trends; Kunden bevorzugen zunehmend OpEx(Betriebsausgaben)-Modelle und vereinheitlichte Dateninfrastrukturen.
- Geschäftsmodell: Ein einheitlicher Software-Stack (eine Code‑Basis) plus das Keystone‑Consumption-Angebot sollen Wachstum, Margen und Wiederkehrerlöse stärken.
🎯 Strategische Highlights
- Portfolio‑Fokus: Drehung auf Flash, Cloud, Block und KI; All‑Flash ist jetzt Kernbestandteil des Angebots, C‑Series/ASA ergänzen Preisbänder.
- Go‑to‑Market: Konzentration auf große Märkte, Rückzug aus ~19 Ländern, JV mit Lenovo für China sowie intensivere Hyperscaler‑Kooperationen.
- Operating‑Disziplin: OpEx‑Wachstum deutlich unter Umsatzwachstum; Operating‑Margin historisch von ~7% auf >25% verbessert; Dividenden und Buybacks Priorität.
🔭 Neue Informationen
- Konkretes: Cloudumsatz bei ~10% des Gesamtumsatzes, zuletzt +33% YoY; Cloud‑Bruttomargen‑Ziel 80–85%; Keystone wächst in TCV (Total Contract Value) und unbilled RPO (Remaining Performance Obligation).
- Geheimnis: Bedeutende KI‑Ankündigungen werden für die bevorstehende Insight‑Konferenz angekündigt; Details wurden noch nicht offengelegt.
❓ Fragen der Analysten
- Lizenz vs. Abo: Management betont Kundenorientierung statt Zwang zu Subscriptions; Support und Cloud sorgen bereits für hohe Wiederkehrerlöse (~40% des Geschäfts sind Support/Cloud).
- NAND‑Risiko: Preisvolatilität wird über Lieferantenverträge und Multi‑Sourcing gemanagt; NAND macht nur ~30% der Systemkosten aus, Preisänderungen werden meist durchgereicht.
- KI‑Timing: Nachfrage für Training (Compute‑getrieben) dominiert aktuell; NetApp sieht kurzfristig mehr Impact in Cloud‑Workloads, langfristig auch on‑prem für Inferenz und Data Lakes.
⚡ Bottom Line
- Relevanz: NetApp präsentiert sich als ausgeführter Konsolidierer mit klarer Produkt‑ und Go‑to‑Market‑Strategie; Margenhebel durch Cloud/Keystone und einheitlichen Software‑Stack ist real. Wichtige Beobachtungspunkte: konkrete Ergebnisse der Insight‑Ankündigungen, Nachfragezyklizität und NAND‑Preisentwicklung.
NetApp — Goldman Sachs Communacopia + Technology Conference 2025
1. Question Answer
So hi, everybody. We'll go ahead and get started here. Welcome to the NetApp fireside chat at the Goldman Sachs Communacopia and Technology Conference. I have the privilege of introducing Wissam Jabre, the Executive Vice President and CFO of NetApp. Wissam joined NetApp in March of this year from Western Digital, where he served as the CFO for 3 years. Prior to Western Dig, Wissam was the CFO of Dialog Semiconductors and served in various senior finance roles at AMD and Freescale.
My name is Kath Campana, and I'm a member of the IT hardware team here at Goldman, we have about 35 minutes for today's presentation, inclusive of audience Q&A. And before I begin, I do have a safe harbor to read. So NetApp asked me to read their safe harbor today. Today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainties. Actual results may vary -- actual results may differ materially from the statements made today for a variety of reasons described in NetApp's most recent 10-K and 10-Q filed with the SEC and available on their website at netapp.com. NetApp disclaims any obligation to update information and any forward-looking statements for any reason. Thank you. Thank you for being here with us today Wissam. September marks 6 months since you joined NetApp as CFO.
Now that you've gotten some time to get a little bit more comfortable and get a look under the hood. We'd love to know if there's any opportunities that you would highlight as most exciting for you at NetApp.
Thank you so much, Kath, and happy to be here. Look, the -- okay. With respect to NetApp. It's been a great 6 months, a great company, fantastic leadership team, a lot of opportunities. I think we have awesome technology as well as great go-to-market organization. All the opportunities that we're pursuing from a growth perspective are exciting for me whether our focus on all flash and our continued -- making good headway there, in addition to within all-flash obviously, continued focus on block as well as cloud business.
And of course, the -- all the upcoming opportunities on AI. Everything is -- I mean, all of these growth opportunities are exciting for me. I would say it's the -- yes, I wouldn't single one of them out. They're equally exciting, and we're focused on them.
You reported earnings 2 weeks ago for fiscal 1Q '26. Before we dig into some more strategic questions. Could you do a brief recap for the quarter and make sure there's any highlights that you'd wanted this audience is familiar with?
Sure. We ended Q1 with revenue slightly, and EPS, slightly better than the midpoint of our guidance for both numbers. We did, as expected, see some good strength in the U.S. enterprise that offset some softness in the U.S. public sector and EMEA. We saw the -- both sides of the business, both segments where hybrid cloud and public cloud grow year-over-year. When we adjust the public cloud business relative to -- with respect to the divestiture we did in Q4, the growth there was around 18% grade growth with a very high-margin business.
We continue to see good also the performance on the operating margin. And then from a cash perspective, we didn't have a Q1 cash sort of record free cash flow of around $620 million, which is really great, continued to deliver down our capital allocation where we wanted basically return up to 100% of free flow to our shareholders in the year. So we did our part in Q1. And the last thing I would say, we also had ranked number one, exiting calendar Q1 '25 in the all-flash market as ranked by -- as published by IDC. So all in all, good, I would say, a solid start to the year.
Maybe one more high-level question. We can get into some of those strategic growth drivers that you talked about at the top. But company has long talked about ONTAP is the backbone of your unified data management capabilities. Why is having a unified operating system, a competitive differentiator for NetApp? And why is that something that your competitors aren't able to do because their portfolios are either built through M&A or otherwise have disparate operating systems across their products.
So I mean, the way to think of ONTAP, it offers unified data management and protection to our customers, whether they use any type of data, whether it's file, block or object stored on -- whether it's stored on-prem or on-premises or in the cloud and in any location. So that's really a key differentiator. When you look at sort of ONTAP with respect to our -- what it differentiates for us or what the opportunity it presents to us is the fact that it's really -- we have a single operating system across the board.
And so that, in some ways, allows us to scale our R&D investments as well. So all in all, it's a great win for our customers, great value for our customers, but also value for us as well.
So maybe turning to each of those 4 strategic growth areas that you mentioned in turn, flash, block, cloud and AI. We'll start -- we'll do them in that order, but maybe starting with flash. Obviously, there's a secular benefit to flash as we transition, particularly at the midrange from more legacy hard disk type of storage media. But can you talk about the transition that's happening at the midrange? And when you think flash will be more competitive for some of the more nearline storage opportunity?
So we have a good opportunity in all-flash. And as I mentioned earlier, we did basically have a #1 market position in calender Q1. The way to think of the -- sort of the way to think of the storage market in general, all-flash in particular, is growing at a faster pace than the overall storage market. So that presents really a good opportunity. Over the last few years, we've seen a continuous transition from basically the midrange 10K HDD type systems towards the more QLC SSD-based systems simply because the TCO and the cost differential in that -- that the QLC offers allowed that to sort of happen.
It became more economic for our customers to do that and for us. Now when it comes to nearline, the cost differential between flash and hard drives is still significant. And so when it comes to secondary sort of storage needs, we still think that the cost differential is high and nearline is probably still going to be HDD focused for some time.
So I wanted to talk about the IDC leadership that you mentioned earlier in the all-flash category in the most recent quarter. What do you think has been driving NetApp's above-market growth in all-flash? And how sustainable do you think this market share leadership position is especially as you have other competitors either distracted or increasingly investing in their all-flash capabilities as well.
Yes. I mean when you look at the strength of our portfolio over the last couple of years, we've really had really good focus on strengthening our portfolio, and it's not only focused on the unified side of the house, but also we've had some block optimized portions of the portfolio. And so if you look at the product set, it does give us a really good differentiator to be able to compete effectively in the all-flash market, and we've managed to really compete with other all-flash peers as well as hybrid flash competitors and sort of gain share in that space. The goal for us is to continue to be as competitive and make sure that we continue to push our portfolio to maintain or gain our position.
So on the block appliance, I think ASA is the appliance that you introduced a few years ago for dedicated block storage. Why did NetApp feel there was a need for a dedicated appliance for block as opposed to the differentiated unified kind of opportunity that you have in the rest of the portfolio. And how has that platform been? Obviously, it's been contributing to growth, but what other opportunities do you see for that dedicated block platform going forward?
Yes. I mean, prior to us, we've always sort of had some presence in log. But we were sort of -- I mean market share perspective, where we're underpenetrated relative to our position in PHY. And we've had -- we've used our unified products to compete until we have -- we developed ASA and now we have a much more block optimized product that can compete effectively in the block storage space. The reason it's valuable to us. It's because, as I started off, we're underrepresented there, and that presents -- that by itself is an opportunity for us to grow our presence and grow our revenue at a slightly faster pace.
We do have a really good product in ASA that's really high performance, and it's really very much suited to the block market segment, and that should allow us to improve our market position there as well.
For people who may be less familiar with the different requirements of a block or file system, why does it have -- what's the advantage of having a standalone block appliance as opposed to a bundled solution. What can you do better or more cost effectively with the stand-alone plan?
Well, it is -- once -- if the product is more suited towards a certain market segment, it allows us to offer a better solution to our customers that is much more cost-effective, higher performance or more performance suited to the market segment as opposed to necessarily using a product, our product portfolio traditionally has been much more focused on file. And so it wasn't as necessarily optimized, I would say, for block. And so it does help us to to gain much more traction in the market. .
Yes. So let's shift gears to public cloud and maybe talking about file as well. How has NetApp's legacy as a file vendor helped with your first-party relationships with the cloud providers, Azure, GCP, AWS. And again, maybe for those who are less familiar with what the product suite looks like, what is NetApp's offering in these in the first-party cloud marketplace?
Yes. So look, our engagement with the hyperscalers is more than a decade old, we started that a while back. And the -- throughout the years, we managed to really be able to offer basically the hyperscalers offer our software ONTAP as part of their own native offering. So it's a native storage solution offered by the -- and labeled by the hyperscalers. And so that allows us to, in many ways, to continue to monetize ONTAP through different means. We've managed to do it through the hybrid cloud. And we can do it if we can do it using other people's appliances that sort of allows us to scale the offering and the -- our software across different sort of market segment as well.
We -- as far as I know, we're pretty much -- we have a unique solution there with respect to our public cloud services business. And it allows us, as I said, to sort of continue to offer our ONTAP to another set of potentially an extended set of customers that typically wouldn't be buying it through the on-prem side.
And what about NetApp has allowed you to have that differentiated first-party relationship.
I believe it's really related to the performance of the product as well as -- its I mean ONTAP, not only does it offer unified data management, it offers great enterprise-grade protection and thus offer great reliability as well as multi-protocol support. And so it's basically many of the characteristics that sort of differentiates it with respect to other storage software solutions. .
And you mentioned this earlier as a headwind, just for the public cloud segment from a growth rate perspective. But last few quarters, NetApp has narrowed the scope of its public cloud segment with the divestiture of Spot and also CloudCheckr. So can you talk about why it makes sense to narrow the scope of what you're looking to achieve in the cloud portfolio and in the public cloud portfolio? And why this is the right mix of business where you are right now?
Yes. So when you -- when we look at the public cloud segment, we've made a decision to refocus the business on first party and marketplace. And so that's what we've discussed so far with respect to the engagement with the hyperscalers and how our software is sort of a native software solution that's sold natively. By doing that, it did allow us to really focus on. So we basically have a small portion of services in addition to first-party marketplace. And by doing that, it allowed us to sort of grow the business at a faster pace as well as when you look at the profitability of our public cloud segment, we just increased the target range, the gross margin target range for that business from 75% to 80% to 80% to 85%. And so all of these were basically facilitated by our refocusing on first-party and marketplace primarily. .
And maybe jumping ahead a little bit, but talking to the guidance raise that you mentioned on your outlook for public cloud margins. Encouraging to see that raise in long-term outlook. And is it just the mix into more first-party that's going to get you from the 80% that you've reported a couple of weeks ago to that 80% to 85% range or the high end of that range? Any other drivers in public cloud that should help gross margins?
Yes. If you look at the business itself, there's really a couple of key drivers in that. There's a certain element of depreciation roll off. As we sort of started up the business, there was an investment in assets that was done earlier to sort of get the business going. And so that starts to -- the depreciation on those assets starts to roll off, but also the software content of the revenue higher, meaning there's more revenue coming from software-only solution as opposed to software attached to hardware. So those 2 dynamics help improved the gross margin over time. Now that doesn't mean that we may not continue to invest in some assets or necessary to deploy some gears or appliances to drive the revenue.
But when this happens in the future, we expect the equipment to be attached to also revenue with it. And so that's sort of what gives us confidence there. The 80% to 85% is a good range for us to target from here.
And is there any time frame we should be paying attention to for that depreciation of the investments that you made for one of your hyperscaler partners?
Not necessarily. I mean this is -- we don't necessarily break that out. And so we look at the public cloud segment as sort of -- it's part of our services. We look at it as one of business segment, and we look at it's gross margin attached to it as also the margin for that segment.
Okay. And last but not least, I want to touch on NetApp's AI opportunity. So encouraging to hear last quarter that you closed 125 AI infrastructure and data lake modernization deals. Maybe starting at a high level, what role does storage and storage appliance play in AI initiatives for enterprises more broadly? Why do they need to modernize their data stacks in anticipation of AI workloads.
So when it comes to AI applications, the data storage requirements are more sort of complicated and relentless in addition to having the need to have unified data. There is a need for the ability to search and organize the data is very, very high, huge volumes of it. And so this is where our AI solutions are really very much geared towards allowing our customers to do that. When you look at data, or unstructured data is pretty much the fuel of AI. And NetApp is very much the unstructured data company. And so we do have a great strength in the space. And when it comes to AI, and it's not only about performance and scale with respect to enterprise storage.
It's also about the ability to provide that the unified data management, enterprise-grade protection, very high reliability, the ability to sort of manage the data across different locations cut through the silos, be able to manage the data, whether it's on premises or in the cloud. And all of these requirements are very well served by our solutions, our AI solutions, so we're very well positioned to benefit from that and to help our customers through transitions to enterprise AI.
Thinking about NetApp's go-to-market in the AI space, you have a number of partnerships that you've discussed in public settings with NVIDIA, Intel, Cisco is in there as well, just thinking about players across the broader AI ecosystem. Should we think about the role of partnerships and go-to-market for AI? And is that different than the way NetApp goes to market with its kind of traditional enterprise storage solution.
It's -- not necessarily. We view all of these relationships as providing more options to our customers to allow them to sort of partner with tried and tested great partners. And so as we think through the various engagements, we have different architectural designs, sorry, references that allow our customers to rely on, not only our solutions, but also partners that have -- that -- where the solution is tried and tested. So it does basically provide our customers more options when it comes to partners.
So shifting gears to some more financial outlook oriented questions. When you reported earnings 2 weeks ago, you guided to 2% growth for next quarter and 3% growth for the full year on the top, implying that we should see an acceleration in the top line in the back half of the year. What are the underlying assumptions from a demand perspective across customer verticals or regions? I know you mentioned some weakness in public sector, but good strength of large enterprise. What are the expectations for 2Q and really the back half of the year from a demand outlook.
Yes. I mean, look, we do operate in a dynamic environment. We talked a little bit about that. There are some -- there's certain macro uncertainties out there that we navigate through. But when we look at Q2. Q2 tends to be a stronger quarter when it comes to U.S. public sector, it coincides with the federal fiscal year. And when we look at the -- at sort of the progression with the rest of the year, we're exposed to really the all-flash market, where we know that we're seeing better growth than the rest of the storage market. We also are adding the capacity when it comes to our go-to-market capabilities that we talked about, and that should allow us to see some good traction in the second half as well as really focused on some large deals that are sort of in the pipeline. So when you put it all together, it sort of forms how we got to the numbers.
Maybe on the go-to-market and the investment in your sales force. There was a number of strategic senior hires in North America that were announced in the last couple of weeks. And it would be great if you could dig into what your priorities are for your sales organization and what capabilities do you feel like you need to enhance with these appointments, and it sounds like there's some outlook for the productivity of those new salespeople to really start contributing to growth in the back half. But typically, what do you see as the kind of time to productivity for some of these investments?
So look, the -- I think maybe this is more of a general approach to how we sort of operate in the company. We're always looking to make sure that we have the best talent and the best people driving basically the best outcomes. And so this is part of the continued focus on making sure we drive good outcomes and when it comes to the second part of the question, by the way, this applies not only to the go-to-market organization. This applies to basically everybody at NetApp, where -- and all functions when it comes to the second part of the question.
With the typical -- we typically see around, let's say, want to maybe closer to, let's say, 1 to 2 quarters before we start seeing more productivity from the go-to-market side. From the time we start deploying resources.
Very helpful. Maybe shifting back to what you mentioned earlier around some of the softness in public sector. And you noted the seasonality of 2Q being a particularly strong quarter historically for public sector. How should we think about broader trends in federal spending or kind of a down year in federal spending on NetApp's performance for fiscal 2026? And how conservative of a view have you taken on public sectors contributions to kind of the overall market for the rest of the year.
So for us, the U.S. public sector is typically around 10% to 13% of our revenue, give or take, depending on where we are in the year. And look, we continue to -- because this is a market that we continue to focus on. But we're looking at focusing on the pockets of that space where we see more opportunities. And so that's how we think of it going forward.
And so what are some of the pockets where you're most exposed? Is it more of an issue of state and local or federal or what feels like a more stable area within the broader U.S. public sector segment for NetApp to be doubling down on?
Yes. I mean we typically don't break it out as such. Obviously, all the various segments are important to us. And -- but what we're doing given the current government is we continue to focus on the areas that present the most opportunities for us.
I want to call on your experience at Western Digital and ask about some of the volatility we've been seeing on the memory side. So maybe first, what is your read on current memory pricing? And then I would love to know now that you're in this seat at NetApp, how you are managing that utility? Is it different than what you would have expected when you were on the other side of the equation? And how you're thinking about things like strategic purchases and planning for kind of changes in pricing?
So I would say even when I was at Western Digital, I don't think I ventured predictions on NAND prices. So I'm not going to start doing that now. It's anybody's guess. But the way we look at, at least at NetApp, the way we manage it is we have a very capable supply chain team, supply management team that continuously monitors the commodity prices. And if we see an opportunity for us to lock in prices, we do that. And we do that over a period of time just to basically allow us to work better visibility for our cost structure.
And in some ways, it gives us a bit of an advantage on the cost side. This is how -- when we look at the rest of the year in terms of product management, sorry, product gross margin. This is what gave me confidence to say that I think product gross margin should be in the mid to high 50% for the rest of this fiscal year. That's because we've locked in some prices. And so that gives us a bit more visibility over the next few quarters.
Yes. That's very helpful. Maybe one last question, and we can turn it to the audience to see if there's any Q&A. I want to talk about Keystone, the storage as service platform that NetApp has shown some very strong growth. I think you called out 80% year-over-year growth in Keystone next -- or last quarter. What is really driving Keystone adoption in your view? And is there anything we can think about in terms of changes in the macro environment or like the rate environment that may influence the customer's decision to choose, a, as a service consumption model versus a purchase consumption model or more of a CapEx type purchase.
The -- look, at the end of the day, it's -- we're happy to serve our customers regardless of which purchase they want to make, whether it's a CapEx model, which is sort of our product as is, that goes out as a hardware with the software attached to it and the support over time or whether it's one of the 2 other options. Our public cloud business, which is mostly consumption-based or as you mentioned, Keystone, which is our storage as a service offering. The purchasing decision depends on the use case and the customer's choice.
And in some cases, also it depends on the size of the customer. Some customers have the ability to sort of they want to -- they feel that they by spending the CapEx upfront, they would sort of benefit from the appliance over time and don't have to sort of have that perpetuity in terms of the consumption. And some customers prefer a model where it's like where they want to pay as they go. And so that depends on their own circumstances and their own choices. When it comes to Keystone. Yes, I mean the numbers we quoted, you quoted are what we said in Q1 when we looked at year-over-year, Keystone was up -- revenue in Keystone was up 80% in Q1 '26 versus Q1 '25, which is really a great growth.
When you look at the unbilled RPOs, the unbilled RPOs at the end of Q1 where, in total, more than $400 million, I think $415 million if my memory serves me right. And the large portion of that are related to Keystone. So it is really a leading indicator with respect to where this business is going. It's growing at a very good pace. We still don't break it out as just by itself, but it is a very high-growth business for us and is doing well.
Maybe I'll open it up to the audience, see if there's any questions for Wissam. I have plenty more, so I can keep going. Maybe talking to your capital allocation framework. You mentioned at the top of the call, aspiring to return up to 100% of free cash flow to investors this year, but you're also clearly making investments both on the R&D side and then in your sales force. So what is the framework that you're using beyond as you balance both shareholder returns and investments back into the business?
From a capital allocation framework, obviously, we want to continue to invest in the business, whether on the R&D front to invest in the great products that we put out there in our road map, or on the go-to-market area so that we can continue to fuel the growth in the top line. And so both the ability to invest in the business and return capital to shareholders are very possible, given the highly cash generative nature of our business. And that's what we're doing. And so this is why we're comfortable with our ability to continue to invest in a very competitive way, very sort of high return that project in addition to returning up to 100% of capital to our shareholders for the rest of the year.
And how do you think about M&A within that capital allocation framework. You made acquisitions in the past, but it seems like some of them are also being divested at the same time. So how does inorganic growth factor into some of the capabilities that NetApp wants to further invest in?
I mean, as part of our capital allocation, as I said, obviously, investing organically in the business is our top priority, earning capital to shareholders is also a top priority. And if there's any sort of value-enhancing M&A tuck-in type M&As, we wouldn't be considering as well.
And maybe to close it out here in our last few minutes, can you tie it all together and talk to the key priority and strategic focuses that you and the rest of the management team are really focused on in the next 1 to 2 years, and how that factors into the longer-term growth outlook for NetApp.
So the focus is on the growth. And you said it. I mean our focus is really on opportunities that we see for us to grow the business. It's really the -- so continued focus on the all-flash market within that also in addition to that, and within that, the block segment of the all-flash market as well as continue to drive our public cloud segment. It's a business that has been growing at a very fast pace. We'd love to see it continue to grow at a fast pace and also focus on how and when to capitalize on the best way to capitalize on AI, we have great solutions that are really geared towards enterprise AI. And so we have really -- we're focused on being able to capitalize on that as we see more of the transition into inferencing a rack type of applications.
Well, thank you very much. It's been a privilege to have you here on stage and join us at the conference today. And yes, it's been great. Thank you very much Wissam.
Thank you, Kath. Happy to be here. Thanks for having us.
Thank you.
Thank you.
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NetApp — Goldman Sachs Communacopia + Technology Conference 2025
🎯 Kernbotschaft
- Überblick: CFO Wissam Jabre skizziert vier Wachstumsfelder: All‑flash, Block, Public Cloud (First‑party/Marketplace) und AI. Q1 lag leicht über dem Guidance‑Midpoint, Free Cash Flow ca. $620M; Ziel: bis zu 100% Rückfluss des FCF an Aktionäre. NetApp verweist auf IDC‑#1 im All‑Flash.
⚡ Strategische Highlights
- ONTAP: Einheitliches Betriebssystem für File/Block/Object über On‑Prem und Cloud hinweg; erlaubt Skalierung der F&E und vereinfacht Multi‑Cloud‑Angebote.
- Block‑Offensive: Dedizierte ASA‑Appliance zur Erhöhung der Marktanteile im Block‑Segment; gezielte Produktoptimierung statt generischer Unified‑Lösungen.
- Keystone & AI: Storage‑as‑a‑Service (Keystone) mit hohem Wachstum; AI‑Opportunity gestützt durch Partnerschaften (z. B. NVIDIA, Intel, Cisco) und Fokus auf unstrukturierte Daten als „Fuel“ für Enterprise‑AI.
🆕 Neue Informationen
- Public Cloud‑Mix: Fokus auf First‑party/Marketplace; Folge: langfristige Brutto‑margen‑Zielspanne für Public Cloud erhöht auf 80–85% (vorher 75–80%).
- Produktmargen: Erwartung für Produkt‑Bruttomarge: mittlere bis hohe 50er‑Prozentpunkte, gestützt durch Preisabsicherungen im NAND‑Einkauf.
- Keystone‑Indikator: Unbilled RPO (nicht verrechnete vertragliche Umsätze) ~ $415M Ende Q1, großer Anteil Keystone — Signal für wiederkehrendes Wachstum.
⚖️ Bottom Line
- Fazit: Der Fireside‑Chat bestätigt die bereits kommunizierten Prioritäten: Produkt‑ und Cloud‑Mix sollen Wachstum mit attraktiven Margen verbinden. Starke Cash‑Generierung erlaubt simultan Investitionen (F&E, Sales) und hohe Rückflüsse. Beobachten: Realisierung der Public‑Cloud‑Margen, Keystone‑Umsatzumsetzung und mögliche Volatilität durch öffentliche Auftraggeber.
NetApp — Citi’s 2025 Global Technology
1. Question Answer
Hardware, tech supply chain. Welcome to Day 1 of Citi's conference. Really happy to have NetApp's CEO here. We also have Kris Newton from the Head of IR for NetApp. And before we kick it off with some questions here, Kris has some prepared commentary.
Today's discussion may include forward-looking statements regarding NetApp's future performance, which are subject to risk and uncertainty. Actual results may differ materially from the statements made today for a variety of reasons described in our most recent 10-K and 10-Q filed with the SEC and available on our website at netapp.com. We disclaim any obligation to update any information in any forward-looking statement for any reason. Back to you, Asiya.
All right. Thank you, Kris. George, welcome again.
Thank you.
I know you've been doing this for a while. So we've been asking all our customers -- all our corporates here that are presenting. You guys just reported results. When you think about how the storage markets evolved relative to, let's say, the start of the year, there were lots of demand indicators, there were puts and takes to the macro, tariffs, DeepSeek, all that stuff. As you sit here today and you kind of reflect back on how things are different relative to a few months ago when you thought about the demand outlook, help us understand how you think about demand.
Yes. I think, first of all, thank you for having me. With regard to change in the overall demand environment through the course of the year, not a whole lot of change. I think there are some macro drivers that are driving caution in overall enterprise IT spending. Those are geopolitical uncertainty, the continuing wars in the Middle East and in Ukraine. a bit more clarity, but still a lot of uncertainty around tariffs and then the posture of various central banks on interest rates.
We are sharply focused on the parts of spending that are constructive. I think even in the last quarter, our enterprise business, meaning nonpublic sector business performed nicely. Those spending priorities in the enterprise are, in some ways, broadly correlated to getting ready for enterprise AI. It's unifying your data, accelerating cloud transformation, cyber resilience and modernization of your infrastructure using higher performance systems. And I think that we have taken share in all of those parts of the landscape.
And then as you think looking ahead, and I know you guys put out fiscal year targets, which you reaffirmed at your last earnings just a week ago. So maybe help investors think about what are the puts and takes to that end demand?
I think the end demand for the full year does not assume a radical change in the economic environment overall. I think if the demand environment, the macro signals to the demand environment get more constructive, it should be an upside to the current outlook. We also think that enterprise AI is still in the early innings of a 9-inning ball game. And so if the AI opportunity in the enterprise inflects substantially, then it should be an upside. I think overall, our view is we continue to be cautious about U.S. public sector.
I think that the second quarter of the year is historically our largest quarter for U.S. public sector contribution. In the second half of the year, the percentage of our overall business that's U.S. public sector should be less. And then on the other trends, we are #1 in the flash market. We've taken share for several quarters. We expect to continue that pace. And our cloud business has performed strongly, where our cloud storage business grew 33% year-on-year. So those are the demand patterns that we see.
Okay. And then maybe first, let's stick to the Hybrid Cloud and then you can talk on the Public Cloud. But on the Hybrid Cloud, while the macro hasn't been changed, you're continuing to see strong momentum on flash, which tends to be the pricier storage, right, relative to HDD-based storage, but there are obviously secular trends there. What -- given the macro is kind of mixed, what confidence that this is still an area that will continue to grow despite all the macro headwinds that exist out there with geopolitical uncertainty and federal pressure, et cetera?
We are accelerating share gains in the market. We are now #1 in market share. And I think broadly speaking, the storage and data infrastructure specialists are taking share from the big integrated system vendors like Dell and HPE. There should be no change in that trajectory over the course of the year. I think the second is, as customers are beginning to think about how do I use AI in my enterprise, they need to get their data ready. It's pretty common. I was with some of the large financial institutions here yesterday and their CIOs were telling me that the biggest challenge and opportunity they have is to organize their data to unify it so that they can use different models.
And I think to get an AI-ready data infrastructure, you need to deploy flash-based systems, and we can unify that data not only on our flash systems but across the cloud. And I think those are the key things for why we feel strongly about our Hybrid Cloud position. The market is really coming to us on what we said from the beginning.
Okay. And then if you can -- if you just double-click on that a little bit, like what are these workloads that you're seeing pulling the incremental, whether its data modernized -- data storage modernization or additional storage services that are needed for AI to have AI inferencing or training? Like what workloads are customers sharing with you or you're involved in these conversations and the sustainability of that demand as we start to see maybe perhaps broader enterprise AI adoption?
Yes. When we looked at enterprise AI, we had always said that enterprise AI was in proof of concept still in 2025 that in the back half of 2025, we would see the early adopters go from proof of concepts to real implementations. And then 2026 would be where a broader number of those clients would move there. We have seen strength across public sector, manufacturing, financial services and health care. And many of those are related to productivity gains. We're yet to see real scale implementations that drive revenue growth.
As examples, in automotive design, it's really about how do I build digital twins, how do I create an immersive digital experience in the car? How do I -- we talked about how do you build an autonomous driving system. Those are the things in manufacturing. In financial services, we have several examples of people unifying large number of documents so that they can understand better mortgage underwriting policies. In health care, for example, it's, hey, how do I do claims processing more quickly and better. There's software development across a broad range of industries and so on.
What they need from an infrastructure standpoint is they need to get all of this data well organized, ensure that it's high quality, have the right guardrails on the data. Some of them create a second copy of the data and what's called a data lake via the underlying storage for a lot of the data lakes. And in other cases, they just -- they don't need a data lake, they'll just unify it on our storage system and apply the large language models to that.
Okay. On the flip side, when you listen to some of the other vendors that are out there, not necessarily storage, but compute, it tends -- AI tends to be very lumpy. There are some quarters where you see this big expansion of growth and then there's always some kind of transition happening, and then growth sort of heaters down a little bit or it's just very lumpy. So help me understand like when you talk to your customers, what kind of visibility do you have? And is it as lumpy for you guys? Or perhaps you have better visibility, perhaps it's more smoother? How are you guys thinking about it?
It's a much smoother curve for us. First of all, our predominant focus is enterprise AI. So we have a much broader customer base that we work with. We have a lot of experience working on enterprise AI with predictive AI for many, many years before generative AI. So we kind of understand the cycle of procurement for those kind of opportunities. So I think the combination of, hey, much larger, broader customer base plus a more steady deployment pattern. You can see that, hey, they got to organize their data, they then have to apply cybersecurity and governance rules, then they want to generate vectorized copies of that data. So it's a more kind of predictable pattern. in the storage and enterprise AI market.
And then there's this view that AI storage or storage has not been a big beneficiary. I mean, of course, we can see the CapEx numbers from hyperscalers you can put in the enterprise neo cloud providers or enterprises like Tesla and xAI, Oracle perhaps in there as well.
And then -- but when you look at storage as a percentage of server compute, it's kind of like not grown as rapidly, whether I look at industry forecast, whether I look at your fiscal year forecast as well. Help us understand like do you see something that could suddenly accelerate the trajectory of growth from AI?
Yes. I think the commentary you made was accurate. I think so far, most of the work in AI has been around training the foundational models and getting them to be more capable, less hallucinations, able to understand broader types of data, multimodal use cases. In training, the storage landscape is actually fairly small. It's basically used as a temporal, what they call a checkpoint, meaning if the large language model fails, it can come back to an interim stage rather than go back to the start. And it's a pretty small amount of storage. It's almost an alternative to memory, right? For example, ChatGPT didn't create a second copy of the entire Internet's data, right.
I think as you go from training to inferencing and using enterprise data, there's more storage growth. In fact, we're not the only ones who said it, but our view of the market is 80% to 90% of the storage is actually in the inferencing part of the use case than in the training part. So most of the storage growth is going to come. I think the second thing there is the real value for people like NetApp is we have this giant installed base of data. And as clients want to use that data for AI, we have the opportunity to monetize it with a lot of software capabilities, guardrails, indexing, search, data lineage, a whole range of data services, which we will talk about and share at our upcoming customer conference.
Okay. And then you talked very positively about the flash performance and you've grown your share in the flash performance. And then -- so just if you can remind investors, what's driven that? How sustainable are those market share gains? And could we see further growth in those market share gains relative to other players who are maybe catching up now with some of their offerings?
Yes. I think we have built out a complete flash portfolio that combines high-performance systems and capacity flash systems on a price performance basis. And then we've also built what was called a unified systems portfolio, which we've always had, complemented that with a block storage specialized portfolio that these 2 address parts of the market that we could not address before and have driven strong share gains for us.
I think that if you look at IDC market data, we have grown share and are the only one in the top 5 players in the market who have grown share for multiple for the last 2 or 3 years. I think when I look out at the competitive landscape, our opportunity to take advantage of some of the disruptions in the market for example, VMware and Broadcom disrupting the hyper-converged systems market allows us to gain share at the expense of our -- some of our competitors as well as the growth of enterprise AI, us and Dell are the large share players in unstructured data, and it's sort of our game to lose.
Okay. And then remind investors again about -- when I sat at your Investor Day, you had talked a little bit more positively about your block offerings, right, which previously you haven't participated in. Why is that it's a new -- why hasn't NetApp been there before, but the opportunity is pretty sizable as you go after it. And that's been sort of the growth story underpinning some of your growth. So if you can help level set, where are you in terms of that block offering? How much more potential there is to continue to grow in that market?
Yes. We have had north of 20,000 customers who use our block storage offerings as part of a unified storage configuration, which means that you can consolidate file, block and object data on a single infrastructure. That was particularly helpful in the large enterprise where clients wanted to have a single unified platform to manage all their data. It wasn't as helpful in either smaller environments of that large enterprise and in a large number of the commercial market, which is midsized enterprise. And so we decided to build a tailored offering for that part of the market, and we're seeing good results. It's early, but we are seeing good results there.
Okay. Let me just ask the investment community here. If they have any questions. If you do, please raise your hand. We have one here, so we can get the mic to you.
Okay. Just want to ask a little bit about the margins, gross margin progression. Maybe you could talk a little bit about product gross margin. What's going on there? Why are you confident that comes back in the back half?
Yes. I just want to start by saying we operate the business to drive gross profit expansion less on the margin rate because if you look at our business over a long period of time, we have been able to convert incremental gross profit dollars to earnings at a very high conversion rate, given our discipline in terms of operating performance of the operating expense.
I think if you look at the 4 components of gross margin, company gross margin, let me start with cloud. Cloud has gone from the mid-60s gross margin rate to now we just raised our overall outlook to be in the target range of 80% to 85%. It's driven by an improving mix of software revenue growth and depreciation of some of our initial investments, particularly in the Microsoft cloud to come off our P&L. We have every confidence that the cloud should continue to grow at a faster clip than our Hybrid Cloud business and at a higher margin rate should be able to contribute more gross profit dollars as a share of the business moving forward.
In terms of professional services, that margin rate should also keep going up as our Storage as-a-Service offering, Keystone, which is a much higher contribution margin business than classic professional services grows as a percentage of the mix. Keystone grew 80% year-on-year this past quarter, and we should expect that to continue to grow as a percentage of our professional services business and overall company. Support is a big business. It's low single-digit growth, but it has very high profit margins, north of 90%, 92%. It's just stable. No big puts and takes on that.
And then on product gross margins, we said that we expect the product gross margins to trend back up in the second half of the year to our target range of mid- to upper-50s. The big puts and takes are continued shift in the overall mix to flash. It's about 2/3 of the Hybrid Cloud segment revenue, a bit higher than that in terms of the product revenue. So that mix should shift up.
The second is costs should get more beneficial to us on a year-on-year compare and even on the sequential compare. We have good line of sight into our cost structure for NAND in the second half of the year, and we should expect that to get better than it was at the start of this year.
Okay. Just on that one, George, I do hear about like NAND pricing. I mean, certainly, in our own internal city models. We talk a little bit about NAND pricing inching up. I think if you listen to NAND vendors, they do talk about as well supply-demand efficiency and better outlook after 1Q, which was pretty down. So just help us understand how that flows through and if -- how we should correlate like product gross margins? Or is there a correlation between product gross margins and just potentially higher -- slightly higher price NAND sequentially in the back half of this year?
Two comments on that. First is the predominant part of our value to clients is software. NAND is about 1/3 of our total cost of goods. And so we have a large amount of software that builds on that. We have the flexibility to pass through higher prices if they go up much higher than what we have modeled, and we do so periodically. That's been the history of the industry. And conversely, if it goes down, we pass that on to clients. Customers, importantly, budget in dollars. And so the fluctuations in prices don't really translate into more spending. It's just that they get to buy more capacity for the same dollars or less so. And then the third thing is we have long-term agreements with suppliers that in return for predictable demand gives us assurance on the cost structures that we have.
Okay. When you think about cloud, it's the Public Cloud portion of your business. It's obviously smaller than the Hybrid Cloud. It's growing at very strong rates. And I know there were some divestitures there. Just if you can remind investors how you're thinking about the Public Cloud portion of your business? What steps are you taking to make sure growth sustains here at these levels, excluding the divestiture? And then, of course, the margins on that are very, very accretive to the rest of the business. So what's -- how sustainable are those factors that would drive both top line growth and improved margin expansion?
Okay. There were sort of 3 things that I would share with you. The first transition in our cloud business was really a move from a subscription-heavy business to a consumption-heavy business. This was similar to the hyperscalers' own models. And because we work with them when they change their model from subscription to consumption, we naturally have to follow. As part of that transition, we are pretty much through it, right? Consumption is the de facto motion in our business. Subscription is a very small part of the business, and we end of life some of the subscription offerings.
The second is we had believed that there would be synergies between some of the operational capabilities and FinOps together with storage. And the market did not develop in that direction after a few years. So we decided last year to divest our spot portfolio. And that is part of the reason why on an as-reported basis, cloud grew 1%. But if you compare it on an apples-to-apples basis, the underlying cloud business grew at about 18% in the first quarter.
The core focus of our cloud business is really what we call our first-party end marketplace cloud storage services. These are our flagship operating system embedded as a native offering, meaning developed with, sold by and supported by each of the big 3 hyperscalers. And that has grown north of 40% this last year and is growing north of 33% this first calendar quarter. We have a broad range of advantages over other offerings in the cloud. And we are bringing more technology as well as expanding our go-to-market. Listen, I think broadly speaking, in cloud, we have an unhindered runway.
And just the pace of enterprise AI adoption impact Hybrid Cloud growth rates versus Public Cloud? Or is it kind of agnostic? Or just help us understand where do you see more of the AI workloads between these 2 segments that you have?
AI workloads start in the Public Cloud usually because the data science teams can spin up a workload in Amazon or Google or any of these cloud providers. We are capturing some of that with our cloud portfolio. As you scale it and depending on the industry, a lot of the data sits in the enterprise and data gravity is very, very strong, right? It's -- if you thought that the models that you apply to structured data, meaning databases or data warehouses where you copy a small amount of data every night in a batch model to a central data lake, that model just does not work for unstructured data. The volume is much, much higher the ability to copy it is just insanely low. And so you really need to bring your AI capabilities to the data, and we'll talk more about that, a bunch of innovations that we are bringing to market that enables organizations to do that.
Okay. And then sort of as you sit back, so AI can obviously be a demand driver for you guys, especially as you start to do more inferencing like you talked about, both on the Public Cloud where it maybe initiates initially and then moves on-prem. As you sit back and you think about margin expansion or profit dollar expansion as well, help us understand like could there be a scenario where you start to see margins expanding both in public and hybrid as a function of more AI inferencing? And when do you -- what's the line of sight to that?
I think in public, we already have a very strong margin profile. In the Hybrid Cloud world and in the Public Cloud world, I think the big driver of further margin expansion is all of the software value we bring to clients as they deploy inferencing, software value around advanced cybersecurity mechanisms on cataloging, searching and organizing your data, implementing guardrails for privacy and governance, being able to generate vectorized representations of your data on the fly without copies. That software is not just for the new data that customers are creating or the new environments that they are creating, but it can be monetized over our entire estate of data in our customers. And so that's probably the most significant multiyear opportunity for NetApp.
And then how does that translate into -- does that also come with more OpEx investments? Or does it translate into better operating leverage?
I think we continue to remain disciplined on operating expense. I think you can see that in our track record over many years. I think that we will continue to remain disciplined about that. If there are opportunities that we can accelerate 1 or 2 things, you can see us do that both by reallocating resources, but also it might be a temporary investment. But I think in the sort of over a 3-year period, you should expect us to grow OpEx less than we grow revenue. Typically, we've grown it at half the rate of revenue, and that's productivity discipline we've installed in the company.
Right. We're asking all our companies if they internally use AI to drive some of those OpEx leverage or OpEx efficiencies that you're talking about?
Yes, absolutely. I mean NetApp is a big software company. Our intellectual property is really software. We use AI to accelerate software development, have seen really strong productivity improvements there. And it allows us to deliver more payload faster. I think the second place where we are seeing good uptick is really in our customer support business, where we can provide more advisory value to clients, but with the margin profile of our traditional support business because we continue to optimize parts of our ongoing offerings and digitize those. And then back office. So lots of different elements of back office.
Okay. The competitive environment, if you can just talk a little bit about it. At one point, there's obviously pricing that has to pass through, whether its tariff related. I'm not sure that really affects NetApp as much. But just any kind of pricing pressures that you see, whether it's the underlying commodity costs that have to be passed through? And how do you see the competitive environment? Is there pass-throughs that is affecting kind of the way you're looking at pricing in the back half and the customers' reception to those higher prices?
Yes. I think we are a mature industry. It's always been competitive, but the players are rational. On any given transaction, someone might be more aggressive than somebody else. But in general, it's pretty rational. We have a sticky software platform. And so for someone to displace us is not easy, right? And on the other hand, we are trying to displace other people. So we have puts and takes in terms of our transaction volume.
In terms of tariffs, as we said, and as you mentioned, Asiya, it's not a big contributor to our cost structure this year. We said that it would be between 40 and 60 basis points as part of our guidance. And as a result, we have not raised prices. We're waiting to see whether there's a more material change in posture of the administration, and then we will take a look at what that means. And then broadly speaking, in general, as commodity cost prices change in the market, the vendors typically pass that on to customers. And as they go down, they also pass on the benefits. So customers are quite well trained at saying, "Hey, this is a good time, and that's a more difficult time." And they optimize their spending.
Okay. And then Dell, just in terms of what's going on in the market from a -- we have had peers like Dell talk a little bit more about Project Lightning, which are a little bit more software-defined and architectures that are also going around. So just high level, how you guys are thinking about the competitive landscape? What do you see as some of your peers coming out with? And how is NetApp positioned with that? And within that, if you can also address something that I hear from investors about HCI, hyperconverged infrastructure, what's going on there? And how is NetApp positioned as people are -- as enterprises are looking for alternatives to VMware?
Yes. I think, first of all, with regard to sort of the data center evolution for AI, how the network fabric changes, how does the storage fabric change. We have some really important announcements at our customer conference where we have some state-of-the-art next-gen technologies being made available, we will be well ahead of Project Lightning or thunder or whatever. Grand announcements are to come. And so we have made that technology, we'll be ready with it, right?
I think with regard to the hyperconverged solution, listen, I think that the price of VMware being raised dramatically or them not wanting to support a class of customers like the smaller customers has caused people to revisit alternatives. We see 3 alternatives that customers talk to us about and that we're well positioned for. One is, hey, I want to keep VMware for compute, especially for production environments, but I want to optimize my spend. And one of the easy ones is to move storage from running on vSAN as part of a hyperconverged to using external storage. And we've already seen clients starting to do that. It allows them to stay on VMware for a period of time while they optimize their spend and look at alternatives.
The second is customers replatforming and they replatform in a bunch of different directions, right? They could replatform to Kubernetes. We are seeing a bunch of customers do that. We are seeing clients go to alternate hypervisors like Nutanix or Hyper-V or Proxmox or HPE VM Essentials. There's just a lot of them out there. And our goal is to -- we already interoperate with a whole range of them. We will interoperate with pretty much all of them based on customer demand.
And the third one is for clients who are -- especially the smaller ones who cannot negotiate directly with VMware or realize that their ability to get well-structured, consistent pricing, we are seeing them move to the hyperscalers who can guarantee pricing or some of the large service providers. We are the platform for VMware on AWS, on Azure, on Google as well as a range of other service providers.
Okay. So last year, we have a few seconds here, George, like when I talk to investors, like what do you think is underappreciated about the opportunity to invest in NetApp shares?
Broadly speaking, we have been working for many years to get the enterprises ready with their data for the age of AI. We talked about unifying data across data types. We talked about unifying data across the clouds, and we are incredibly well positioned now together with our large installed base to enable clients to get real value from their data. We are also, as part of that, we have the most secure storage and data -- cyber resilience of data in the planet. We are #1 with modern data infrastructure with flash, and we have a growing unhindered opportunity in Public Cloud. And I think as you look at our customer conference upcoming, we will introduce a lot of additional software capabilities that we can monetize in a broad footprint.
Great. Thank you, George. I appreciate it.
Thank you for having us.
Best of luck for the rest your meetings here.
Thank you. Thank you for having us.
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NetApp — Citi’s 2025 Global Technology
📊 Kernbotschaft
- Kurzfassung: NetApp positioniert sich als Nutznießer der Enterprise‑AI- und Hybrid‑Cloud‑Welle: starke Flash‑Marktanteile, beschleunigtes Cloud‑Wachstum und verbesserte Cloud‑Margen. Management bestätigte die zuletzt kommunizierten Jahresziele, sieht aber makro‑ und public‑sector‑Risiken.
🎯 Strategische Highlights
- Hybrid Cloud: NetApp betont Unification von Daten on‑premise und in Public Clouds als Kernvorteil für Enterprise‑AI; Flash als Treiber für AI‑Ready‑Infrastruktur.
- Cloud‑Go‑to‑Market: Übergang zu Consumption‑Modellen abgeschlossen; First‑party Cloud‑Services wachsen >33–40% und bieten hohe Margen.
- Software‑Monetarisierung: Fokus auf Datenservices (Indexing, Suche, Guardrails, Vectorisierung) plus Keystone (Storage‑as‑a‑Service, +80% YoY) als mehrjährige Ertragsquelle.
🔭 Neue Informationen
- Guidance‑Status: Keine neue offizielle Guidance — zuletzt bestätigte Ziele wurden bekräftigt; keine Änderung der Jahresprognose angekündigt.
- Margin‑Color: Cloud‑Bruttomarge wurde auf Zielband ~80–85% gehoben; Produktmargen sollen in H2 wieder in den mittleren bis oberen 50‑Prozentpunkten landen.
- Kostenfaktoren: Manager sehen bessere NAND‑(NAND‑Flash) Kosten in H2, NAND macht ~1/3 der COGS; Tariff‑Effekt im Guidance‑Rahmen 40–60 Basispunkte.
❓ Fragen der Analysten
- Margen & NAND: Analysten fragten nach Produkt‑Bruttomargen und Korrelation zu NAND‑Preisen; Management erwartet H2‑Erholung, kann Preisschwankungen teils durchgeben und hat Lieferverträge zur Stabilisierung.
- AI‑Nachfrage: Sichtbarkeit und Lummigkeit der AI‑Investitionen waren Thema; Kurian argumentiert, NetApp habe ein breiteres, gleichmässigeres Enterprise‑Pattern als reine Compute‑Player, skaliert aber noch nicht in großem Umfang Revenue durch AI‑Implementierungen.
- Wettbewerb & HCI: Fragen zu VMware/Hyperconverged‑Trends; Antwort: mehrere Migrationspfade für Kunden, NetApp profitiert von Extern‑Storage‑Moves, Replatforming zu Kubernetes und Cloud‑Alternativen.
⚡ Bottom Line
- Bewertung: Call liefert substanzielle operative Farbe—Share‑Gains, stärkere Cloudmargen und ein klares Software‑Monetarisierungsmodell sind positiv. Kurzfristige Risiken bleiben (Makro, US‑Public‑Sector, Timing großer AI‑Rollouts). Für Aktionäre: konstruktive Story mit H2‑Margin‑Upside, aber Geduld für materialisierte AI‑Revenues ist angebracht.
Finanzdaten von NetApp
Umsatz
Der Umsatz stellt die Summe aller Einnahmen eines Unternehmens z. B. für dessen Produkte oder Dienstleistungen dar.
Umsatz (TTM) einfach erklärtDirekte Kosten
Direkte Kosten sind die Kosten, die direkt im Zusammenhang mit der Herstellung des Produkts oder der Dienstleistung entstehen.
Bruttoertrag
Der Bruttoertrag gibt an, wie viel vom Umsatz nach Abzug der direkten Herstellkosten im Unternehmen verbleibt. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der Bruttomarge (engl. Gross Margin).
Brutto Marge einfach erklärtVertriebs- und Verwaltungskosten
Die Vertriebs- & Verwaltungskosten (engl. Selling, General & Administrative expenses, kurz SG&A) beinhalten alle Aufwände für Marketing und den Verkauf sowie die allgemeine Verwaltung des Unternehmens.
Forschungs- und Entwicklungskosten
Die Forschungs- und Entwicklungskosten (engl. research & development costs, kurz R&D) geben Auskunft darüber, wie viel das Unternehmen in die Forschung und die Entwicklung seiner Produkte investiert. Vor allem prozentual vom Umsatz und im Vergleich zu direkten Wettbewerbern sind die Kosten interessant.
EBITDA
Das EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) ist der Gewinn des Unternehmens vor Zinsen, Steuern und Abschreibungen. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der EBITDA-Marge.
Abschreibungen
Abschreibungen stellen Wertminderungen von Vermögensgegenständen des Unternehmens dar (z.B. durch Abnutzung von Maschinen).
EBIT (Operatives Ergebnis)
Das EBIT (engl. Earnings Before Interest and Taxes) ist der Gewinn des Unternehmens vor Zinsen und Steuern, das auch als operatives Ergebnis bezeichnet wird. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von
der EBIT-Marge.
Nettogewinn
Der Nettogewinn stellt den Gewinn oder Verlust nach Abzug aller Kosten dar.
Nettogewinn einfach erklärtaktien.guide Premium
| Jul '26 |
+/-
%
|
||
| Umsatz | 7.391 7.391 |
12 %
12 %
100 %
|
|
| - Direkte Kosten | 2.171 2.171 |
10 %
10 %
29 %
|
|
| Bruttoertrag | 5.220 5.220 |
13 %
13 %
71 %
|
|
| - Vertriebs- und Verwaltungskosten | 2.273 2.273 |
5 %
5 %
31 %
|
|
| - Forschungs- und Entwicklungskosten | 1.023 1.023 |
2 %
2 %
14 %
|
|
| EBITDA | 2.106 2.106 |
26 %
26 %
28 %
|
|
| - Abschreibungen | 182 182 |
21 %
21 %
2 %
|
|
| EBIT (Operatives Ergebnis) EBIT | 1.924 1.924 |
34 %
34 %
26 %
|
|
| Nettogewinn | 1.418 1.418 |
21 %
21 %
19 %
|
|
Angaben in Millionen USD.
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Firmenprofil
NetApp, Inc. beschäftigt sich mit dem Design, der Herstellung, dem Marketing und dem technischen Support von Storage- und Datenmanagement-Lösungen. Das Unternehmen bietet Cloud-Datendienste, Datenspeichersoftware, Datensicherung und -wiederherstellung, All-Flash-Speicher, konvergierte Systeme, Dateninfrastrukturmanagement, ONTAP Datensicherheit und Hybrid-Flash-Speicher. Das Unternehmen wurde im April 1992 von David Hitz, James K. Lau und Michael Malcolm gegründet und hat seinen Hauptsitz in Sunnyvale, Kalifornien.
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| Hauptsitz | USA |
| CEO | Mr. Kurian |
| Mitarbeiter | 11.700 |
| Gegründet | 1992 |
| Webseite | www.netapp.com |


