Dynatrace Aktie

Welcome, everybody, and thank you for joining us. I'm [ Marty Vouin ]. This is [ Jane Patel ]. We are the JPMorgan equity research team covering enterprise software. And it's a great pleasure to be here with Rick McConnell, CEO; Jim Benson, CFO; and Dan Zugelder, CRO of Dynatrace. Rick, Jim Dan, really appreciate you guys coming back to TMC.

We'll start off on a good note. You guys finished fiscal 2026 surpassing $2 billion in ARR, fourth consecutive quarter of 16% ARR growth and a fiscal '27 guide that bakes in net new ARR acceleration. So it's been a banner year for you guys. But then just to start off, why don't you guys give a quick introduction and just let us know what Dynatrace is solving for the world's enterprises today and how that's evolving in the AI world?

Sure. DynaTrace is in the $75 billion plus observability space. Observability is targeted at enabling enterprises to run their software better. So think about us as helping to prevent incidents to remediate incidents and to optimize your environment. This is what observability software generally does. We often think of Dynatrace's vision in delivering the world software that works perfectly. So that would be our objective.

And obviously, as we evolve so rapidly into an agentic world, this brings a huge array of new opportunities to the observability space. Because agents enable us to actually take action and to execute those actions in a more autonomous way. So you can imagine systems that are self-healing effectively to enable software to always work better than it's worked before.

So I'm sure we'll talk more about this, but it is a very, very exciting space that we believe is a is a tailwind or receives a tailwind from all that is happening in AI based on the expansion of workloads to drive towards autonomous operations and in general, the necessity of delivering software that works perfectly.

That's great. And I think the self-healing part is a good way to describe it. I'm sure we'll touch on it, but the more that AI accelerated CoGen, I think it's made that observability even more important and critical and something that you need a third party can do it excellently to do it.

But let's just start with the fiscal 2027 guide. Jim, if we think about the nuances from the earnings call last week, the guide implies net new ARR growth of 16% to 23%, accelerating from 12% in FY '26, reported ARR of 15.5% to 16.5%. That range from 16% to 23% of the ARR, it's wide. Can you give us a sense of what drives the high end versus the low end of that and what you can control in that equation?

Yes. I'll start with fiscal '26 was a year first. You mentioned in your opening remarks that we had consistent ARR growth of 16%. So we grew net new ARR at 12% in fiscal '26. We haven't done that in 3 years. So one of the things I talked to investors about is the phases that we've been going through. Fiscal '25 was a fixed year where we did some things on the go-to-market side. Fiscal '26 was stabilized and fiscal '27 was accelerated. So I've talked about that over time.

We mentioned logs. We -- Dan will probably talk about it in a bit around platform consolidation, end-to-end observability is certainly something that more and more enterprises are looking to do. So that is certainly a tailwind. So relative to the range, I think what you see is that at the low end of the range, it still implies an acceleration of net new ARR growth of 16% and you mentioned 23% on the high end.

Some people have asked me, they said, geez, Q4 landed a little bit lighter than maybe people would have thought. And I would say it did land a little bit lighter than our internal expectations. And I'd say largely that is we had softness in our EMEA market, notably in the Middle East. The difference between growing double digits and growing 9% is a few million dollars. So when I look to fiscal '26, there's a lot of momentum building in the business. And we expect it to continue. All the things that I just mentioned will continue.

Relative to a range, I mean, our range is usually 1 point, plus or minus. So I think what you get at the high end of the range is a continuation of what we've been doing and building. Even at the lower end of the range, you're getting that. I think you know that historically, I've used the word prudent. that was called out on the earnings call. This guide is no different than any other guide I provided every year. So there is an internal plan and then there is a haircut for what we do that we're going to tell the investor community. And it's no different than what it always is. So we certainly have line of sight to doing better than the high end of the guide.

Obviously, we got to see how the year progresses. I mentioned in the call that we would be a little bit more half 1 weighted. And just to clarify that, our historical linearity is like 44% of our net new ARR in the first half, 56% in the second half. That doesn't mean we're going to do more net new ARR in the first half. It just means that we'll do a couple of points more, maybe 46%, 54%.

And it's because we have strong forecasted pipeline entering the year. And our pipeline visibility is always tighter in a 3- to 6-month window than it is 12-month window. So we actually just believe there's just a lot of tailwinds. And as the year progresses, we'll update our outlook accordingly.

Yes. And just to be 100% clear, your guidance philosophy essentially is unchanged from what you guys have done historically?

That's right.

Yes. Yes. If we just double-click on that 9% net new ARR growth in Q4 and then going forward, I know you mentioned there was some softness in the Middle East. I assume the Iran conflict doesn't help that situation. But if you can just talk about okay, if you have those slight headwinds, out of those tailwinds that you're seeing, which ones do you think are going to be able to drive a lot of that? What should give investors confidence in what we're seeing through the rest of the year?

I think the biggest one is I think we will continue to do what we did with logs. Our expectation is that logs will continue to double. So we ended the year well over $100 million in our -- we have a lot of confidence that we will continue that trajectory that we have the right product with the right pricing and packaging at the right time.

And I think we've shown it in and ability to go into our installed base and sell it and actually even introduce new logos. So I think logs will be a big source of it. I do think we'll continue to see workloads grow with end-to-end observability. More existing customers and new customers looking to consolidate. One, they can save them money. You consolidate multiple vendors and you could save money just through software costs. Beyond that, we allow their environment to run more efficiently because once you're on Dynatrace, you can -- you have a platform where you have deterministic answers to figure out issues as opposed to people chasing alerts and dashboards.

And so it really is just a -- this is not like new plays. It really is and it's a continuation. Dan can talk about the go-to-market model is largely unchanged. We're going to go down with our strategic accounts. We've had Global 500. We'll probably go down another 100, 150. We'll have 4 to 5 reps in that part of the pyramid. So you'll have fewer accounts per rep. We'll get better penetration. The penetration that we've had in those accounts since Dan made those changes, the fastest-growing segment that we've had in the company. And it's about running that play again. And we think that, that will continue to be another source of productivity improvement.

Yes, and having the continuation of the existing tailwinds feels a little bit more comfortable than anything new having to kind of layer in.

One other thing that I would mention is that you know that we've been at the Dynatrace platform subscription for a while. And so we now have over 75% of our ARR on that contracting vehicle, a little over 60% of our customers. Fiscal '27 is the first year where you're actually going to go through three annual reset cycles. We haven't had that in the past. And the first year of EPS was fiscal '24.

Most of our DPS customers have 3-year cohort classes. They are coming up for their actual renewal in fiscal '27. So there's a significant percentage of our installed base with DPS that is going to go through either a renewal or an annual reset. It's a huge opportunity for an expansion for us for all the reasons we just said. Consumption is growing at a very rapid clip. It's been growing north of 20% for well over 4 quarters. And if we can continue with that. Again, it will be a source of expansion opportunity.

Yes. Yes. It sounds like a lot of upward pressures in the right direction. Touching on some of the other things you were talking about, Dan, I think this is your wheelhouse. Dynatrace, you guys started this go-to-market transformation a couple of years ago, shifting reps to focus on 4 or 5 accounts in the Fortune 500, building the partner motion, comp plan changes.

And as Jim said, you just finished kind of the stabilization phase. So when you're looking at that pipeline coverage entering FY '27 is healthy enough to guide net new ARR modestly to accelerate. One of the themes in our partner work is that the pipeline quality matters more than the quantity. I assume you guys kind of have the same perspective. Can you talk about what you're seeing in terms of that quality and how you measure it? Is it the stage progression, deal velocity, close rates? What is giving you confidence in that pipeline?

Yes. I think it probably starts with the methodology and the inspection, the quality of in, what goes in, the approach we take with that. But then the analytics play a role as well. The motion for Dynatrace, if you go back a few years ago, was a very different selling motion regarding pipeline. It was a very mid-level enterprise engagement, typically very feature-based.

And over the last 3 years, it's transformed into a much more enterprise value selling motion. So we have a different approach, a pretty dramatic different approach. And that's matured at this point. So we understand what goes into our pipeline. We understand the risk of what matures, what doesn't, at what pace. So I think it's just the maturity of the motion that gives us the confidence in the pipeline.

That's great. I want to turn it over to [ Jayden ] here. But Rick, complementing on that enterprise motion on the shift to the left, developer side, you got DevCycle, MCP server, cloud code, cursor. Is this an evolution of the enterprise motion or a different velocity engine kind of targeted AI natives and the AI native buyers?

Great question. Definitely the power of the and. I learned this from my earlier career in Cisco, and we were always talking about the power of the and. This is definitely it. We don't foresee a shift from the enterprise to AI natives, for example. We believe that it is the enterprise plus AI native. We have been working very diligently over the last 18 months to build developer capabilities into the platform.

And you've seen those over the last couple of quarters through a myriad of announcements related to integrations, for example, into AWS, Bedrock Agent Core into GitHub Copilot into Cloud Code into a myriad of different other elements. All of these enable our platform to be more developer ready. And we didn't grow up on the developer side like some others in our industry.

We grew up in the enterprise side, focused on IT ops selling to the CXO. And this is why out of our customer base, we have an average selling price of now about $500,000. It's because they are large end-to-end enterprise deployments. And they -- these customers use us to make sure that their software always works. And they want to deliver end-to-end observability at multiple levels. completely integrated data lake house, integrated fully across logs, applications, infrastructure, real user monitoring, et cetera. and then integrated for all personas.

And this is what we do better than anybody. This has done a traces superpower. We want to take that superpower that we've delivered to the enterprise and bring that to the developer community, bring that to AI natives. And that really is the next step in our evolution as an organization.

Great. Dan, I think this one is for you. Let's talk a little bit about the disconnect between what we hear from investors and what customers or what you're seeing with customers? One consistent theme we hear from investors that customers are more reluctant to spend because of all the uncertainties due to AI. A lot of this discussion centers on the application side, but I think it's worth touching on here.

Dan, I assume you're the one across the table from CIOs and CROs every week. What do customer conversations actually sound like right now versus what we're hearing from the investor community?

Well, I think there has been -- I don't know if it's new, there is cost concerns. People are looking to -- and that's why consolidation has been such a play is that -- no question it gets people's attention when you're saying I'm taking two or three tools and making them into one, and there's going to be a 10% to 15%, 20% cost savings. So there's an attractiveness of that conversation.

When you can couple that with saying I'm going to give you a better outcome, that's usually the combination that people are looking for. So we're not looking just to do things to cut costs, but if we can deliver a better observability outcome. So I think as we enter AI, and we just came out of our sales kickoff, I reiterated that our motion of tool consolidation cost out and logs is a great example of that, where we sometimes take 40%, 50% cost out because of combining logs with metrics and traces, you just need less of them in a more efficient way.

So that -- it does resonate with our customers. There's no question. It has been, and I think it continues to be -- get people's attention. What you do in this world that's been created with AI is a fantastic tailwind because you're creating then budgeted new projects their AI projects that need observability. So you continue to run your entire play around tool consolidation, the enterprise end-to-end observability. And now we have a motion that we've added that is more about saying, going after these specific AI projects that need observability.

So you have a little bit of a bespoke process in go-to-market, and then you have our very mature enterprise market. So that's created additional opportunity for us. And then Rick talked about the AI natives to have their own specific market as well. So AI has created additional markets and for observability for sure.

The one thing I would add, just to append to Dan's remarks is, we absolutely believe that observability is a beneficiary of AI evolution of AI-first organizations. It is critical in our view that in an AI-first world, you need more observability, not less. We do not see observability as a market and infrastructure environment, which is going to get disintermediated by AI.

Quite the contrary, we see that in our existing customer base, maybe 30% or so of workloads are actually observed in a sophisticated way like using Dynatrace in a probabilistic world where you're using lots of LOMs, agents to build software, we believe that you actually need more observability to oversee those workloads than not, number one.

Number two, we bring incredible contacts, billions of interconnected data points in real time, very specific to a particular organizations environment. And number three, we bring domain expertise of understanding that environment specifically and how that environment is operating. So observability is going to benefit from a tailwind in AI, not just in deployment of AI natives, but also in the enterprise itself, where obviously, enterprises are deploying more and more AI workloads that are inclusive of AI, largely built by AI, coded by AI and over time, will be operated by AI in a very agentic world headed to an autonomous environment.

All of these factors are driving an environment for observability that has become more and more mission-critical to organizations day by day. And of course, it's our commitment to do everything we can to be a beneficiary of this trend for observability overall at Dynatrace.

Yes. It seems like there's a lot of AI tailwinds that are benefiting the business on top of the execution that you guys are providing. Jim, on that point, when do you expect these AI tailwinds to meaningfully contribute to accelerated growth?

Well, I think we're already starting to see it. But you got to remember that the way our model works is you're signing up customers on a contract with DPS and then they have 3, 1-year commitments and then they push consumption. So the underlying component of DPS is consumption. It's not a seat-based model, it's a consumption model.

Now we recognize revenue ratably but we consume based on what customers are -- what workloads customers are adding and the growth in those workloads. So we're already seeing some of the benefits that -- again, I mentioned that it's been over 4 quarters that consumption is growing north of 20%. And the way to think about that is that -- and I think this is where people sometimes struggle is why is ARR not growing 20%. And there's a lag. There is a lag with just the nature of the way the DPS contracting model works. But if you can continue to grow consumption north of 20%, you will see a convergence of ARR and consumption over time.

And if I our selling motion is just as much about bringing workloads onto the platform as it is expansion of ARR because it's it's the preemptive piece of expansion on ARR. So our salespeople are out there just trying to get workloads on to Dynatrace, we they're AI workloads, whether they're logs, whatever expanding to more applications in general. Their motion is like, I know if I get more consumption -- when that DPS comes for renewal, that will give the fuel to that fire to be able to expand more. So you can understand how we are very consumption-based even though we're an or an ACV and ARR as far as the way we measure the business, the focus is now -- is all on consumption.

The other thing that I would say is that we have integrated account teams that Dan's account reps are the quarterback for us. So we have customer success teams, they are measured on consumption. They are compensated on consumption. Dan has bespoke strike teams or bespoke product areas. They are measured on consumption. They are compensated on consumption. So this consumption mindset is -- exists throughout the company.

And I'd say we continue to run plays now. There's going to be plays on consumption. So again, at its core, get them on the DPS platform, have teams of people work with them to get more value to Dan's point, reps ensuring they find new workloads. We've got customer success teams that are helping ensure that they're getting value out of the different product areas.

And then specifically on the strike teams, they're both -- they're on the front end with sales on deals, and they're also on the consumption side around driving more consumption. So it's -- I'd say we have a lot of the ingredients in place. They've been in place now for a year. I think it's led to what has been stabilization, and we're quite confident that it will now lead to acceleration.

Great. Let's tackle sort of the bear case on observability head on. Rick, this question is for you.

I must give the bear case to Jim. I'm just kidding.

The question that comes up most often on our end is this outstanding idea that as the cost of code goes to 0, customers can use open telemetry plus Vibe coding to roll their own observability layer and an LLM can reason over that telemetry. We've written tens of times that we think this thesis is off base, but better to hear from you than anyone else. What is your thoughts on that? And why is that true or not true?

Yes. I mean I sort of gave the precursor to this answer already. So I can -- I think I can do it briefly. But -- the starting point is I sort of oversimplify to bifurcate the world into application seat-based software with standardized workflows and highly dynamic software -- infrastructure software that needs to take real-time data into account. These are very, very different models. And in the former case, it is much easier to [ VIB ] code a standardized workflow than a highly dynamic workflow based on context.

And that is sort of the underlying thesis and our view is the combination of significant domain expertise, highly specialized for organizations like JPMorgan, for example, or the largest organizations on the planet to be able to integrate and observe their environments is absolutely nation critical to those organizations and are you really going to rely on a vibe-coded standardized piece of software. It doesn't have the same degree of domain expertise. Doesn't have the same degree of real-time context based on billions of interconnected data points. Doesn't have the ability to oversee or observe probabilistic models and by the way, there's an even added element here.

For the history of Dynatrace, we have been focused on a particular question or answering a particular question for our customers. And that question is, is it working? If you think about what does observability do, is it working or maybe is it working well? Is it optimized? That's what we've been focused on in an LLM world of models that are providing input to allow trustworthy actions to take place through agents, you have to answer a separate question.

And that is, is it correct -- in other words, is the information coming from models actually accurate so that it can be trusted and implemented. We have customers that are using us in payment terminals that have to work every time. They need agents to be able to take immediate action to provide corrective action to make them work. We have banks who are using them in mobile using Dynatrace as part of mobile apps to assist customers to transfer money from one account to another. That's got to work every single time, whether it's health care, manufacturing, their use cases in each of these environments that are critical to be driving trust worthy outcomes based on AI and LLM inputs.

And you simply can't rely upon an LLM to provide that degree of context, that degree of domain expertise to support an environment that then was created with a standard LiveCode. It just isn't going to work. And so -- and if there's one answer to all that, I would say, context is it.

Great. On that point that these tools need to just work, the place where that makes the most sense is the enterprise, right? So Dan, this one is for you. The most striking thing in your recent quarters is the consistency of 7-figure deals, $200,000-plus new logo lands and as you said, roughly $500,000 ARR per customer, which Jim has framed as having a path to $1 million plus over the long term. A partner told us that consolidation is the only conversation that matters right now. CIOs are tired of paying for 5 tools that overlap. Is that sort of the right read on buyer mindset right now?

Consolidation is definitely on their top of mind. But I mentioned this before, it is obviously cost. It obviously has to do with if you are a C-suite, up to the CEO of organizations, and there is a major outage. CEO will be -- the first question is, what's the problem? Obviously, that I/O, if they cannot answer that question very quickly, their job is on the line. So that is -- when you have a fragmented observability stack, it means that, that answer becomes that much more difficult. because everybody is looking at their individual tools and saying, I'm good. And they're asking the question, they're going around the room and people are answering, I'm good, I'm good. And somebody have stopped saying, but we have a major outage going on right now.

So we deliver that so you have visibility across your entire application and infrastructure stack. So the consolidation plays on a cost basis. There's no question it, but it plays on delivering a better outcome. I think that trend is not going away. It's a bit -- some of the C-suite I speak to all the time is that they're just trying to continue to pull things together, pull optimize costs but deliver a better outcome.

That is not -- that's been there. I think it's catching when. I think there's a lot more. Logs have played a big role in that, that if you look at it, we were 18 months ago, we really weren't playing in the logs business. So that's accelerated this view of a better outcome. Most people are using another -- some of the traditional log providers, and that was redundant to observability. So that was actually -- it's fairly low-hanging fruit for them.

I would just add that -- it seems to me that the holy rail that Dan and I hear from CIOs, CTOs, CXOs basically every day as they want to get to autonomous operations. They want to get to autonomous operations because the cost savings are extraordinary. And by the way, they're having more difficulty finding head count to actually manage environments rather than less. So they need to be able to do more on an automated basis. By the way, to the extent that, that can be predictive, it's even better. so that you eliminate issues before they even occur.

In order to get to autonomous operations, you have to have to Dan's point, end-to-end observability because it is the confluence of elements that enables you to have confidence and trust in the outcome that enables an agent to take action. And if you don't have that degree of confidence in trust, you cannot rely on the agent to take the correct action. So the mechanism to get to autonomous operations from accounts is to begin with end-to-end observability.

And this is why, last quarter, for example, 22 deals of greater than $1 million, which is pretty substantial. For run rate, all driven by really this end-to-end observability motion, all setting up not as the end but as the mechanism to drive toward autonomous operations as we look at.

You mentioned logs earlier and a bit on this last question as well. Logs has definitely been one of the biggest surprises, positive surprises in the Dynatrace story over the last 12 months with over $100 million of annualized consumption, which growing north of 100% year-over-year. Rick, you were out there quoted in the ether around the $250 million number, which we interpreted as aspirational. The underlying question here is, let's say we pass that $250 million, where can this business grow? What is the overall market here that you can drive this to be?

I'll start and look to Dan and Jim to comment further. But I mean, the logs business alone is a multibillion-dollar market. I mean you look at Splunk, you look at others in this market, and it's already many, many billions of dollars of log observability -- and we believe that -- we absolutely believe that our business can continue to grow toward that $1 billion mark and over the course of time, even beyond that.

And the reason is because we believe that we have a solution that is better than a stand-alone log solution. Stand-alone log solution is focused only on logs. What we can do, which is consistent with what we've been discussing here before, are two things related to logs. Number one, by integrating, as Dan was talking about, logs with traces, metrics, really user data, behavioral analytics, et cetera, you get a better outcome. you can see the entire environment by seeing the entire environment inclusive of logs, you deliver a better outcome. Those answers that come from that better outcome lead to the autonomous operations of the environment that I'm describing.

The second thing is you actually -- because you have traces, metrics, logs, real user data, it actually is more beneficial to have multiple different data types than just more logs. So you can actually accumulate fewer logs, but when combined with these other data types, you actually end up in an environment where you get a much richer environment to be able to provide analytics that allow for things like auto prevention, auto remediation, auto optimization.

And so better outcomes, lower price point and you have lots of our existing customers that are using a log vendor for logs us for observability, and they're increasingly moving that log workload to us in order to get the benefit of end-to-end observability that we've been talking about for all the reasons we've been discussing.

Great. I have one last question, and I can hand it off to [ Ari ]. Jim, this one is for you. We would be remiss not to ask about this. The Starboard team published a fairly detailed letter on April 28, and both of you and Starboard have described the engagement as constructive. Rather than dwell on the letter itself, help the audience understand how you're thinking about the value creation framework for Dynatrace over the next several years.

Yes. Well, I mean, we think of value creation beyond all investors. So that's kind of how we're viewing Dynatrace that we want to provide shareholder value for all. And I think at the end of the day, when you think about what we're trying to do, everything we tried to build and outline was an acceleration in the growth of the business.

This business can and should be north of what it has been delivering. And so for us, there's been a big focus, again, going back to my fixed stabilized accelerate, putting things in place to go on the offensive to go after the opportunity. I think Dan talked about some of -- the model we had before was good for when the company got to $1 billion and we needed a different model to be able to scale. And so when I think about acceleration, I think it's in our sights. And you've seen that for sure, at the high end of our guide, we expect that, that will happen this year.

On the margin front, we are a rare company that operates at 29% or 29%, almost 30% operating margins. We've driven 400 basis points of leverage in the model. In each year, we'll tweak it a little bit because sometimes you'll make investments in 1 year, you'll get a return the following year. So driving efficiency and driving leverage is always part of the story that Dynatrace is a balanced growth and profitability story and it's a sequencing of when you would do that. So I think we've demonstrated that we can do that, and we will do that.

I mentioned in the call that we're driving 150 basis points of operating expense leverage in fiscal '27. Offsetting what is the near-term gross margin headwind. So again, margin and leverage very important. And then we believe the shares are undervalued. We have significantly bought back stock we increased the pace of our buyback 40% from Q3 to Q4. You know that we doubled the authorization to $1 billion in February.

And so we believe that at these prices, it's very attractive, and we will continue to put capital to use in the form of buyback. We have -- we generate a lot of cash flow. We have a fair amount of cash on the balance sheet. So accelerate growth continue to focus on efficiency and then put your buyback to use at very attractive values. And I think that's what we've been doing.

Yes. Well, Rick, Jim, Dan, it's been fantastic to have you guys here and sharing your insights with us. A lot of stuff going right in your business. We're really looking forward to where that goes. So thank you.

Thank you.

Greetings, and welcome to the Dynatrace Fourth Quarter and Full Year Fiscal 2026 Earnings Call. [Operator Instructions]

As a reminder, this conference is being recorded. I would now like to turn the call over to your host, Noelle Faris, Vice President of Investor Relations. Thank you. You may begin.

Good morning, and thank you for joining Dynatrace's Fourth Quarter and Full Year Fiscal 2026 Earnings Conference Call. Joining me today are Rick McConnell, Chief Executive Officer; and Jim Benson, Chief Financial Officer.

Before we get started, please note that today's comments include forward-looking statements such as statements regarding revenue, earnings guidance and economic conditions. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q and our upcoming annual report on Form 10-K that we plan to file later this month.

The forward-looking statements contained in this call represent the company's views on May 13, 2026. We assume no obligation to update these statements as a result of new information, future events or circumstances. Unless otherwise noted, the growth rates we discuss today are year-over-year and non-GAAP, reflecting constant currency growth and per share amounts are on a diluted basis. We will also discuss other non-GAAP financial measures on today's call.

To see reconciliations between non-GAAP and GAAP measures, please refer to today's earnings press release and supplemental presentation, which are both posted in the Financial Results section of our IR website. And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and good morning, everyone. Thank you for joining us for today's call. Dynatrace delivered a strong finish to fiscal 2026, marked by meaningful scale, durable execution and continued innovation. In particular, we surpassed $2 billion in ARR and delivered our fourth consecutive quarter of 16% ARR growth. We drove continued traction in logs, now well over $100 million in annualized consumption, growing more than 100% per year.

We launched major platform innovations, including Dynatrace Intelligence and domain-specific AI agents. We advanced our cloud-native integrations across AWS, Azure and GCP, moving operations from reactive monitoring to autonomous action. We extended our agentic AI ecosystem with native connectivity to Anthropic's Claude Code, deepened our integration with ServiceNow and broadened developer workflow integrations with GitHub Copilot.

We acquired DevCycle, a feature management company as well as Bindplane, an open-standards-based telemetry pipeline company as we entered the new fiscal year. We maintained a leadership position in all major third-party analyst reports for Observability and AIOps -- and we delivered robust operating and pre-tax free cash flow margins.

Our consistent performance in fiscal 2026 underscores the growing criticality of Observability, the strength of our strategy and the value of our platform to customers. Jim will share more details about our Q4 financial performance and fiscal 2027 guidance in a moment. In the meantime, I'd like to cover 4 topics: how AI is reshaping the Observability market, why we believe Dynatrace is unique, Q4 customer highlights and the growth opportunity ahead.

To begin, Observability is entering a new era, one in which Observability is more mission-critical than ever. But a new set of demands is reshaping what Observability must deliver. Observability has already become foundational for enterprises looking to deliver business resilience amidst growing workload complexity and data volumes. And increasingly, organizations are looking to leverage their Observability solution to evolve toward autonomous operations, enabling software to auto prevent, auto remediate and auto optimize.

Adopting this approach requires organizations to trust the accuracy of the data that fuels agents to take action. Deterministic and causal insights from Dynatrace allow our platform to become the system of record so that development and SRE teams and increasingly AI agents can act with confidence to deliver what we refer to as answers, not guesses. Beyond business resilience, organizations now need Observability for reliable AI.

The former addresses the question of, is it working? The latter addresses the question of, is it accurate? Namely, is the content coming from AI models trustworthy in driving action and/or credible in providing recommendations to end users.

AI also adds yet another layer to the software stack, increasing the need for more Observability. Enterprises are deploying new agents, models, orchestration layers and agentic architectures that behave differently than traditional systems. Their environments generate dramatically more telemetry, connect decisions across agents and introduce probabilistic behavior that must still operate safely, securely and at enterprise scale.

Organizations now require continuous validation of system and agent behavior, governance and auditability of autonomous decisions, cost control across GPU-intensive infrastructure and strong security management. As a result, software development life cycles are evolving as well, requiring organizations to operate in 2 modes.

The first is human-led with development teams building and operating resilient systems. These teams are increasingly augmented by AI-powered Observability that drives intelligent automation, agentic workflows and progressively more autonomous operations. We continue to invest to expand our reach in this area by extending left to provide development teams, platform engineers and SREs with the Observability functionality needed to put workloads into production faster.

Second mode is agent-led, resulting in AI-first environments in which agents themselves are primarily acting as the builders and operators. In this environment, Observability insights are consumed directly by the agents in the creation and oversight of delivered software. And those insights are crucial to the effective and trustworthy operation of the environment. We believe the winner in Observability will be the provider that can meet the needs of both human-led and agent-led environments with a shared system of truth that spans both modes across AI, cloud-native and traditional workloads.

This is the moment for which the Dynatrace platform has been built. Serving customers in both modes with the trust and accuracy that autonomous operations demand and the reliability that AI-driven initiatives require is exactly what the Dynatrace platform was built to do. So why do we believe Dynatrace is unique? It is because our advantage is architectural, not feature-based. Dynatrace is built as a real-time context engine that operates at massive scale across millions of monitored entities and exabytes of data, all connected and all in real time.

By combining deterministic AI with Agentic capabilities, we deliver faster, more accurate insights than approaches that rely on agentic AI alone. This level of intelligence, speed and efficiency cannot be achieved with point solutions that offer visibility without causality. And this is why so many of the largest organizations in the world rely on Dynatrace.

As enterprises increasingly operate in agent-led environments, this architectural advantage compounds. Every new workload, AI service and agent added to the Dynatrace platform deepens causal context, strengthens autonomous reasoning and extends the gap between fragmented visibility and the unified intelligence that only Dynatrace delivers.

That intelligence is built on 3 integrated components of our third-generation platform. Grail has an extensible AI data lake house that connects every signal across an enterprise's digital environment. Smartscape has the real-time integrated topology graph and Dynatrace Intelligence delivering both answers as well as action. Together, these 3 elements provide durable competitive differentiation.

For other providers that add capabilities across stitch data stores, it's difficult to reproduce a unified data foundation with real-time causality plus trustworthy automation in the most complex mission-critical environments and certainly extremely difficult to do so in the time frame AI demands. We've now delivered agents across 3 domains, and customers are already using them in production to coordinate agents to take end-to-end action. Our SRE agent handles tasks such as Kubernetes, troubleshooting, infrastructure optimization and automated incident resolution.

Our developer agent supports use cases that surface production context during deployment, validate changes and prevent issues before they reach customers. And our security agent identifies vulnerabilities, triaging threats and accelerating security response, all in real time. That intelligence extends beyond the Dynatrace platform itself. Ecosystem integrations then enable agentic interactions to extend Dynatrace intelligence into third-party tools from ServiceNow and GitHub to the hyperscalers to drive autonomous actions across development, SRE, ITSM and ITOps workflows.

What separates Dynatrace's agents from others is the deterministic foundation underneath, real root cause analysis, anomaly detection and forecasting grounded in Grail. That's not AI that guesses, it's AI that reasons from facts. More than 500 customers are deploying Dynatrace's agentic capabilities to run operations autonomously and extend that intelligence into AI development tools like Claude Code and GitHub Copilot.

At the same time, more than 850 customers are using Dynatrace to observe and trust AI and LLM workloads in production today. Enterprises aren't just managing their environments with the Dynatrace platform. They're using it as the intelligent foundation for AI agents across their ecosystem, creating a critical role for Dynatrace as AI adoption accelerates.

This momentum is increasingly evident in customer wins across multiple buying personas, highlighting 4 examples from Q4. One of the largest banks in Brazil signed a 7-figure expansion and is standardizing on Dynatrace with 100% OpenTelemetry data flowing into Grail, choosing Dynatrace for an open scalable architecture with a clear runway for broader platform expansion. Another large U.S.-based airline selected Dynatrace as a 7-figure new logo through a partner-originated opportunity.

They chose Dynatrace to consolidate a complex multi-vendor environment to improve business Observability outcomes and reduce operational disruption. A leading hospitality SaaS provider consolidated on to Dynatrace as a 7-figure new logo, displacing legacy tooling and invoking end-to-end visibility across their cloud-native platform. And in AI native security platform selected Dynatrace as a 7-figure new logo to deliver end-to-end Observability across AWS. Together, these wins reflect increasing demand for an end-to-end AI-powered Observability Platform in the most complex environments.

Looking ahead, our strategy is to win with both human-led and agent-led operating modes on a single platform. Our product and go-to-market approaches reflect this dual reality, combining enterprise engagement focused on business outcomes with a strong developer motion that enables agentic workflows to expand at scale. This strategy leads us to an expanded set of growth drivers for FY '27.

First, our go-to-market investments in both direct sales and partner enablement have improved productivity and deal quality. End-to-end platform deals are getting larger and more strategic with Q4 annual contract value of anchor deals up 60%, with a record 22 deals with incremental annual contract value over $1 million. DPS, which now represents greater than 75% of ARR also continues to produce double the platform adoption and consumption of non-DPS customers.

Second, cloud growth is an accelerating tailwind with the major hyperscalers now growing at 40% annually. As customers scale hybrid and multi-cloud architectures across AWS, Azure and Google Cloud, Dynatrace's expanding cloud-native integrations and automation drive sustained platform usage as complexity and scale increase.

Third, logs and telemetry pipelines represent a meaningful consumption and displacement opportunity. With our Bindplane acquisition now complete and resulting in expanded ingest from OpenTelemetry, we are simplifying telemetry collection and routing at scale, reducing friction for customers to bring more data into Dynatrace, and we are accelerating time to value plus consumption growth.

Fourth, agentic AI itself is an expansion driver. As agentic development accelerates, customers need more context, precise answers, governance and closed-loop automation, areas in which Dynatrace is structurally advantaged. And finally, developers are a long-term growth engine through the integration of Dynatrace Observability into AI development life cycles, including support for Claude Code, Cursor and GitHub Copilot. With our DevCycle acquisition, we extend this opportunity even further, expanding Dynatrace's footprint earlier in the life cycle and driving durable usage over time.

To close, Observability is already mission-critical infrastructure for AI-driven enterprises. Context and domain knowledge make Dynatrace not only durable, but essential in an AI-first world. We believe we are uniquely positioned with a differentiated end-to-end platform, providing the intelligence engine and AI control plane that produce both insights as well as autonomous action. With tailwinds in cloud and AI plus Dynatrace-specific growth drivers, we are focused on accelerating ARR growth in fiscal 2027 and enthusiastic about the year ahead. Jim, over to you.

Thank you, Rick, and good morning,everyone. As we close out fiscal '26, I want to take a moment to reflect on the execution and underlying momentum for Dynatrace over the past year. At the start of the fiscal year, we laid out a road map designed to put the company on the path to ARR acceleration.

We talked about the growing trend of large enterprise customers seeking end-to-end Observability solutions, the maturation of our go-to-market transformation, the powerful consumption economics of our Dynatrace platform subscription or DPS licensing model, the expanding opportunity in logs and the secular tailwinds driving Observability adoption in an AI-first world.

All of these were strategic underpinnings to stabilize ARR growth in fiscal '26 and position us for future acceleration. Let me walk you through a few milestones that defined fiscal '26. We achieved 4 consecutive quarters of consistent ARR growth at 16%. We delivered double-digit net new ARR growth for the first time in 3 years. We now have over 75% of ARR and 60% of customers on the DPS licensing model.

We exceeded our $100 million log management annualized consumption goal, growing 100% plus year-over-year in every quarter of the year. We delivered a robust 29% non-GAAP operating margin for the year while making targeted investments focused on accelerating growth and improving scale. And finally, we stepped up our share repurchase program, doubling our authorization to $1 billion in February and spending over $478 million in fiscal '26, representing 90% of our free cash flow.

Collectively, these achievements demonstrate the building momentum in the business and our confidence and conviction that ARR acceleration in fiscal '27 is in our sights. Let's review the Q4 and full year results in more detail. Growth rates mentioned will be year-over-year and in constant currency, unless otherwise stated. Annual recurring revenue, or ARR, ended the year at $2.05 billion, representing 16% growth for the fourth consecutive quarter.

This ARR result reflects a foreign exchange headwind of $4 million compared to our guidance. Adjusting for foreign exchange movements, Q4 net new ARR was $81 million, coming in near the high end of guidance. And net new ARR for fiscal '26 was $277 million, representing 12% growth with consistent double-digit growth in the first and second half of the year. This healthy performance was driven by strength in new logo bookings, growing momentum in logs and ongoing success in capturing large end-to-end consolidation opportunities.

We added 126 new logos in Q4, including a record nine 7-figure lands as we continue to target new logos in large enterprise accounts with a higher propensity to expand. The average land size in Q4 remained robust at over $200,000 and helped drive new logo ARR, up 43% in the quarter and up 30% for the second half. Our value proposition continues to resonate with enterprise customers outgrowing their existing DIY and commercial tooling solutions.

They are seeking business value from tool consolidation and coming to Dynatrace for the depth, breadth and automation of our unified AI-powered Observability Platform. Once customers experience the benefits of the Dynatrace platform, they have been quick to expand their usage.

Our average our average ARR per customer is now over $500,000. With cross-sell and upsell opportunities still ahead of us in our enterprise base, we believe the average ARR per customer opportunity could be $1 million or more over the long term. Gross retention rate in Q4 remained in the mid-90s, underscoring the value of the Dynatrace platform as mission-critical infrastructure our customers depend on.

Net retention rate, or NRR, on a trailing 12-month basis was 110% in the fourth quarter. Our DPS licensing model has now become our contracting standard. As I mentioned earlier, we exited the year with over 75% of our ARR and over 60% of our customer base on DPS. With access to the full platform, customers are adopting Dynatrace more broadly across their IT environments, resulting in increased consumption.

We continue to see a broader usage and deeper penetration of capabilities across the platform, notably in log management, which remains the fastest-growing product category, growing over 100% and exiting the year well over $100 million in annualized consumption. We expect fiscal '27 to be another year of robust consumption of the platform.

Moving on to revenue. Total revenue for Q4 was $532 million, and subscription revenue for Q4 was $506 million, both up 16% and exceeding the high end of our guidance range by 200 basis points. Turning to profitability. Q4 non-GAAP operating margin was 27% and above our guidance of 26% -- non-GAAP net income was $124 million or $0.41 per diluted share, $0.02 above the high end of guidance.

In our GAAP results, please note that our Q4 GAAP operating income includes $28 million in restructuring and impairment charges, primarily reflecting actions to align our cost structure with our strategic growth and scale priorities. These actions included targeted workforce reductions and impairment charges from office footprint rationalization.

Turning now to a quick summary of the full year results. Total revenue was $2.02 billion, and subscription revenue was $1.93 billion, both growing 17%. Non-GAAP operating margin came in at 29% -- we continue to drive scalability in the business model while investing for growth and scale with some years driving more leverage than others, while we sequence investments and expected returns. Over the past 4 years, we have expanded operating margins over 400 basis points, and our margin profile is well above peers of similar scale.

We also continue to drive efficiencies in our management of equity compensation. Fiscal '26 stock-based compensation as a percent of revenue was just under 15%, representing a decrease of more than 100 basis points from fiscal '25 levels. Non-GAAP net income for the full year was $518 million or $1.70 per diluted share. Our non-GAAP earnings factored in an effective cash tax rate of 18.5%. Free cash flow was $529 million or 26% of revenue, $4 million above the high end of guidance and roughly 100 basis points above fiscal '25.

As a reminder, this strong cash flow margin includes absorbing 600 basis points of impact due to cash taxes. We are somewhat unique relative to most software companies given our strong GAAP profitability and therefore, pay more in cash taxes. Excluding cash taxes, to provide an operational compare closer to our peer group, pretax free cash flow for fiscal '26 was 32% of revenue.

Moving to our share repurchase program. In addition to doubling the size of our share repurchase authorization to $1 billion in February, we significantly increased the level of buybacks in Q4, repurchasing 5.9 million shares for $224 million compared to roughly $160 million in Q3. This uptick in spend reflects our conviction in the company's operational momentum, long-term growth and cash flow trajectory and view that our shares are undervalued.

For the year, we repurchased 11.4 million shares for $479 million, representing 90% of our free cash flow. As of March 31, we had approximately $849 million remaining of the $1 billion authorization, and we plan to continue to take a disciplined approach to capital allocation, investing in innovation and growth while delivering value to shareholders. Turning to our fiscal '27 outlook. We entered the year with high conviction, fueled by a rapidly expanding market.

The shift towards agentic AI and autonomous operations has made Observability a foundational requirement. Further, intensifying vendor consolidation, inclusive of log management plays directly to our strengths as enterprises trade tools sprawl in favor of an AI-enabled end-to-end platform that can deliver a compelling ROI. We believe our fiscal '26 results prove we are winning and exiting the year in a position of strength. We have stabilized ARR growth, delivered double-digit net new ARR growth and continue to improve our go-to-market execution. With these building blocks in place, we are well positioned to sustain and improve our current momentum.

Now let's turn to our full year guidance. We expect ARR to be between $2.38 billion and $2.4 billion, representing ARR growth of 15.5% to 16.5%. This ARR guide implies full year net new ARR adjusted for foreign exchange movements of $320 million to $340 million, growing 16% to 23% and accelerating from fiscal '26 levels. While we don't provide quarterly ARR guidance, we expect net new ARR to be modestly more weighted to the first half of the year compared to historical seasonality as we entered the year with healthy forecasted pipeline coverage.

As usual, we'll revisit our full year ARR outlook once we get closer to the midpoint of the fiscal year.

Turning to revenue. We expect total revenue to be between $2.32 billion and $2.34 billion. Underlying that, subscription revenue is expected to be between $2.22 billion and $2.24 billion, both up 14% to 15%.

Note, our total revenue and subscription revenue growth rates are impacted by a difficult fiscal '26 compare from the change in accounting for on-demand consumption revenue and other miscellaneous onetime revenue true-ups.

We expect non-GAAP operating margin of approximately 29.5% Unpacking operating margins, we continue to drive efficiency gains across all functions, notably in sales and marketing and G&A. This operating margin guidance includes 150 basis points of additional OpEx leverage versus fiscal '26. This scalability is expected to be partially offset by a headwind of 100 basis points in gross margins from an increase in cloud hosting costs driven by robust consumption growth within our customer base.

We expect this margin pressure to be temporary as we execute on defined projects to improve our cloud cost efficiency with gross margins beginning to recover during fiscal '28. Another important area of leverage is stock-based compensation. We expect stock-based compensation as a percentage of revenue to once again decrease by 100 basis points in fiscal '27 to just under 14%. We expect non-GAAP net income to be $584 million to $594 million, resulting in non-GAAP EPS of $1.93 to $1.95 per diluted share based on 302 million to 304 million shares outstanding. Our effective cash tax rate is expected to be 18.5%.

We expect free cash flow margins of 26.5% and pretax free cash flow margins of 32%. As a helpful reminder for your modeling, due to seasonality and variability in billings, we expect free cash flow to be significantly higher in the first and fourth quarters and significantly lower in the second and third quarters.

Looking to Q1, we expect total revenue to be between $547 million and $551 million and subscription revenue to be between $523 million and $527 million. As I noted earlier, our Q1 total revenue and subscription revenue growth rates are impacted by a difficult compare from the change in accounting for on-demand consumption in Q1 last year.

Non-GAAP operating margin is expected to be 27.5% to 28%. Lastly, non-GAAP EPS is expected to be $0.44 to $0.45 per diluted share based on a share count of 298 million to 299 million shares. In closing, the strength of our Q4 and fiscal '26 performance sets a solid foundation for fiscal '27. The secular growth drivers fueling the Observability market continue to expand and our AI-powered end-to-end platform differentiates us and puts us in a strong competitive position.

We are committed to maintaining a disciplined approach to optimizing costs and improving efficiency. At the same time, we will continue to invest in future growth opportunities that we expect will drive long-term value. With that, we will open the line for questions. Operator?

[Operator Instructions]

Our first question comes from the line of Matthew Martino with Goldman Sachs.

Maybe to start, and I appreciate the setup on kind of the fiscal 2027 outlook. But when we look at kind of the Q4 net new ARR, it came in around 9% on a constant currency basis. And the fiscal '27 guide implies a fairly meaningful step-up in the net new from here.

Can you walk us through the bridge between the Q4 exit and what's embedded in the FY '27 growth algorithm? And then ultimately, the role the renewal cohorts around DPS are going to play in terms of getting you to that full year guide?

Sure. I'll take that, Matt. That's a good question. I think what I would tell you is that we had a very solid Q4. We had a great half 2. We had a great fiscal year.

So there's underlying momentum building in the business. If you kind of step back and you say, what did we do in fiscal '26? And I outlined it in the prepared remarks, it's a year of milestones in the year first. We stabilized ARR growth at 16%. We showed double-digit net new ARR growth for the first time in 3 years. Logs, well over $100 million, growing 100%.

The go-to-market traction is building. You've seen it in large deals, record new logo lands over $1 million. DPS now over 75% of our ARR, consumption growing at a very rapid rate. I outlined 2 years ago that we were going through a fix, stabilize, accelerate kind of journey. And we're in the -- we just finished the stabilization. If you look at this guide, you're right, this guide implies almost double the net new ARR growth from fiscal '26 levels. And it's all of the building momentum that we've seen. So it's not anything new like we need some new play. This is just a continued execution of the existing play.

So Q4 was a solid finish. You're going to have quarters that are like that. You're going to have quarters that are more robust than that. I can tell you that pipeline is healthy. Forecasted coverage is good. There's just significant interest. So I think it's just a continued building of what we've been doing. We talked about this with our go-to-market changes 2 years ago. They're starting to take root, and we expect that, that will continue.

And I would say, Matt, that AI tailwinds, agent tailwinds, cloud tailwinds are also contributing to our view of FY '27. So it's a combination of internal growth as well as market factors overall.

Our next question comes from the line of Eric Heath with KeyBanc Capital Markets.

Jim, just to continue on the point there. I mean, was there any macro impact in the quarter just given some of the geopolitical volatility? And did it cause some deals to push? And just any additional commentary you can speak to about the DPS renewal activity in the quarter among some of the fiscal '24 cohort of customers?

Yes. I'd say from a macro perspective, you know it as well as I do that certainly, there's a lot going on in the Middle East right now. I would not say that had any material impact on the quarter, something that we're monitoring for sure, for our EMEA business.

But I would say nothing notable. Relative to DPS, again, DPS even beyond kind of -- it is the contracting standard. Now that we have 75% of our ARR on that, -- and as we outlined that when you get customers on this vehicle, you can now team them up with our customer success teams and our SRE teams to drive consumption and consumption continues to grow at a very rapid rate.

As you would expect, consumption for our DPS customers is growing much faster than our non-DPS customers. We continue to see healthy expansions. One thing to note, I think I've mentioned this in the past that fiscal '27 is a year where you're going to see the largest cohort of DPS customers coming up for their annual resets or in some cases, their actual renewal.

And so there's an opportunity, again, depending upon how consumption grows to continue to see healthy expansion. So we're quite pleased with the traction there and the momentum that we're building in that area in particular.

Our next question comes from the line of Will Power with Robert W. Baird.

Okay. Great. Rick, in your prepared remarks, you called out what you all view as some of your architectural advantages. Can you just kind of speak to how that's resonating with customers, what you're doing, what you maybe still need to do to help demonstrate that? And maybe as part of that, anything you could share with respect to AI native adoption of the platform?

And then just maybe more broadly, what you're seeing in terms of agentic usage trends that might speak to? I think you talked about 500 customers using some of your agentic capabilities. But anything you could share on just the broader usage within those architectural advantages?

Yes. A lot of questions in there, Will, we'll attack them. So the architectural advantages, we typically will talk about Grail as a completely integrated, massively parallel processing data lake house. We talk about Smartscape as an integrated topological graph that can provide analytics and context.

We talk about Dynatrace Intelligence, which we launched back in January is covering really 2 elements of the spectrum. First element of the spectrum being around deterministic AI and then the second regarding agentic AI, where we actually can take action. What all of that is driving to is a completely integrated, fully unified platform that enables our customers to move into an agentic world successfully. And that agentic world enables autonomous operations to take hold, which is what they need to be able to manage increasingly complex overall IT environments and software -- and software workloads.

So we believe that, that architectural advantage is durable, and we believe it's sustainable. And that when you get into manual tagging of data stores across multiple data stores, you end up with an environment that is much more fractured. So that was piece number one.

With regard to AI natives, we have been focused mostly in the history of Dynatrace on IT operations, on CXOs. That's how we've ended up with end-to-end Observability, and that's when we get into these larger deployments for large customers where we've been incredibly successful with the go-to-market plan over the last couple of years, which we initially deployed. That is evolving to include developers. And we've made huge strides in the platform beginning 18 months ago with new implementations around elements like we mentioned last quarter like Bedrock agent core integration or Azure SRE agent.

This quarter, we talked about Claude Code integrations. Now Assist headed into AI control tower. So we continue to evolve the platform to enable more developer adoption. That developer adoption opens and unlocks the opportunity with AI natives, which we're driving along with developers now.

And finally, you mentioned agentic. Agentic is certainly a very strong opportunity for us in multiple ways. Number one, as it's driving us toward autonomous operations in our existing core base of enterprise deployments. But secondly, also in, as I mentioned, a brand-new way of development.

We see a sea change in a movement from software development life cycles to AI development life cycles, and we believe that Observability fundamentally is going to be a core foundation of that. We also believe that Dynatrace based on our architecture going back to my first remarks, has an opportunity to be a primary participant in that shift from the software development life cycle to the AI DLC. Three different questions. So I try to attack all 3 of them, but good question.

Our next question comes from the line of Mark Murphy with JPMorgan.

This is [Indiscernible] from JPMorgan on for Mark Murphy. You mentioned closing a record 22 deals with more than $1 million ACV. I think 9 of those were new logos. We had a couple of channel checks over the quarter that mentioned momentum in the Dynatrace business and new logos, large new logos specifically. So I'd love to kind of hear what you think is driving some of the momentum with the large deals and new customer lands at scale.

I'll take that. I think one of the things that we've been talking about, I think I began talking about it probably 2 years ago, and I talked about it as an emerging trend of these very large enterprises that had fragmented DIY and commercial tooling solutions that were looking to vendors for consolidation, both for economic benefits and also just a better customer experience. And so that trend has continued.

And I would say, especially in very large customers that there is huge interest. There is significant interest in integrating fragmented tools to save money. There is money to be had when you can go from multiple vendors to one vendor, and you can get a better experience with Dynatrace for all the reasons that we've outlined. So that trend has continued. I'd say the changes we made on the go-to-market side, we're developing much better and deeper relationships with C-level decision makers. These are the people that make these decisions.

And so it actually is a market tailwind moving in that direction. And we're in a good position to benefit that from the platform depth and breadth that Dynatrace provides. And so I expect that, that will continue.

Our next question comes from the line of Koji Ikeda with Bank of America.

Jim, maybe a question for you. When I look at past transcripts and the way you've characterized the guidance was you always used the word prudent. And I noticed this time you didn't. And I look at -- you definitely talked about much stronger net new ARR growth this year. And so I just wanted to ask, has the guidance philosophy changed with the removal of the word prudent? And if so, why now?

No, our guidance philosophy has not changed, Koji. I would say that the way we've guided in the past and the way you should think about this guide. I think I've built enough experience with you guys that you know how I do guide. I don't think it's necessary to continue to kind of provide that language that you should expect that what I guided here is consistent with how I've guided historically.

Our next question comes from the line of Matt Hedberg with RBC Capital Markets.

Rick, I wanted to come back to some of the first couple of questions that were asked. And referencing your script, there's a lot of positivity about industry trends and why the Dynatrace architecture is well positioned to capture that.

But I think the question people keep asking me is, given those, why aren't you growing faster? I think NRR was maybe a little bit lower than what people are thinking. And I guess I'm just wondering like is there a lag between enterprise AI and inferencing spend and ultimately, your Observability products? Like is it just a timing thing that's holding you back from better growth?

Question, Matt. I do think that there is a bit of timing difference between what we're seeing in the enterprise and what AI natives are seeing. I think that is with regard to, for example, agentic deployment, agentic usage.

As I said in my remarks, we're already seeing 500 customers plus deploying and using our agentic capabilities. We've got now more than 850 customers that are using us to evaluate the reliability and trust of AI and LLM workloads. So in the enterprise, we certainly are beginning to see that kind of adoption.

And we believe that, that adoption will, of course, through the DPS mechanism, get deployed into the numbers over the course of time. APS, as you know, does have a bit of a lag with regard to expansions vis-a-vis a straight consumption model, which is why we see some of the delta between our consumption numbers with those being in the low -- in the 20% plus range relative to ARR. So that's some of what you see. With regard to AI natives, this is where I believe the new evolution evolutionary elements and development capabilities in the platform will facilitate us expanding to the developer, expanding to AI natives more aggressively as we look to FY '27, and we're beginning to see some of that momentum in the AI natives as well.

Our next question comes from the line of Raimo Lenschow with Barclays.

Perfect. Can you talk a little bit to -- on the large customer momentum? That sounded like a very good outcome this quarter. And I was also surprised on the new customers that came up straight into large. Is that something that you're seeing now as your offering got a lot broader, the platform pricing kind of makes adoption really nicely there. Is that something that you're seeing in the pipeline as well?

Yes. I mean, Raimo, I'd simply say it's all of the above. And I kind of answered it previously that large enterprise customers are looking for vendors to consolidate on to be able to integrate fragmented tools and provide a better experience.

And it becomes even more so when you move into an AI-first world. And so we're in a great position to be able to do that. And so I would say the go-to-market changes that we've made have allowed us to go access and penetrate those opportunities. One thing I will tell you is that while we're not making radical go-to-market changes at all for fiscal '27, it's a continuation of what we've been doing.

The traction that we've made in our large strategic accounts, which is think of them as the Global 500, we're going to extend that motion down probably to another 150 or so customers where we're going to improve the density of coverage and get closer to customers to be able to drive either new logos or expansions with these existing customers by getting closer to them. And so I think it's just -- it's a phenomena of what's happening just in the industry that large customers are looking for vendors that they can consolidate on that -- and we have a very unique position to be able to give them both better economics and a better kind of business outcome.

I would just add, Raimo, that I believe that point product Observability is dead or at least dying. And that's why we see some of the ongoing expansion that we saw this quarter and that we see in the pipeline related to end-to-end Observability. And we have a great proven solution there for large enterprises to deploy. And it's at the data layer, it's a domain layer, it's at the persona layer.

All of those layers are looking for end-to-end Observability because that is what is enabling the best outcomes of Observability, number one. And number two, it is a necessity as you look to an agentic future to be able to leverage that underlying fabric in order to deliver the agentic future that's expected leading toward autonomous operations.

Our next question comes from the line of Ittai Kidron with Oppenheimer & Company.

Jim, I had a couple of things I needed to hopefully can clarify on the fiscal '27 guide. You made a comment that net new ARR is going to be weighted towards the first half. I'd love to get some color on this. Again, were there deals that [Technical Difficulty]

You're breaking up, I can't hear you.

[Technical Difficulty]

For ODC. If you could break that down, that would be great.

Yes. I couldn't hear the question. The only thing I heard in the question was the first half. I think you said, could I clarify the commentary about maybe net new ARR being a little bit more weighted to the first half. And I would say it's modest, but I'd say we wanted to make sure we provided some color on that.

I think it's mostly a function of -- we have very strong forecasted pipeline coverage. It continues to build. And so I think what we're signaling is that we expect to have a good start to the year, not just for Q1, but also for Q2. Obviously, your visibility over the next 3 to 6 months is greater than over the kind of beyond that. And I'd say what you see is this is just growing visibility and confidence around what we can deliver.

Our next question comes from the line of Sanjit Singh with Morgan Stanley.

I wanted to get back to some of the drivers that you're seeing in the core business. Clearly, vendor consolidation, tool consolidation is a sales motion that you guys have been executing very well on and has probably been the driver of enterprise large deals for the past couple of years. To what extent is the business seeing the impact yet?

Or do you expect to see the impact from just the big increases in just software development initiatives with these coding agents getting adopted, not even if we just even exclude the AI natives, but even in the enterprise, you're seeing quite strong adoption of coding agents and that should drive more software creation. What do you think that ultimately drives -- comes -- emerges as another core driver for ARR growth for the business?

Yes, I'll take that, Sanjit. Absolutely, as we mentioned in the prepared remarks, I think that whole notion of AI evolution is a core driver. The ability to use AI coding agents is critical. We talked about the integration into Claude code, for example, as a mechanism for that for debugging, root cause analysis, those sorts of elements. So we do see this going through a few stages, whereas today, they're using coding assistance. Coding is done at least in part by AI systems and AI capabilities.

We see that transitioning to an AI DLC where the primary builders of code are, in fact, agents themselves, where agents are building and operating code. And so we are going to go through rapidly this process evolving through a software development life cycle in our perspective, all the way through an AI DLC. We absolutely are seeing momentum in this area in the enterprise with our customers.

That's where I talked about the 500 customers or so already using us to do agentic integrations. So we're seeing this and the expectation during FY '27 is that, that will be a growth driver driving actually increased and accelerated ARR.

Our next question comes from the line of Keith Bachman with BMO Capital Markets.

I wanted to ask a clarification and a question. Jim, if you don't mind, could you just relate what you think the NRR will be for '27? I'm just trying to back into the net new guidance. And then my broader question, Rick, for you is, when I think about Dynatrace, you've made progress in logs, maybe a little less so in security in terms of at least for investors, the visibility we have with that potential.

But when I think about you versus your nearest publicly traded competitor, I think there's been more meaningful product expansion. And so I just wanted to see philosophically with Grail out there, how do you think about the product expansion opportunity over the next couple of years, particularly now with an activist involved who may be looking for more margin expansion. But if you could just speak to your product expansion philosophy over the next couple of years?

Let me take the front end of that, Keith, and then I'll let Rick comment on the broader question. So we don't guide specifically between new logo and expansion or NRR. You should expect that it's going to be similar to what we've had historically, which is net new ARR is going to be roughly 1/3 new logos, 2/3 expansions.

As you've seen this year, sometimes it may be weighted more towards one than the other. And I think that's a function of reps are compensated on maximizing bookings, whether it be new logos or expansions. And so that's one of the reasons we don't guide, but can certainly look at it that if you look at the historical levels, that's roughly what we're going to operate.

And so to your point, if you look at the high end of the guide, which is net new ARR growth of 23% or 24%, you're going to see it both on the expansion side and on the new logo side.

And Keith, on the broad product acceleration front, what I would say is there's been a huge amount of innovation in the Dynatrace platform over the last couple of years. Of course, we've delivered Grail, foundational data lakehouse. We've talked about that. We delivered Dynatrace Intelligence back in January.

This is a major setup for an agentic operations system that can allow for true -- truly autonomous operations, leading to the evolution of overall development through an AI DLC. Dynatrace Intelligence is really a foundational enabler of that. As you mentioned, we have logs. The logs capability is quite substantial, as Jim mentioned in his remarks, now well above $100 million, growing at more than 100%.

So a huge amount of opportunity there, bringing logs into an end-to-end Observability Platform, we believe, to be quite foundational to getting end-to-end Observability right as a foundation for the agentic future. Talked about AppSec. We don't say -- we haven't said as much about AppSec. It is absolutely a relevant ongoing investment thread for us, not growing as fast as the logs front, but we do see ongoing convergence of Observability and security use cases, and so we're focused on those.

And I would say now that our third-gen platform continues to emerge and be more mature, you're going to see a further acceleration in innovation around feature set and functionality for add-on capabilities in the platform as we look at.

Our next question comes from the line of Patrick Colville with Scotiabank.

I guess maybe this one is to both Rick and Jim. If I look at the financial model, we had a lot of questions on the top line. I just want to kind of zoom in on the bottom line, in fact. The guidance, you gave this helpful commentary that expecting GMs to come down slightly in fiscal '27 due to cloud hosting costs.

Do you mind just unpacking why that is exactly? And then also just maybe just zooming out, like what is the philosophy on profitability as of May 2026 because Dynatrace is wonderfully profitable, but we've been at levels that have been consistent now for about 2 years, and you're guiding to kind of flat again in fiscal 2027. So like how are you thinking about that aspect of the business?

I'll start with Patrick, that we continue to drive efficiency in the business, which is why I mentioned that if you look at operating expenses, this guide implies 150 basis points of incremental leverage in operating expenses. We are going through a bit of a, I'd say, a year with gross margins, which is kind of -- I'd say it's a good news, bad.

The good news is what's driving that is robust consumption of the platform. And so all the reasons we talked about that consumption is growing rapidly, growing significantly faster than ARR growth. There is a lag between when you see that in an expansion and when you see that show up in revenue. Whereas when you look at cost of goods sold, you see that immediately because it is recognized as incurred. And so it's truly a function just of growing consumption on the platform. And there's a bunch of initiatives, as you can imagine, that we're driving very defined initiatives to improve our cloud cost efficiency ratios. There's always a give and take between R&D dollars that are spent on those things versus R&D dollars that are spent on efficiency.

And so our expectation is that this is temporary and that as we enter fiscal '28, you're going to start to see margins go back -- gross margins go back to more historical levels. I will remind you that even a bit of pressure on gross margins, we still have incredibly robust gross margins even with a 100 basis pointhead wind. So this is a kind of a philosophy of continuing to drive leverage in the model. As I mentioned in my prepared remarks, some years, we're going to do more than others. Sometimes we sequence investments where the return on those investments comes in the following year. But you can expect we will continue to drive efficiency across the business.

Our next question comes from the line of Miller Jump with Truist Securities.

So the logs momentum continues to stand out. Can you just talk about where you are in your ability to displace competitors for security use cases in logs and the comparative size of the market opportunity that you see for Observability versus security there?

I'll take that, Miller. We have not done an on-prem SIEM. So we have not addressed that with the security use case. We have addressed the Observability use cases, number one. Number two, as we've reported in the past, we are working on and we'll expect over the course of time to deliver a cloud-based SIEM. So that will begin to take on some of the security use cases around logs.

But for the moment, most of the commentary has been around Observability logs.

And that brings us to the end of the call. So let me just wrap up. First of all, thank you all for your engagement and continued support. We really do appreciate it. FY '26 was a solid year of stabilized ARR with us at 16%. We delivered double-digit net new ARR growth through the course of the year. We saw it as a year of exceeding $2 billion in ARR. And of course, we delivered very, very strong logs momentum, as we indicated, now well more than $100 million, still growing at 100%.

We have a number of growth drivers in the business. We're very excited about what's happening by way of innovation. And we believe we have a number of market tailwinds around AI, around cloud, around agentic that will provide further fuel to the opportunity to accelerate FY '27 ARR growth, which is precisely what we're looking for with accelerating net new ARR growth at the midpoint of our guide. We thank you again for joining. We look forward to connecting with you at upcoming IR events, and we wish you a great day.

Goodbye. This concludes today's conference call. You may disconnect your lines at this time. Thank you for your participation.

All right. Continuing the session before lunch. I'm Sanjit Singh, I'm the infrastructure software analyst on the Morgan Stanley software research team, thrilled to have the management team from Dynatrace. Chief Executive Officer, Rick McConnell; and Chief Financial Officer, Jim Benson. Rick and Jim, thank you for joining us at the TMT conference once again.

Thanks, Sanjit. Always good to be with you.

Awesome. Before we get into the discussion, for important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures.

I'm going to start out with my comments, I'm a big bull on observability in the category, not just for this year, but going forward, particularly in the agenetic world. We'll dive into those conversations. Just to give us some context, Dynatrace is coming off a couple of strong quarters. Net new ARR is staying at 16%, constant currency for the second quarter in a row. The ARR base is now up to $1.9 billion. You got an operating margin in the high 20s. Trailing 12-month free cash flow margin of 32%. So squarely in that rule of 40 plus territory. We are at a time in the market though, where there's a lot of revisiting of first principle thinking when it comes to software providers and how they pave value for their customers.

So Rick, with that as a context, what are the core problems that Dynatrace is helping customers solve today? And what problems will Dynatrace help customers solve going forward?

The simple way to, I think, begin, Sanjit, is number one, we deliver through observability, resilient software. And at the end of the day, there is no time in history that we can recollect where delivering software that worked perfectly was more critical. So that is a foundationally #1 in terms of priorities. And in the observability space, I would say, overall, we are at the -- we are in an era where observability generally is becoming absolutely mission-critical to essentially every company in the universe that is delivering core software.

The second piece that is evolving and evolving rapidly by way of problem we're trying to solve is reliable AI. Because it isn't just about delivering software that works. It is about delivering AI-first workloads that actually are delivering the outcomes, delivering the content that you're expecting to be delivered.

Yes. That makes a ton of sense. And maybe we can dive a little bit deeper in terms of the product innovation cadence at Dynatrace. There's a lot of buzz coming out of your conference, and that conference is called Perform at the end of January. We'll get into the specific product analysis, but the big theme from my point of view was around Dynatrace Intelligence. And this representing the next major evolution of the Dynatrace platform. So can you give us a sense of what makes up the Dynatrace Intelligence platform. What capabilities and value will this unlock for customers?

So Dynatrace Intelligence, we announced at our Perform Conference about a month or so ago. And Dynatrace Intelligence fuses together the innovations of deterministic AI along with Agentic AI. Now deterministic AI, we look at it, Dynatrace, is really our super power. This is what we would argue we do better than any other observability company on the planet. And the reason is because we've had 20 years of context of building systems based on an underlying data lake house with Grail, a software top logical map using wrapping and Smartscape, elements of artificial intelligence, beginning with causal AI to predictive AI to generative AI, all of which are designed to indicate to a software developer or software provider, specifically what is happening in that software environment at any given moment.

And when something breaks, what broke? With a very high degree of clarity, specificity and accuracy so that you can take immediate action. We do this one of the largest organizations on the planet that have billions of interconnected data points that we are analyzing and providing results and analytics against in real time. That deterministic AI, that foundation and what precisely is happening by way of analytics in your environment then sets up the foundation to be able to take agentic action against that set of analytics.

And that's where the agents come into play. We believe that what the market will hear what customers will hear from basically every observability players. I've got agentic AI. I'm delivering agents, they can take action our supposition when we get into things like proofs of concept and others is that you have to start with reliable trustworthy input to those agents. Otherwise, those agents are going to be taking actions that are guesses. And so the result of that is we believe that Dynatrace Intelligence is really unique in the market space of delivering both what the answers are, what the analytics tell you along with the agents linked into that, that can take action.

And by the way, those agents in that agentic framework are really an ecosystem of agents, not just Dynatrace agents. That can take action, for example, through hyperscalers, through ServiceNow, through Atlassian, through others to essentially enable auto prevention, auto remediation, auto optimization in your overall environment, which gets you back to where we started in your very first question, which is resilient software and reliable AI.

Yes. And I had -- my next question was around some of the things you announced around agents. But before I get to that, if we kind of zoom out and get at least from my point of view, why I'm bullish this category, we think about the attach rate of observability to agentic deployments. Do you feel like that that's going to be as high or even higher than sort of like the cloud-native application era. I mean, these agents are going to be accessing critical business systems. They're going to be calling external tools. They're going to be interfacing with your end users. Like is it sort of obvious that this is all going to be monitored, tracked, logged from your guys' perspective?

We have a theory, which I would say is early stage at the moment, but it speaks to precisely what you're suggesting. And that is, today, we look at the preponderance of workloads that happen across enterprises, the largest enterprises that we typically would sell to. Maybe 30% plus or minus of workloads and traditional workloads are observed by Dynatrace. Why is that? Well, if you need to observe your primary set of infrastructure, you need to observe your primary mobile app, your primary website, whatever those workloads may be.

But I was speaking to a customer recently down in Australia, and their comment was we have 2,000 apps we have this much -- we're not going to -- we don't need -- they don't have the same level of criticality. We don't need to observe all those workloads. In the case of agentic AI, especially, and in an LLM environment that is producing probabilistic outcomes, we believe that you really are going to need to observe darn near 100% of those workloads because it is going to be sufficiently independently operating that you are going to have to do extra work to have systems that can give you the confidence that you're delivering resilient capabilities.

You're also going to have the systems that are mission critical to delivering reliable AI outcomes. And so the result of it is, we believe that in this world that is evolving rapidly to an AI-first world, 2 things happen. Number one, explosion of workloads. So you just have more raw workloads. And then the second is your very point of the question, you need to be able to rely upon those outcomes in such a way that probably drives more observability as a penetration rate against those workloads.

Yes, it makes tons of sense. So let's talk about some of the agentic capabilities you introduced at Perform, your user conference. So you have an agent-first reliability engineers, you have an agents for development, you have agents for security teams. Which of these are you most excited about from a monetization perspective? And how are these domain-specific agents priced.

Sort of like asking what's your favorite kid. It's hard to say. I mean, I think that they are all critical. And the way to think about the agents is, first, you have the foundational agents. These are agents like an SRE agent that would tell you root cause analysis. For example, you need to know specifically what's happening. And then sitting on top of that, you have sort of management and supervisory agents that can direct traffic. So do the agents tell, a, Dynatrace agent to take action to resolve a particular incident maybe to turn off a feature, for example, that we can do internally. Or do you assign that to a third-party agent to like an AWS agent that may provision more storage or whatever it might be or a ServiceNow agent and might take some workflow action.

So that's sort of the next layer. Third layer would be those agents that actually could take action to resolve issues and then you have a series of ecosystem agents that integrate. So it is sort of a very thoughtful stacked map that can define what agents are taking action. But I see that as -- while critical to overall architecture and the architectural topology, foundationally, the more critical piece, I think, for investors and others take away even customers with whom we speak is that start with a deterministic foundation, you then have the confidence to take agentic action, and we, Dynatrace, have produced an architecture through Dynatrace Intelligence that enables you to take that that agentic action thoughtfully either through Dynatrace agents or third-party agents to be able to deliver against those elements of essentially an auto correcting software ecosystem, which is ultimately what we all want to be able to deliver.

Awesome. Let's talk about in terms of sticking on the theme of product innovation. You launched your next-generation real user monitoring service powered by Grail, powered by Smartscape and Advanced AI in the context of that you've gotten to like $100 million consumption run rate with logs. The question here is like, given what the traction we see today with digital experience monitoring and now with this next-gen platform on RUM, how confident are you that this can be your next $500 million, $1 billion plus business?

Well, I will tell you that we already have $400 million-plus businesses. We obviously -- one of them, obviously, most recently at Logs our DEM business is well over $100 million in our Infrastructure Monitoring is actually the second fastest-growing business, interestingly enough next to Logs business. And then there's obviously full stack for APM. So the expectation is across all these categories and some of the things that Rick talked about is more workloads, more workloads across a broader stack, the biggest sales play that we've been able to drive has been end-to-end observability.

These are customers that are looking to consolidate fragmented tools onto one platform. You see in our land sizes for new logos, you see it in the expansions that we're doing. And so these are going to be primary sources of growth now and in the future.

I want to have a discussion with both of you on Dynatrace's defensibility in the era of AI. But let's get an update first on just some of the trend lines of the business. I wanted to walk through this with you, Jim. In terms of the ARR performance, we've seen constant currency net new ARR stabilized at 16% for multiple quarters after years of deceleration. Can you talk us through the specific factors that contribute to stabilization? And do you feel like this is kind of the new baseline for growth as we look forward into fiscal year '26?

Yes. So I appreciate the question. So again, to your point, we've had 3 quarters of stabilized ARR growth at 16%. We've had 3 consecutive quarters of double-digit net new ARR growth, which obviously fuels ARR. Our guide for the fourth quarter, at the high end would suggest this continues. To your point, we haven't done this in several years. You say, well, what has caused that? Well, what has caused that was changes we said we made basically a little -- almost 2 years ago now, where we made go-to-market changes. And we were very clear when we made those go-to-market changes. These were changes to go on the offensive.

So those changes were we oriented more resources around large enterprise accounts, what we call the Global 500, so the 500 largest companies or governments on the planet. We continue to fortify our partner ecosystem, in particular with the GSIs. And so everything we put in place 2 years ago, we knew year 1 was going to be a maturation year. We needed to get the resources staffed. We needed to get the alignment going. We changed some compensation plan designs. And so we knew year 1 was going to be a period of building. What you're seeing this year you're seeing execution consistency, which is exactly what we expected when we built the plan 2 years ago.

So the maturation of the go-to-market model has continued to advance. I expect that will continue going into fiscal '27. And then you look -- even though we're not going to guide here, you look at fiscal '27, there's a lot of momentum in the business that we expect that if we can continue to execute like this you'll see it continue into next year.

To follow on that point, and this is an area of question that I get asked a lot about investors. The underlying consumption in the platform, you guys have purchase going north of 20% and outpacing the subscription revenue. So in terms of the lag between consumption growth and then that materializing ARR, what's the best way to think about those 2 dynamics?

Yes. I mean, I get that question a lot because one of the things we wanted to make sure we shared with investors is what's happening with the underlying growth in the business, which is how customers are consuming the platform. Obviously, our model is a subscription model. And so subscription model as revenue, is ratably recognized. That isn't always how consumption occurs. And so if ARR is growing 16%, and consumption is growing 20%, it will converge. The challenge is the timing of it. There's a lot of dynamics that go into when that will occur.

We do look at something internally, we look at the consumption to ARR ratio. And the way to think about that is the headroom. What is the headroom a customer has before they need to do an expansion. And so for us, it's about continuing to drive more consumption. And one of the things that we've done is even though the model is a subscription model at its heart, the Dynatrace platform subscription model is a consumption model.

Customers commit to a dollar amount, they can commit to a term. And then they consume. And it's a frictionless model, they can consume because they have the rate card for every capability on the platform. They're getting value, and we can work with them on driving more adoption of different product capabilities, they'll consume more. The more you consume, you can consume faster and it will burn through your commitment early and you'll do an expansion.

And so I expect that we will continue to provide that as a metric, like how we're doing around driving consumption. We now have teams of people. They're measured on this. They're compensated on this. We have specific product strike teams for Logs measured on consumption. Product strike teams for DEM measured on consumption. Product strike teams for application security, measured on consumption. And then our CSM teams are also measured on consumption for the accounts that they support. They're not product specific. And so we've advanced a bunch of activities that are very consumption oriented. That wasn't the case 2-plus years ago. It was a very SKU-based model. Now it's a get them on the Dynatrace platform subscription and drive consumption.

That's a great context there. One of the things I've been saying all week, Rick, is that my conversations at the beginning with investors was sort of like, Sanjit congratulations, you cover infrastructure software, you cover data platforms, your companies don't have seat-based models, you're so lucky. And in the last couple of weeks, now everything sort of gets questioned, right, in terms of the defensibility. So I wanted to spend some time with you, Rick, talking about how Dynatrace is positioned in this era of AI and give you some of the scenarios that I get asked about and get your sort of perspective.

One of the questions I've been getting is how does the value proposition of Dynatrace platform changes when the agents are doing the investigating and triaging versus human site reliability engineers or DevOps personnel working through dashboards?

On that topic, Sanjit, specifically, I would say that we expect exactly that evolution we expect over the coming years. And by the way, what the investment community is talking about at the moment, in most cases, is not what customers are talking about with us at the moment. There's a broad disconnect, I would say. But if we look out over the course of the coming years, we do expect that humans, end users, if you will, will become a relatively lower consumer of the Dynatrace platform and agents will become a relatively higher consumer of the Dynatrace platform.

That does not, in any way, translate in my view to any disintermediation of observability by AI. Rather, we see observability as being mission-critical to these AI workloads where agents are taking action that have to result in reliable outcomes. And you're simply, in our view, not going to have a probabilistic system providing input to a probabilistic system on delivering an outcome that is trustworthy or the kinds of organizations with whom we do business.

So it is that sort of notion that we believe that observability and in particular with some bias, Dynatrace, can and should become the control plane or reliable AI. And that really is based on an architectural moat of, as I mentioned earlier, Grail, Smartscape, Dynatrace Intelligence, the various technologies that we have built into the platform to deliver both deterministic AI and certainty of answers that can be trustworthy and that can be acted upon in a reliable way to deliver the AI outcomes of the future.

Whether those outcomes are delivered by an end user or by an agent, in some sense, is not that impacting to our overall business model. In fact, to the extent agents are a bit chatty and they're going to consume more analytics than an end user would then, if anything, we believe that that's a tailwind to Dynatrace just as AI broadly as a tailwind to absorbability and Dynatrace by virtue of generating more workloads.

And one thing I'd add on that, Sanjit, is that we're not a seat-based model. And so because we're not a seat-based model or a consumption-based model, so we monetize through consumption. So get them on the platform again through the Dynatrace platform subscription. We don't even have to change our monetization model for the way we go to market with product packages. It's already in place.

Yes. I take advantage of those elements, yes. And correct me if I'm wrong, one of the marketing messages that you've had for years even before the [indiscernible] was answers -- like literally, answers not dashboards, right? So...

The answers are not guesses. That actually came from Rick.

Yes. answers, I guess, is one of them. And the other thing we would say is, you're right, the answer is not dashboards. It is it is really critical for our customer base to get precisely to answer, not try to ascertain what's happening in the environment through a dashboard and through alerts in that environment.

Awesome. Let's go through the second kind of flavor in terms of investors' concerns on the category more broadly, but also with specific to Dynatrace. So this other angle is that the ability to combine open-source tooling to collect metrics, chases and logs, and combine that with an agent, either for one of the model labs to reason over the data and execute an incident response. And so I guess what investors are getting at is the potential for customers to manage observability themselves at theoretically lower cost or even more nuance, negotiate better pricing when it comes to their Dynatrace renewals and bills. Why is this line of thinking off base?

My response to that is that, look, the primary deployment of observability throughout history of observability has been DIY. It is, relatively speaking, quite recent that companies like Dynatrace and observability companies have come into the fray. And so DIY continues to be feasible that you could use open-source tools, you can use, OTel, Open Telemetry, you can bring in these sorts of elements and you can manage it on your own. The fact of the matter is that is getting more and more difficult to do each and every day.

Now might an LLM decide to do that for their own infrastructure, maybe, why? Because that is core to their business, delivering a resilient LLM that has reliable AI output, as you can imagine, for the LLMs is quite core. In the case, you've an enterprise, the largest banks, the largest health care organizations, the largest airlines, delivering a dynamic end-to-end observability solution that can process billions of interconnected data points contextually in real time. That is super complicated, and it takes this sort of broad-based platform architectural moat that we've described to have constructed that. That is not, in our view, a likelihood of an outcome, certainly for the vast majority of large enterprises.

If we call this category monitoring, and that goes back into the late -- mid- to late 1990s. One of the things about this category monitoring observability has been highly tied to changes in compute cycle. And the history is being that the leader in one cycle doesn't typically stay the leader in the next cycle. I actually think in this category, Dynatrace is one of the true success stories. You guys were a leader, multiple cycles to go when we were building on-prem job applications. You guys innovated, rewrote the platform from a clean sheet of paper, looking like aces today, but in terms of this broader AI debate, what are the ingredients of the business that allows Dynatrace to stay on top of the innovation frontier with potentially a new platform shift ahead of us.

Well, we've talked about some of it. I think the Dynatrace Intelligence is a core part of that. This notion of it's not just about deterministic AI and agentic AI. It is about using deterministic AI and agentic AI outcomes becomes particularly critical and doing so in real time. That dynamic in our view, and we've talked about the shift toward agents as consumers, if you will, observability of observability data. And in that environment, I would say that structure, that architectural context is even more critical to deliver.

So that becomes sort of the next generation, even as AI-first sorts of models evolve, those models are going to evolve in a way in which observability foundationally becomes more critical. But you really do have to have the deterministic piece. And I'd say that is where Dynatrace differs from others in the market to be able to provide that underlying foundation for success.

I think the other thing just covering the space, in the context of investors debating with cost of code going to 0, that customers can now build anything, right? I think what you guys have been doing, what some of your peers have been doing. These aren't tools. These are distributed compute platforms that processes billions, trillions of data points in real time. It's not like we can go out and build this easily. This is pretty hardcore stuff.

So some of what you're suggesting, I think, is exactly right, which is -- it is -- at least in our view, it is much easier for an LLM as you vibe code something to rebuild something that has a standard workflow. Our workflow at any particular customer, at any given moment is highly dynamic, highly variable depending on what's happening at that moment in time based on a data plane and contextual data as input to that system that is inherently different than it was seconds ago, let alone minutes or hours ago.

And that dynamic element means that the platform always needs to be learning. And that is a shift that doesn't result in, I'm producing a piece of code for a moment of time, and it takes that sort of domain expertise of the individual environment in the context of the overall platform and its generation that delivers meaningful value.

Yes. That's great context. So we've talked about the secular debate. Let's get down to the field level and talk about some of the things that are going on in the ground in the business. Starting with kind of market to market in terms of the go-to-market progress. We're about -- I think, Jim, you mentioned almost 2 years into the go-to-market changes. You stated that visibility and confidence is greater now than a year ago with pipeline also accelerating. Where are you seeing the most success and which elements are still maturing.

So I'd say it's playing out about as we expected. So again, when we outlined this almost 2 years ago, where we are in our journey is about what we expected. I'd say the #1 sales play, I think I may have mentioned it earlier, is end-to-end observability. So we have 3 sales plays. We have end-to-end observability. We have an APM land play where you land, you do a POC and you expand from there. And then we kind of have a cloud-native play as well. I would say, universally, the most successful sales play has been end-to-end observability. That we have a sales organization that knows how to sell it. The value proposition is very clear. We can actually allow them to save money and they consolidate tools and they can get a better outcome.

So I'd say we're still -- even though I talked about this 2 years ago, Sanjit, that this was an emerging trend. This is a prevalent trend now. This is more and more enterprises are looking to consolidate fragmented tools onto one platform, not unique to our particular industry. You're seeing it in security in other places as well. So I'd say it has been a source of growth, and I think it will be a continued source of growth because it's still many companies are not doing this. I'd say the area that we're making great traction, and we're very proud of the fact that we hit our $100 million milestone for Logs.

But that's just the tip of the iceberg. So to your point, we have a lot more growth to be had within Logs. 40% of our customers leverage our Log solution, continue to grow the cohort classes. And so they start on the platform smaller, and have grown significantly. So between end-to-end observability, Logs in this growing use cases, that you will see this also with AI-native workloads that these are all areas that will continue to mature. And the good news is the go-to-market motion is we're year 2 which is where we thought the productivity improvements would begin. We expect those productivity improvements to even accelerate further in fiscal '27.

I mean, to your point on like the consolidation buying behavior, there's -- if I just kind of look at this market, it's been crowded. There's a lot of players. You can probably name a dozen different players. But there's probably not that many they can pull off the consolidation deal, right? And so when we think to that and then I look at the success you've had in winning large deals on the pipeline being constituted with deals over $500 million, kind of speaks to your ability to really win those consolidation opportunities.

When we think about managing the timing of variability inherent with these large enterprise deals and while maintaining guidance accuracy, what rate of success are you seeing converting the pipeline needed to see, not only your goals for fiscal year '27, but just making sure that you get more confidence into your guide?

So I would say 2 years ago that we were growing pipeline or closing pipeline 2-plus years ago, with an or. And so I'd say the consistency around what we drove for net new ARR quarter-to-quarter varied a bit. I'd say what we have now is we are growing pipeline and closing pipeline at the same time. So pipeline growth is very strong. I'd say the quality of the pipeline is also very strong. And we measure that by just inspecting the pipeline and looking at kind of where we're at from a sales stage perspective. So -- and I think that comes from the go-to-market changes that we made.

Again, we may go-to-market changes to get closer to customers that one of the big changes we made around the enterprise accounts was to go from maybe 10 accounts per rep to say, 4 to 5, which means they're a lot closer to the specifics of their customer base, which means when you're looking at pipeline and deal flow, there's a lot more intimacy around what exactly is happening with that brings confidence now around closing. Now your timing might vary a little bit, but I would say even though we continue to see end-to-end deals keep growing in number and growing in size.

I'd say our confidence in our ability to not have to land all of them. Some are going to maybe close one quarter, some will close the next quarter. I'd say we have building confidence that the consistency in the go-to-market execution just continues to advance, and I expect it will continue to.

That's definitely encouraging. I think from my seat, when I think about the last 12 to 18 months. It felt like you guys would execute on quarters, knock down some of those bigger deals, we'd see good ARR results, but because the pipeline was weighted toward those deals. We had to be more conservative on the forward quarter. Is that also part of the solution maybe getting a higher velocity, more transactional blocking and tackling business that generates some of that ARR and that revenue as you guys go and penetrate your larger enterprise customers? Maybe Rick, you can speak to the potential to build a higher velocity sales motion, maybe it's mid-market or upper mid-market, just your thoughts on that.

I actually think, Sanjit, you're going to see in a cloud-native-AI-first world is you're going to see not a pivot, not a transition, but an evolution toward more departmental selling, in particular, the development audiences associated with cloud-native deployments. So I wouldn't walk away from the session thinking, wow, Dynatrace is going to go to SMB because our value proposition really wins most often in the larger enterprise. But it doesn't always have to win in centralized IT. I think it is just as pervasive, just as impactful in smaller groups within that larger enterprise, which then get aggregated. So I think that is some of the transactional volume that we can imagine evolving into the future.

Awesome. Let's talk a little bit about capital allocation. So you announced a new $1 billion share repurchase program. Can you maybe give us why re-up for $1 billion? What's the signal that you're looking to send to the market?

So I'll take that. So we were -- I think it was probably -- I think it was May of '24 that we put the $500 million authorization in place for the first -- in the first go. We tripled what we spent on our buyback in the third quarter because we actually thought it was a significant value dislocation for the company based on what we believe the prospect of the company were and what we were valued at. And so we exhausted it. We doubled the authorization. Again, going back to our philosophy. Our philosophy is, one, invest in the business. So that is the first use of capital.

But because we have $1 billion of cash, and we generate $500 million of free cash flow, we're in an advantageous position where we can both return capital through a buyback and opportunistically grow and look for opportunities from an M&A perspective. And so you can expect that we will be buyers at current prices, probably at an increasing level to even more so than what we did in Q3. So that's what we're going to do. I'd say from an M&A perspective, we are active shoppers, but disciplined buyers. And there are things that need to kind of fortify the platform and fortify what we think is an opportunity to kind of grow and broaden the observability use cases.

Maybe last question to wrap up. In terms of stock-based compensation, how you're managing that, what level of share dilution should investors expect? And in terms of getting is more GAAP profitable? How would you sort of rank those priorities?

Well, we got a unique company that is GAAP profitable. So we're not becoming GAAP profitable. We are GAAP profitable, which is unique in kind of the software space. But relative to stock-based compensation, we've always been a very appropriate user of stock-based compensation. This year will be around 15% or 16% of revenue. And my expectation is that we'll probably -- we'll drive some more scale from that going forward. And so while others are trying to catch up relative to the profitability, look at the profile of the company, the company has almost 30% operating margins. Because we're a cash taxpayer, where most tech companies are not, we generate, on an equivalent basis, call it, 32% free cash flows on a pretax basis.

So it's been a focus on the things that we're doing have all been about how do we accelerate growth in the business, accelerate growth in the business. You'll find that it's -- again, you will actually drive more leverage when you accelerate growth in the business. You'll actually get it at the same time. And so we're quite optimistic about the opportunities ahead for the company, where we're at, where we're positioned, both on the go-to-market side, where we're positioned on the product side and the platform side. And so I'd say this is an exciting time for Dynatrace because I think a lot of what we've put in place is actually kind of something that we're going to see this momentum continue into fiscal '27.

With that, we're out of time, Rick, Jim, thank you for giving us the update on Dynatrace. Best of luck going in Q4, and thank you for coming to the TMT conference.

Thanks, Sanjit. Thank you all.

Welcome to Dynatrace's Fiscal Third Quarter 2026 Earnings Call. [Operator Instructions] Please note, this conference is being recorded.

At this time, I'll turn the conference over to Noelle Faris, Vice President, Investor Relations. Thank you, Noelle, you may now begin.

Good morning, and thank you for joining Dynatrace's Third Quarter Fiscal 2026 Earnings Conference Call. Joining me today are Rick McConnell, Chief Executive Officer; and Jim Benson, Chief Financial Officer.

Before we get started, please note that today's comments include forward-looking statements such as statements regarding revenue, earnings guidance and economic conditions. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q and annual report on Form 10-K. The forward-looking statements contained in this call represent the company's views on February 9, 2026. We assume no obligation to update these statements as a result of new information, future events or circumstances.

Unless otherwise noted, the growth rates we discuss today are year-over-year and non-GAAP reflecting constant currency growth and per share amounts are on a diluted basis. We will also discuss other non-GAAP financial measures on today's call. To see reconciliations between non-GAAP and GAAP measures please refer to today's earnings press release and supplemental presentation, which are both posted in the Financial Results section of our IR website.

And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and good morning, everyone. Thank you for joining today's call. Dynatrace delivered very strong third quarter fiscal 2026 results, exceeding our guidance across every metric. Through this fiscal year, we've driven a stabilization of ARR growth at 16%, 3 quarters of consistent double-digit net new ARR growth, annualized log consumption that has now surpassed $100 million, a strong balance sheet and a healthy cash flow generation that have allowed us to double the size of our share repurchase program while still investing aggressively in innovation, and finally, an increased ARR guide of 125 basis points at the midpoint that puts us on track to achieve $2 billion in ARR by the end of fiscal '26.

Our sustained strength underscores the increasing criticality of observability to the software ecosystem, accelerated demand for our end-to-end observability platform and successful execution of our go-to-market strategy. Jim will share more details about our Q3 financial performance and guidance in a moment.

In the meantime, I'd like to start with some highlights from our annual customer conference perform illustrating the substantial evolution and differentiation of the Dynatrace platform in capturing the AI opportunity along with several customer and partner advancements.

Perform 2026, which took place just 2 weeks ago, was an invigorating event where we hosted roughly 2,000 people in person, including customers, prospects and partners plus thousands more virtually. If you weren't able to join us, I encourage you to watch the replay of our main stage presentations. Each year, Perform offers the opportunity to examine the larger forces shaping our industry. And this year, the shift is more profound than ever.

I shared 2 primary takeaways from my opening keynote. First, Observability is entering a new era, one in which it is foundational to resilient software and dependable AI environments. Second, Dynatrace is unique in its ability to combine trustworthy deterministic AI with agentic AI to deliver reliable autonomous outcomes. And this is why we see Dynatrace as the AI-powered observability platform for autonomous operations. Let's unpack this a bit.

To start, in 2023, the AI market was estimated to be less than $200 billion and it is now on a path to be nearly $5 trillion in the next 7 years. Meanwhile, cloud and AI native workloads are exploding. Hyperscaler growth continues to climb, now approaching $300 billion in annualized revenue from AWS, Azure and GCP alone growing in the high 20s. That level of growth at this kind of scale is simply unprecedented.

But this astonishing scale and growth are also accelerating the challenges our customers face every day. As we have often stated in the past, workloads and data are exploding along with a massive increase in their complexity. Tools are fragmented and it's often difficult to know whether AI results can be trusted. And without trustworthy insights, organizations understandably are hesitant to automate.

One ramification of all this has become abundantly clear, AI-powered observability has become essential in an AI first world. The question then becomes, how do organizations harness the value of observability to help deliver on the promise of AI? Dynatrace exists for this moment. We are already helping organizations realize increased value from AI. We have been driving to this point for many years, from initially enabling organizations to be reactive to issues to proactive through automated root cause analysis, to predictive by adding machine learning and anomaly detection allowing customers to anticipate and resolve issues before they become customer impacting.

This is our quest to help customers deliver software that works perfectly. Our third-generation platform is fully available and built for the complexity and incredible scale of modern cloud and AI native environments. Its advancements allow us to look ahead, predict issues and build resilience directly into the fabric of an organization.

So what makes Dynatrace unique? Our differentiation is integrated deeply into the platform's architecture. And it comes down to 3 things: Grail, Smartscape and AI. First is Grail, our massively parallel processing Data Lake house and the only analytics engine purpose built to process exabytes of observability and security data in real time while preserving full context. This isn't a general purpose data store retrofitted for observability. Grail was architected from the ground up for modern software, where a single transaction can reverse hundreds of services across multiple clouds.

In the agentic era, where every AI-driven transaction can be unique and unpredictable, real-time contextual processing is essential. Logs are a great example of why this architecture matters. When logs are unified with traces, metrics, events, sessions and other telemetry in the same platform, they don't just add volume. They add decisive context. Once customers experience the increased value and lower cost of having logs in context with other data types, they are eager to replace their legacy logs tooling. That's why we are delighted to have exceeded the $100 million logs consumption threshold with current growth of over 100% year-over-year.

Our second major differentiator is Smartscape, our real-time dependency wrap that continuously maps the entire technology stack. Smartscape builds a living topology model that understands not just what exists but how everything connects and impacts everything else. So the platform always has the current context of the environment itself.

And third is AI, and this is where the first 2 converge. Grail provides unified data at scale and Smartscape provides the topology in context. Together, they enable our causal and predictive AI, proven in the most demanding enterprise environment and continuously evolving to deliver optimal outcomes. This leads to our announcement at Perform of Dynatrace Intelligence, one of the biggest innovations in our history. Dynatrace Intelligence is the industry's first agentic operation system built for modern software ecosystems. By fusing our determinantic AI foundation with a agentic AI across an ecosystem of agents, Dynatrace Intelligence delivers AI-powered observability that organizations can trust.

With Dynatrace Intelligence at its core, our platform is purpose-built for the agentic era, enabling a future where AI-powered observability can help customers auto prevent auto remediate and auto optimize. Similar to Grail, Dynatrace Intelligence is embedded in the platform and is not sold as a separate SKU. It is available to every customer today. We expect to monetize it in 2 ways. First, through increased platform usage as customers adopt AI assistance across teams driving greater use of Grail. And second, through usage-based agentic execution where AI-driven actions are delivered through workflows and ecosystem integrations. The durability of infrastructure software comes from deeply engineered data planes and AI control planes that operate in highly dynamic production environments.

Dynatrace has developed broad domain expertise and is uniquely positioned with Grail, Smartscape and Dynatrace Intelligence that is built directly into the backbone of the platform. Each of these capabilities is complex in its own right, but magnified in the Dynatrace platform as they are designed to operate as one system, applying AI to deliver answers and automation in environments that constantly shift in composition and workflow. This foundation has been built over years of operating at scale in real-world production environments, making the Dynatrace platform, both highly differentiated and difficult to reproduce quickly or safely. We, therefore, strongly view broad-based AI expansion as a tailwind for Dynatrace.

AI-assisted development with our [indiscernible] code copilots or AI-driven software delivery, compresses release cycles and increases the rate of change across already complex enterprise stacks, that raises operational risk unless teams have an observability control plane with closed-loop feedback to protect reliability and user experience. And as AI-driven systems become more probabilistic, outputs vary and issues can be harder to reproduce. AI doesn't reduce the need for observability. Rather, it makes observability essential for trusted insights and automation so organizations can operate with confidence.

I'd like to turn next to our customers. At Perform, more than 70 customers shared how the Dynatrace platform has become an indispensable component of their software environments. Here are just a few of their incredible stories. One of the largest airlines shared how they're using Dynatrace to help them deliver 31% better reliability, 75% fewer incidents and a 10% reduction in mean time to resolution, leading the industry in on-time departures and arrivals for 2 years in a row.

Canadian communications giant, Telus, shared how they're using AI to move from firefighting to proactive reliability, reducing the average time to resolve issues from 40 minutes to 5 minutes. Vodafone shared how they're using AI to modernize operations at massive scale, migrating more than 2,500 users, 8,500 dashboards and 8 terabytes of daily log ingest from their legacy logging provider to Dynatrace in just 2 months.

And Nationwide share how Dynatrace has helped them reduce Priority One incidence by 74%. In addition, customers expressed very strong interest in our strategic collaboration with ServiceNow to advance autonomous IT operations and scale intelligent automation. At Perform, ServiceNow's EVP and GM of technology workflow products reinforced our Better Together vision, highlighting use cases of how customers can integrate with Dynatrace to get greater efficiencies in their teams, accelerate agentic initiatives and drive automation with confidence.

In an agentic world, engaging in and integrating with an ecosystem of partners, including our long-standing relationships with global system integrators and hyperscalers, will be mandatory. And we are investing to deepen and broaden those relationships. In Q3, we announced deeper technical engagements with all of the major hyperscalers. We're integrating with Amazon bedrock aging core embedding Dynatrace with Azure's SRE agent and serving as the launch partner for GCP Gemini command line interface extensions and Gemini enterprise.

Finally, as the velocity of software development continues to accelerate, we have advanced our strategy to extend left to developers with the acquisition of DevCycle last month, built on open feature, an open-source initiative originally created by Dynatrace. DevCycle is a feature management platform that helps developers, SREs and platform teams bring progressive delivery for AI native applications directly into the Dynatrace platform. This solution will enable customers to accelerate their ability to release features in a controlled manner and remediate issues faster.

To wrap up, we've seen impressive customer momentum over the last several quarters with dozens of 7-figure wins, rapid logs expansion and customers standardizing on our platform for end-to-end observability. And we have delivered extraordinary innovation with Dynatrace Intelligence and the evolution of the Dynatrace platform to deliver significant customer value. This momentum is a testament to our unique ability to provide precise and trustworthy answers that serve as the foundation for autonomous operations in delivering resilient software and reliable AI.

As I hope you can tell from my remarks, we are highly enthusiastic about our opportunity ahead.

Jim, over to you.

Thank you, Rick, and good morning, everyone. Q3 marked another quarter of strong execution as we once again surpassed the high end of guidance across all our key metrics, showcasing the growing demand for our leading AI-powered observability platform and the durability of our balanced business model. As Rick mentioned, we achieved 3 consecutive quarters of double-digit net new ARR growth, record new logo ARR, and we surpassed our goal of $100 million in annualized consumption for our log management solution. The combination of our ongoing go-to-market maturity and execution, the increasing necessity of observability in an agentic AI world, our leadership position in the market and our unified platform differentiation give us confidence that the momentum in the business will continue as we look ahead.

Our conviction in the business is further evident in the Board's authorization of a new $1 billion share repurchase program that is double the size of our inaugural program. I will share more information on that later in my remarks.

Now let's review the third quarter results in more detail. As the business has evolved with the introduction of DPS, we have continued to look for ways to provide investors with the best KPIs of our performance. Given what we have learned as DPS has matured, and with the changes in the on-demand consumption accounting treatment, going forward, we will focus on ARR and its underlying growth driver, net new ARR. This is the primary metric that drives our subscription revenue, and it's how we measure and track the business internally.

Turning now to ARR. We ended the quarter at $1.97 billion, representing 16% growth and demonstrating stabilization of ARR growth for 3 straight quarters. Q3 net new ARR was $75 million, adjusted for foreign exchange movements coming in well above our expectations. Net new ARR was up 11% from a year ago and represents the third consecutive quarter of double-digit growth. This strong performance was driven by both record new logo ARR and steady expansion ARR, including a number of 7-figure end-to-end observability deals.

In Q3, we added 164 new logos to the Dynatrace platform. The average ARR per new logo was over $160,000 on a trailing 12-month basis. We continue to target landing with high-quality new logos that have a greater propensity to expand. The average land size in Q3 was particularly robust at over $200,000 and helped drive new logo ARR over 21% off a robust Q3 of fiscal '25.

Our value proposition continues to resonate with enterprise customers that are outgrowing their existing DIY or commercial tooling solutions. They are seeking business value from tool consolidation and coming to Dynatrace for the depth breadth and automation of our unified AI-powered observability platform. Once customers experience the benefits of the Dynatrace platform, they are often quick to expand their usage.

Average ARR per customer continues to grow and is now nearly $500,000, highlighting the continued adoption of the platform and value we provide to customers. As we have said in the past, given the significant cross-sell and upsell opportunities in our enterprise customer base, we believe the average ARR per customer opportunity could be $1 million or more over the medium to long term.

Gross retention rate in Q3 remained in the mid-90s, demonstrating the strategic relevance for the Dynatrace platform as mission-critical to our customers' operations. Net retention rate or NRR on a trailing 12-month basis was 111% in the third quarter, consistent with the prior 2 quarters. As Rick mentioned, we continue to see broader usage and deeper penetration of capabilities across the platform, notably in log management, which remains our fastest-growing product category and surpassing the $100 million annualized consumption milestone we set for ourselves. With our log strike team in place now for 9 months and our selling motion continuing to mature, we expect logs to be an ongoing source of significant ARR growth.

Moving on to revenue. Total revenue for Q3 was $515 million, and subscription revenue was $493 million, both up 16% and exceeding the high end of guidance by 150 basis points driven by strong net new ARR.

Turning to profitability. Non-GAAP operating margin was 30%, exceeding the top end of guidance by nearly 100 basis points, driven mostly by revenue upside flowing through to the bottom line. Non-GAAP net income was $135 million or $0.44 per diluted share $0.02 above the high end of our guidance.

We generated $27 million of free cash flow in the third quarter. Due to seasonality and variability in billings quarter-to-quarter, we believe it is best to view free cash flow over a trailing 12-month period. On a trailing 12-month basis, free cash flow was $463 million or 24% of revenue. As a reminder, this includes over 600 basis point impact related to cash taxes. Pretax free cash flow on a trailing 12-month basis was 30% of revenue.

Finally, as of today, we have substantially completed the $500 million share repurchase program announced in May 2024. In Q3, we increased the pace of our repurchases, buying back 3.5 million shares for $160 million at an average price of just over $45 per share. We believe the strength of our balance sheet and cash flow generation afford us the ability to continue to strategically invest in R&D innovation for our customers while also returning capital to shareholders.

We announced today our Board has authorized a new $1 billion share repurchase program. This program is the largest in our company's history and doubled the size of our previous program and underscores our confidence in the business, our conviction in the long-term growth opportunities and view that our shares are undervalued. We intend to be active buyers in the market at current levels.

Moving now to guidance. The demand environment for observability remains robust, and the growth drivers fueling the business continue to trend positively. The landscape is benefiting from secular tailwinds of end and observability, cloud modernization and AI workload proliferation. Our go-to-market strategy continues to build momentum and consistency as evidenced by 3 consecutive quarters of consistent double-digit net new ARR growth.

Our DPS licensing model continues to enable broader adoption and increased usage of the platform. Logs continues to be a significant source of growth for both our installed base and new logos. The combination of these strong underlying growth trends give us conviction in the ongoing momentum of the business. As a result, we are raising full year guidance across the board.

Starting with ARR, we are raising ARR growth guidance 125 basis points to a range of 15.5% to 16%. And expect to surpass our next milestone of delivering over $2 billion in ARR. The high end of this ARR range implies another quarter of double-digit net new ARR growth.

Moving to revenue. We are raising total revenue and subscription revenue growth guidance by 75 basis points at the midpoint to 16% growth. Turning to the bottom line, we are raising full year non-GAAP operating income guidance by $9 million and free cash flow by $13 million. This translates to a non-GAAP operating margin of 29% and free cash flow margin of 26%. Finally, we are raising non-GAAP EPS guidance to a range of $1.67 to $1.69 per diluted share, representing an increase of $0.05 at the midpoint of the range. This non-GAAP EPS is based on an expected diluted share count of 304 million shares.

In summary, we are very pleased with our Q3 and continued momentum through fiscal 2026. We are focused on executing to close the year out strong.

And with that, we will open the line for questions. Operator?

[Operator Instructions] And our first question is from the line of Raimo Lenschow with Barclays.

My question was if you think about what you see in the client base in terms of understanding how your automation stories coming together, how it's important to kind of bring all the decent data sources together in one place, what does it mean in terms of engagement levels decline, et cetera? Is that -- are we seeing an ongoing kind of bigger kind of the [indiscernible] -- or bigger momentum they are building? What do you see in the pipeline in terms of deal size, et cetera? Just kind of seeing how that momentum is ongoing.

Raimo, thanks very much for the question. I guess where I'd start is end-to-end observability is what we're seeing as being very, very strong in terms of the sales play and momentum at the moment, this is where our customers are looking to expand. They are realizing that there is extraordinary tools for all that there is lack of expense management in that and poor outcomes. And so this is, I'd say, the #1 area where we're seeing momentum in the business is precisely that. And as you look to an AI-first world that's coming it becomes even more pervasive that end-to-end observability is a mandatory foundation to be driving those kinds of outcomes.

Our next question comes from the line of Sanjit Singh with Morgan Stanley.

Congrats on the stabilization in AR growth for the last several quarters. I wanted to ask a follow-up on Raimo's question. In a world where agents are doing a lot of the investigating and the triaging on incidents versus human site reliability engineers, there's sort of 2 questions there. What's the pace of that change? Like how realistic are we going to see that sort of environment in the next a couple of years? And then two, from a product perspective, how does that change observability? And how does that change how customers will use Dynatrace?

Sanjay, so in terms of pace of change, I think that there is still a lot of apprehension about just how much conviction organizations have in driving AI and AI outcomes. So I think it's going to evolve over a period of time. Having said that, I do think that there is a significant change in observability as we look to the future and that it really becomes, in our view, the control plan for enterprise. And what I mean by that is simply that observability becomes foundational through this agentic action without deterministic AI without assuredness of understanding what the baseline problem is. And of course, we use the notion of answers, not guesses here, you simply can't take agentic.

So the steps that we see that organizations have to go through are: number one, you have to get the end-to-end observability because that's where you get the broadest, most concrete outcomes and answers. Number two, you then use that deterministic AI to develop an understanding of what actions need to be taken. And then number 3 and only then and agentic AI take over [indiscernible] probably only with a portion of the actions required for auto production, auto remediation and auto optimization. So it is going to be a journey, but that journey is beginning today and that journey begins with end-to-end observability followed by the leverage of deterministic AI as a mission-critical foundation for agentic ai to follow.

Our next question comes from the line of Gray Powell with BTIG.

Okay. Great. So yes, it's really good to see log monitoring consumption past the $100 million mark this quarter. I guess a couple of questions there. Like how quickly has that materialized over the last year? I know that there was sort of a new iteration that you came out with in late '24? And then what are your -- what are the next milestones for the product?

Thanks for the question, Gray. Again, we're very pleased. We told you last quarter that we were on the precipice of hitting this milestone, we exceeded it. Our logs business is continuing to grow north of 100%. So by far, the fastest-growing product category in the business that -- you're right that we've seen a significant step function increase in the acceleration of the business from last fall to now, last fall was when we were able to get the log product use case complete. We had the product packaging and pricing right, that evolved a little bit in the following quarter. So you saw a step function increase and it continues to exceed our expectations.

Relative to the next milestone, we haven't necessarily set our next milestone publicly. I can tell you that it will be a significant source of new ARR. We're seeing this already. Rick mentioned these end to end observability deals. Nearly all of them have logs embedded with them. So we expect this to be a huge source of ARR growth for the business going forward.

Our next question is from the line of Will Power with Baird.

Yes, I guess I'd echo the congratulations on the results. Great to see the ARR growth, stabilizing the strength in net new ARR. As we think about the net new ARR trends, the consumption commentary you just provided, the logs opportunity, the AI opportunity. Maybe help us think about kind of the puts and takes that could contribute to ARR perhaps accelerating as we move into fiscal '27? How do we think about the outlook there?

I'll take that, Will. Good question. Again, we're focused on continuing the momentum. As I said in my prepared remarks, third consecutive quarter of net new ARR, double-digit net new ARR growth, stabilizing ARR at 16%. If you look at the high end of our guide, I'd suggests that continues into Q4. So it will be 4 quarters of stabilizing growth for ARR and 4 quarters of double-digit ARR growth. We've said that our objective is to show an acceleration in ARR. Obviously, we'll have to continue to execute like we have. The go-to-market momentum continues. We continue to benefit from large-scale end-to-end observability deals. So the changes we made are manifesting themselves in the results. We're seeing traction with partners. I'm not going to provide guidance on this call. I can tell you we're very optimistic about the momentum in the business. We'll have to see come May what the guide is, but our objective is to build an acceleration in the top line growth.

The next question is from the line of Koji Ikeda with Bank of America.

Jim, in your prepared remarks, you mentioned net new ARR and ARR the core foundations and the building blocks of growth. But last quarter, you did give a new metric, the annualized platform consumption dollar growth rate of 20% plus. I wonder if you could share how that metric compared this quarter compared to fiscal second quarter? Is it directionally higher? Is it the same? Or is it lower than the 20% plus that you gave last quarter?

It's a good question. We've shared a lot of KPIs, and we've tried to share KPIs as investors try to understand our journey with DPS, which would certainly get them on the platform allow them to access the platform all offerings, and that's playing out nicely. So relative to consumption, consumption continues to grow north of 20%. So consumption is growing very healthy, consistently higher than ARR growth.

The next question is from the line of Ryan Mac with Wells Fargo.

[indiscernible] on for Ryan Mac. This year, you've talked about some of the strength in large deals and large deal pipeline. Is there any update you could provide on how those large deals are progressing and maybe whether your incremental confidence on those deals coming through has changed in the past couple of months? I have a follow-up if there's time.

Sure. I'll take that. I think what I talked about in Q2 was we continue to see a robust pipeline. That pipeline is very weighted to large deals, deals over $0.5 million, deals over $1 million. And that makes sense relative to the go-to-market changes we made last year that we were focused on these accounts that had a large -- or a high propensity to spend. I think what you're seeing, you started in the Q3 results that we built consistency in close rates of these large deals. Our expectation in Q4 is you'll see that again.

So I think what we've done is we build consistency in our execution. You're seeing that through the first 3 quarters. The expectation in the fourth quarter at the high end of our guidance, you'll see that again. And it's heavily driven by this continued trend of very large enterprises looking to vendors to consolidate on. And Dynatrace is in a very good position. You saw even new logos, new logos, 5 of our new logos were over $1 million. So this is both existing customers and new logos, looking to Dynatrace to be their provider of choice as this trend continues.

I would just add to that also, that we see AI as an enormous tailwind to the observability business overall. You have to have the observability in order to drive an AI first world. We believe that fundamentally. And the result of that is that you have to have end to end observability to get the best outcomes, the best underlying analytics and insights to be able to take agentic action. So as the world shifts toward a move of autonomous operations, observability becomes foundational and end-to-end observability is fundamental to maximizing the success of that type of [indiscernible].

Our next question comes from the line of Eric Heath with KeyBanc.

I guess, what stood out to me that was most impressive was the fiscal 4Q net new ARR guidance, there's a strong lift from what you're expecting previously. So just maybe an extension of the prior question there but...

Eric, could you just speak up a little bit?

Yes, any better?

That's a little bit better. Thank you.

Okay. Yes. So just to touch that question. So the fiscal 4Q net new ARR guide was a strong lift from what you were expecting previously. Just an extension from the prior question, your response there. Just any more detail you could share on what has given you the confidence in the outlook, maybe some assumptions on the close rates in those large NN deals?

Yes. I mean one of the things I talked about in the last call is the -- we had very healthy close rates in the first half of the year. We saw a healthy close rates in Q3. I'd say our visibility of the pipeline here, especially near term, is quite strong. That doesn't mean we expect we're going to get every deal. But we do believe that we have a very good line of sight to be able to deliver against this guide, the range that we're providing. So I think some of it is the visibility and I think it's also what I think is a continued improvement in our go-to-market maturity around having an ability to call the ball on some of these large deals, I think our ability to do that continues to improve.

The next question is from the line of Keith Bachman with BMO Capital Markets.

I wanted to ask about new logo growth. Jim, you had called out that I think you had 164 new logos, solid growth there. And yet if I look at the numbers, it appears you're still getting about 70% of your ARRs coming from existing clients, 30s -- 30% is coming from new logos. And I'm just wondering, is that the way we should be thinking about as we look out over the next year, I think investors have some worry that the existing customer base may not sustain growth for a period of time. And so trying to understand how you might be able to expand your new logo growth and particularly maybe going -- not the small business, but maybe expanding the TAM a little bit.

As you talked about, AI is foundational. So maybe that presents some opportunities for a broader customer audience. At the same time, there are solutions out there that are less expensive that require more work. And I'm not sure how DPS would fit into, is that a facilitator of new logos? Or is it a hindrance in that you got to make a little bit larger commitment? But just maybe talk about how we should be thinking about new logo growth over the next couple of years.

So I'd say near term, Keith, but -- one, I would say we're very pleased with the new logo momentum that we're having, in particular, that there is a lot of momentum with just customers that are looking to Dynatrace to consolidate fragmented tools on. So we continue to make good traction there. You should expect in the near term kind of over the next year, that it will be a, call it, roughly 1/3 new logo, 2/3 expansions. I would clarify, we are not even close to exhausting our ability to expand within our installed base.

We continue to grow. We almost have $0.5 million now per customer. So -- and we have many, many million-dollar customers. So the propensity to expand is still pretty material. But near term, I think we're going to be roughly 1/3, 2/3. We do look at that, Keith, relative to what are the different velocity motions you can do to maybe land a little bit lower, I think, in this cloud AI native world, that's probably an area we continue to get some traction in. But near term, you should expect kind of the mix that I just mentioned.

Keith, I would just add that with sensibly the completion of the third-generation platform that is now out there, it does enable us to do a much better job of tuning and targeting to different personas, SRE, platform engineering, particular developers at our Perform conference a couple of weeks ago, we had a full developer day with a ton of developers working on the product and the solution overall. We just did the dev cycle transaction, which enables us to extend a further with regard to feature management.

So you can expect us to be leaning into development teams and developers as an added persona with a primary intent of generating over the course of time, new logo momentum in unit volume not just in ACV, which is what Jim was referring to by way of a record quarter in Q3.

The next question comes from the line of Matt Hedberg with RBC Capital Markets.

Congrats on the consistency, really good to see. I guess for either of you, I wanted to ask about the competitive environment. I guess, both from smaller vendors like [indiscernible] getting acquired. But I know investors are also worried that large language model providers at some point might do everything in software. I mean just given that concern, how do you think about the competitive risk from some of these frontier model providers as well?

Matt, a lot in that question. Let me start with the first part, which is some of the acquisitions in the industry. And I would just say, as we look at [indiscernible] and observe others, we really don't see them in the market very often on a direct competitive basis for us, simply because of our target segment typically being in the global 15,000, the largest accounts on the planet and what they're looking for is end-to-end observability and many of these solutions that you mentioned really have point solutions either focused on logs or focused on metrics, but really not an end-to-end solution that's at all comprehensive to be able to compete against Dynatrace at that level.

So we always are paranoid about competition. We're looking at moving chess pieces, especially as larger players get into the market. And so we're very observant of that, but at the same time, the smaller players haven't really been competitive in the past. With respect to this dialogue around LLMs replicating, observability, that's a longer answer and something that we've been spending a lot of time thinking about to try to give you a succinct response to it, I would say, number one, we view there to be a very sizable difference between enterprise software with standard workflows and infrastructure software like ours with highly dynamic workflows, requiring variable evaluation of billions of interconnected data points.

Secondly, as I mentioned earlier, we really do see observability as the control plane for enterprise. We don't believe that you can easily replace observability through vibe coding or an LLM instantiation that can do the same thing that we do.

Third, we really see our focus and our moat really is being architectural and not code based. We have a platform with Smartscape, with Grail, with Dynatrace Intelligence, not just individual point products and the interaction of those becomes quite sophisticated. We have AI increasing complexity across LLM and agentic systems, not reducing it.

And then finally, we've built an extraordinary amount of domain expertise over more than a decade of valuation of AI workflows or workflows based upon the AI analytics that we complete. And we do believe that grounding AI actions in a deterministic and explainable system is much more powerful than using and relying only on probabilistic models. So there's a lot to be had in there in terms of additional conversation. But the net of that is we see Dynatrace has a very, very durable solution over the course of the long term for the overall environment we see for managing enterprise AI [indiscernible].

The next question comes from the line of Patrick Colville with Scotiabank.

And I thought your answer just then -- it was really fascinating. I guess I just want to pivot back to the question earlier on the 4Q guide. I mean I'm calculating the updated guide implies 22% net new ARR growth in constant currency in 4Q. Which -- if I'm calculating that correctly. I mean, that would be the biggest net new ARR guide for a long, long time. So just -- can you just circle back, what gives you confidence there? Because I know that's the #1 question we're going to be receiving like why does Dynatrace have confidence in that number?

Well, I'll start with why we have confidence in the number, and then I'll clarify what the guide is as far as the growth rate. We have confidence in the number because our pipeline is in incredibly robust. We continue to have significant demand for observability. And so the change we made in the go-to-market side are playing out. So we have -- this is just we have good visibility. So our visibility is what drives our conviction, that's one.

I'd say relative to the guide, and this probably just puts and takes relative to FX. At the high end of the guide, it would imply another quarter of double-digit growth. It's not 20, it's like in the kind of 10% or 11% in the fourth quarter relative to the guide. But still quite robust. Again, 4 quarters of double-digit net new ARR growth which is continued in building momentum in the business.

Our next question is from the line of Ittai Kidron with Oppenheimer.

A couple of small ones. First of all, if you could give us an update on how your security strike teams are doing, if there's any progress there? And then, Rick, I want to go back to your answer about LLMs and what they can do to observability. The opportunity is very clear. Again, just on the cost side, you just announced Dynatrace Intelligence, which sounds fascinating. I guess logically speaking, it would seem that customers would find this as the way to interact with your system longer term.

I guess the question is, again, could agent -- third-party agents just intermediate you and actually replace Dynatrace Intelligence and third-party agents can do that? And somehow, again, you get step removed from the customer system working in the background and customers only engaging with third-party agents to interact with your system. Wouldn't that this intermediate the value that you bring to your customers?

Thanks, Ittai. On security, it continues to be an important business for us. It's growing nicely. We said that it would take us longer to get to the $100 million level than logs a few quarters back, but we see ongoing progress there. We do see the ongoing convergence of security and observability, so no change there. And our security strategy remains to be focused on observability buyer as opposed to the CISO where we have relationships today. So that continues to be our strategy, our focus and our evolution of security and the security strike team.

On the overall LLM environment, I think I covered it relatively completely. I would only -- I guess I would only add that no, we don't see it as highly likely that an LLM is going to be able to replicate Dynatrace for all the reasons I described. In particular, we see that in a highly variable environment that is playing out on a day-to-day basis with all of these interconnections within that environment in large enterprises that it would be very, very difficult for any AI piece of solution or a piece of software to then replicate that environment for all the reasons I described.

The next question is from the line of Mike Cikos with Needham.

It was great to get some of the data points around average land and new logo growth, et cetera. But maybe for Jim, I want to ask about DBNR with the stabilization we've been able to demonstrate here at the 111. Can you help us think through where we are in driving an improvement in this metric, just given the go-to-market maturity that you are talking to in these observability deals as well as where are we in that DPS renewal cycle? That would be terrific.

Thanks, Mike. So again, we're pleased to see a continued stabilization in dollar-based net retention rate at $1.11. I think I mentioned this in the past that our sales organization is focused on maximizing bookings. So you're going to have some quarters where you're more new logo heavy, you're going to have some quarters where you're more expansion heavy. But I would say, Mike, we are still in the building phase. You mentioned EPS that in fiscal '27 will be kind of your first full 3-year cohort classes coming, so that you'll have a 1-year, 2-year, 3-year cohort classes. So there is a building momentum going into fiscal that to the extent we can continue to execute, you should see an inflection in that metric.

The next question is from the line of Brad Reback with Stifel.

Rick, in an increasingly agentic world, do you feel you'll need to evolve your pricing kind of paradigm in order to properly monetize?

It's a good question, Brad. The way that we articulated in my prepared remarks and the way that we see it evolving is that we monetize the agentic world in 2 ways. Number one, through increased workloads and increased overall usage of the platform through Grail, through Smartscape and in delivery of the analytics that we provide on all day everyday basis. Secondly is we do expect to monetize directly agentic workloads. So with a combination of those 2 elements, we do believe that there is direct monetization of the agentic AI element.

And if you look at Dynatrace Intelligence, overall, it really does have both components that number one, it has the component deterministic AI to evaluate what's happening in your environment with certainty and through causation and context. We then take those answers and then deliver those into an AI environment that is agentic in nature where either a Dynatrace agent or a third-party agent through an ecosystem that is essentially orchestrated by Dynatrace can take action. And it is through that agenetic workflow that we can provide additional monetization.

Our next question is from the line of Miller Jump with Truist Securities.

I know we aren't guiding to '27 right now, but I was just hoping to understand how you're thinking about hiring as we zoom out? Specifically curious if there's AI efficiencies that you're potentially getting on head count or if some of the initiatives you've talked about are causing you to lean in further on hiring maybe in the year ahead?

Yes. We're not going to guide here for fiscal '27. But I can tell you that your point about leveraging or internal productivity is something we continue to leverage within Dynatrace. And so in that regard, that will continue. That will certainly be a source of kind of moderating hiring in certain areas, whether they be customer support, G&A, driving more sales productivity. I don't think it's necessarily going to be a driver of us not hiring in the R&D space, even though we're leveraging heavily AI within that realm as well to make our developers more productive. So we'll continue to hire in R&D notably. And then I'd say hiring thereafter is going to be kind of more moderated.

The next question is from the line of Andrew Sherman with TD Cowen.

Jim, great to hear of the 20%-plus consumption growth continued. How should we think about the gap of that between ARR and revenue growth? What drives the convergence of those 2 over? And what time frame would that look like?

Yes, it's a good question. We've gotten that -- that was one of the reasons why in our prepared remarks, I didn't comment on consumption growth. It's very healthy. DPS is playing out the way we expected. I would say there is going to be -- there's certainly a lag between consumption growing at those rates and seeing it manifest itself in an expansion. Sometimes you're seeing early expansion, sometimes you do not. So I'd say that there's no simple answer to that. I'd say there is an elongated time period between consumption growth and then seeing ARR acceleration that comes thereafter.

But again, the whole premise of getting customers onto the platform for DPS is get them to consume more. Consuming more means they are getting more value. More value means likely an early expansion because they're trialing something that maybe they weren't using before. And so even when consumption growth is healthy, there are other reasons why customers expand. They expand because they're entirely new use cases that they're looking at. And so again, look at our performance around driving double-digit net new ARR growth, our expectation is we want to continue to do that going into fiscal '27.

Our final question will be from the line of Brent Thill with Jefferies.

Just on the go-to-market side, if you can maybe talk through the plans on the sales hiring front rep capacity, how you're seeing, obviously, you're getting great production, good to see the good results. But maybe if you could just walk through what you're seeing there and what you're expecting to do in terms of the overall distribution adds over the next year?

I'll take that. We continue to drive improvements in sales rep productivity. So we will continue to hire reps. It's important to remind investors that, it's not just reps that drive this productivity. We've continued to get significant traction with leveraging our partner channels, notably GSIs and the hyperscalers continue to be a source. So continued improvement in productivity per rep. So hiring will continue. We'll have more to say about what we're going to do in that space in the Q4 call, but that's what you should expect as you think about fiscal '27.

Thanks very much to you all. That brings us to the end of our call. We very much appreciate your gauge questions, your ongoing support. To close, we believe that observability is becoming increasingly critical to the overall software ecosystem in delivering reliable software and AI. We have very strong conviction as we entered Q4 with momentum headed into FY '27. And we are enthusiastic about what we see ahead from a customer standpoint and from the number of personas engaged in and requiring observability solutions to deliver the outcomes they seek. We very much look forward to connecting with you at our events over the coming months, and we wish you all a very good day. Thank you.

Ladies and gentlemen, this concludes today's conference. You may disconnect your lines at this time. We thank you for your participation.

Time is running. Okay. Welcome to our next session. Really happy. I didn't realize, Rick, that you were just based here, so that's even better.

Yes, based in the Bay Area. So this is very approximate.

So it's a question I'm asking everyone at the moment. And it's, how does it feel out there in terms of end demand? Because I guess the -- is it stock market? And we can debate that all day long. But like difficult to find answers at the moment, but how is the real world?

From my perspective, not a huge amount of change in macro, obviously, incredible amounts of deployment of capital being spent on data centers. We're all very aware of that. I haven't really noticed or observe much change in the overall spend environment for enterprise-oriented software at the moment.

And the -- if you think about it, like the bigger question -- so the big thing going on for you guys is that you're talking more about strategic deals that the customer conversations are changing, et cetera. Talk a little bit about what's driving that from a customer perspective? Maybe start with where the industry is as a whole and then how you can help the customers on that?

Sure. Well, the evolution of the selling environment for us has evolved immeasurably even in my 4 years of tenure at Dynatrace. When I began, it was very silent. You had the APM vendors and then you have the infrastructure monitoring vendors and you have log management vendors and application security vendors.

And over the last 4 years, really, that has consolidated in a material way. And the real question is, well, why? Why is it? Why is it consolidated? And my simple answer to that is outcomes are better that in a highly complex environment, especially with our target customer set in the Global 15,000, really even the Global 2,000 or 3,000 at the high end of the pyramid. Huge amount of complexity, hundreds of applications, huge amounts of infrastructure, which are growing immeasurably, even more so in an AI world.

You have a log management coming into the fray now, which is getting integrated into the overall observability framework. And the result of it is you can't manage it manually. You can't do what you used to do. When I was at an oil and gas company and the principal walked me into the network operations center, and there were hundreds of people staring at hundreds of screens, trying to do manual processing of alerts.

That doesn't work anymore. You have to automate that. It has to be oriented around an AI world, and it's got to get integrated into an overall view of your software environment to deliver the best answers and the best outcomes. And that's why it's consolidating. And that end-to-end observability trend uniquely -- maybe not completely uniquely, but it certainly benefits Dynatrace.

And do you -- on that note, though, because like we've been talking about full stack observability for a few years now. And I was like, yes, I want to do that. I remember like I wrote my first big note on observability like 5 years ago and it was like that's what everyone is doing.

It was brilliant.

Yes. Yes. Thank you. Yes. But it is only now coming kind of together. Is that kind of driven by product maturity? Or like back then it was all marketing. We knew you need to get there, but the products weren't there? Like how do we have to think about that?

It really is an evolution, I think, of capabilities. It is the product capabilities. Like, for example, at Dynatrace we have, over the last 5 years, evolved our platform to our third-generation platform. This resulted in a couple of years ago, the delivery of Grail.

Yes.

Grail for us is an underlying foundational massively parallel processing, data lakehouse. It stores logs, traces metrics, behavioral analytics, business events, user data, that sort of thing. That data lakehouse is overseen by a fully integrated, completely AI-oriented or AI-powered platform, which is Davis, which does causal AI, predictive AI, Generative AI, headed to agentic AI. We can talk about that if we wish in a bit.

And that has resulted in delivering answers that are trustworthy, incredible to then enable automated action. And it is the stack of the data plane, the AI plane for answers and outcomes that are able to deliver automated action that's really come together over these last years. That sort of capability didn't exist for Dynatrace or really anybody else 4 or 5 years ago.

Yes. Okay. Perfect. And then so you have -- if you go to your customer, you have it, but now like, look, take Box as an example as well. But like everyone, we're still on-premise, we're still messy. How do I kind of go from that messy world to your kind of new fancy world?

This is one of the advantages, not overselling it. This is one of the advantages of Dynatrace in that our capabilities exist on-prem, in the cloud, they exist in multiple cloud environments, AWS, Azure, GCP, et cetera. So you can manage your migration from on-prem workloads to cloud workloads to AI native workloads seamlessly with Dynatrace and you can oversee all of them using our Observability framework at your discretion and at your rate of expansion or migration.

And so by enabling that, we really do facilitate a mix, a hybrid environment that continues to evolve. And in the largest of enterprises, that really matters because the largest banks on the planet, the largest commerce companies and the largest pharmaceutical companies, they're going to have a mix of environments forever or at least for a very, very long time to come.

Yes, yes. So then -- so if I'm like a big enterprise on-premise cloud, so I can start consolidating at home towards Dynatrace, as I move to the cloud, I can use Grail or can I use Grail on-premise as well? Or is that more cloud core? And so as I move to the cloud, I just do more, more Grail...

Well, one important part of -- one important distinction, Raimo, is that -- even if you have an on-prem workload, you can observe that in the cloud. And that enables Grail.

Yes, yes.

So yes, the observability needs to be happening in the cloud, but that can apply to all sorts of different workloads.

Okay. Perfect. Okay, makes sense. And you mentioned log as a thing that came up a lot. That was probably the last leg to bring all the stuff together?

Yes.

You start talking more about logs like, where are you on that journey? And I'm asking because it does look like there used to be a log company that was very big that might -- where a lot of feeds might come up for renewal, like what are you seeing there?

Well, logs has been the fastest-growing business that we've seen. We really got to the point of enabling logs. I'd say that we're ready for prime time at enormous scale beginning in about October of last year, so October of '24. At that point, logs was a very small sort of single-digit millions of dollar business for us. That has grown to the point where in our earnings release for our second quarter earnings that we just completed a month or so ago.

We talked about that number being almost $100 million in consumption. So it is -- logs is essentially a business that has grown from 0 to near $100 million in 1 year, and it's growing at well more than 100% per year. Well, 100% growth on a $20 million number is a lot smaller than 100% growth on a $100 million business. And so that really is fueling a good amount of growth. And I would say it is driven by 2 factors.

One is priced relative to incumbents in the market. But it's not quite the way that you would think about it and without overly belaboring it, I would simply say that it isn't that we're just coming in and saying, well, we're a lot cheaper. It is that if you incorporate logs traces metrics, other analytics user data, you actually don't need to store as many logs in order to get better outcomes, better answers.

Yes, yes.

So the results of it is that for enterprise customers, you can actually get more efficient in your overall cost without us coming in as Dynatrace and just say, well, we're going to give you a 30% discount over what you're doing today. Just continue it the same way. So the 2 drivers of logs business for us are: number one, overall cost of managing a logs environment, as I just discussed.

And then the second is delivering better outcomes. And that better outcomes piece is, I would say, much more relevant especially as you head into an agentic world for autonomous operations because this is where you want all data types to be delivering the answers that you need to be able to take that action. So you can think about it, end-to-end observability really consists of 3 different layers, integrated data layer, integrated domain layer. This is application performance monitoring, infrastructure monitoring, log management, et cetera. And then the third layer is the persona layer.

You want developers, IT ops, SRE, platform engineering, even executives all to be able to access that same data. That is what end-to-end observability is. That is what enables the best outcomes, and that is ultimately what will enable automation of that environment.

Can I -- because I'm the financial guy, so I look at numbers. The..

I don't believe that. I think you got way more -- way more to offer...

If I just look at numbers, the big log guy, who is like massively bigger than all of you guys. In this new world, and I'm doing less logs like, is that same size up for grab? Is it going to be a bigger market? Is it going to be a slightly smaller market? How do you think about that?

Gosh, Raimo, I look at this as -- I look at this as sort of like the mainframe market that was always going to disappear.

That never did. It was supplemented with client server and then it was supplemented with cloud and then it was -- and I think this is the same. We can get more efficient with logs. But gosh, as AI workloads grow almost in an unbounded way, what's going to happen. The overall workflows to be observed is going to increase immeasurably.

So okay, yes, yes. Okay. That answers it. And then the -- since we talked about players in the market, we just saw -- obviously, it's an interesting market. And if something is interesting, and other people want to share of that. We just saw like Palo Alto to like a kind of step into the -- with Chronosphere into your market. How do you think about kind of how this will play out? Because like to some point, they look at the same data set for some of it. On the other hand, not fully, I think your data volume is much bigger. Like how do you think about how that's kind of going to play out?

I would say several comments on this. First, it provides absolute validation of the observability market being ready for prime time. Again, 4 years ago, when I began at Dynatrace, it was -- you go talk to customers, and it was difficult for me to get a meeting with the CIO. It's sort of observability. How do you spell that?

That is no longer the case. I assure you. I -- in the last 30 days, I have done dozens of meetings with CIOs, CTOs and others. Observability is ready for prime time.

It is broadly understood that you cannot do it manually. You cannot engage in the same way that you used to be engaged. So that was one element. The other element is just the evolution of AI is exploding these workloads and requiring more and more observability as we go. And so as we look at these components, I think all of these are factors and how the market is evolving.

And it's evolving very, very rapidly. And relative to the power deal specifically, I think it also validates the emerging of application security with observability. We've been talking about this for some time. I think it is indelible that we see that convergence. And we've looked at that as well.

The one thing I would say is that I do think it's not without its challenges and the reason for Palo, and the reason is because the buyer profile is a little bit different. The selling to the CISO where the CISO organization is very different than selling to the CIO organization, I believe that the buyer for observability is different than the traditional buyer for Palo. So cross-sell is not something that is easy to get done there.

Yes. Okay. Perfect. Hey guys, could you in the back of the room? All right. Could you just kind of quieten it. Thank you.

The next thing is like you mentioned GenAI already a little bit. Can you just -- like you guys have been doing AI like for a while and with more kind of anomaly detection, et cetera? Like how is GenAI kind of play into this [large ML]?

Yes. Let me -- let me answer it this way. What I would say is that we sort of view the observability market having evolved through several phases in a way back when a decade or more ago it was really reactive. It was, wow, something broke, what happened and then you start doing research. It moved from there to maybe what I would call Phase 2, which was proactive, which was automated root cause analysis. Something went wrong, you had immediate root cause, you took a look at it, you knew what was going to happen and then you resolved it as quickly as you could.

The third, which is sort of where we are now is predictive operations, which was anticipating issues but still resolving them manually. So you were using causal AI, predictive AI, predictive AI was adding machine learning, anomaly detection, those sorts of elements to anticipate problems so that you could get them resolved before end users would see them.

Where we are going next is to a world of autonomous operations. And this is where it really gets exciting, which you take predictive operations to the next level, and that is to not just see it anticipated, cut it off before end users see the impact do so manually. But rather through an agentic world, an agentic ecosystem, you could actually handle those sorts of elements on an automated way through MCP servers, auctioning out through various different other agents, it could be a ServiceNow agent, it could be an Atlassian agent, it could be a GitHub agent, a hyperscaler agent.

And then resolving issues really in real time before they become an issue. And what's amazing is of the companies I've talked to recently, they get the fact that, you don't need autonomous operations on 100% of predictable incidents in order to matter. If you get to the ability where you can autonomously, react to respond to and resolve 20%, 30% of the potential incidents before the largest organizations on the planet. That can save them tens of millions of dollars in annual cost savings. Not to mention the user experience benefit that they get by not having the challenges that they might otherwise see.

So that's one aspect. The other aspect I wanted to speak to is like, in theory, with GenAI, like the whole idea is like there's going to be a lot more software, there's more applications, et cetera, which basically means there's more observability that is needed. Is that a fair statement?

Absolutely. I think that's exactly right. You're going to -- to the extent that you can write code so much faster, deliver so much more in the way of applications, you end up requiring or mandating a lot more infrastructure. The result of all of that is an explosion of workloads.

The more workloads you have, the more you need to then be able to observe those. And by the way, there is an added element. You take a look at what we would refer to as AI observability. And AI observability is what we refer to as observing AI workloads. You have to do all of what you do today with regard to all of the other workloads.

You have to observe applications, you have to observe infrastructure, you have to do log management, you have to do all of what you do today. But you also have an added mandate, an added ask from customers. And that is, by the way, could you please make sure that the content that is delivered is accurate.

And this is where you get into hallucinations, you get into guardrails, get into these sorts of elements of, please tell me also, can you validate the data that is coming out of the answers that are being delivered and that makes it even in some sense, more complicated, but also more mandatory, that observability becomes a requirement.

And so the -- that sounds all really interesting, like at the moment, if I talk to the industry players, that's a little bit of a bragging competition going on. It's like, oh, yes, I work with this -- what's your kind of...

Differentiation?

Yes, differentiation position, you talk about like AI customers or whatever, what's the situation here for you?

The picky phrase I've been using to denote the answer to this question is really, answer is not guesses. And what Dynatrace delivers is answers, not guesses. We always have. This is why the biggest and the big, the most complex of the organizations around the planet tend to buy Dynatrace.

And they do so because in Grail, we can handle billions of interconnected data points in context, manage them across all data types, across all domains and give you an answer that is highly contextual and that is causal, not based on correlation, but causation instead.

The result of that is with a very high probability, we can tell you precisely what the answer to the problem is. Why did it occur? And we will tell you precisely what that answer is. We don't guess based on correlations. We know based on the environment that we've structured.

And for those of you that have used Generative AI and some of the overall LLMs and you've sent out data, you've asked questions and you've gotten wrong answers back. You know that there are issues with that underlying trustworthiness of data. In our case, in order to take autonomous action. You must trust the answer as to why the problem is occurring because otherwise, you're solving the wrong problem.

And the last thing that you can do is have some sort of autonomous agents or agent ecosystem take action on solving the wrong problem. You have to trust the answer. And if you trust the answer, you can then enable autonomous action. And what Dynatrace does uniquely, it is our superpower is to be able to tell you precisely what the action is. Not to live you a dashboard that it's red, yellow, green, not to tell you these are the things that are happening in your environment that you may want to look at based on correlation, but rather this is the answer. This is the cause.

And that enables you to have the trustworthiness of that answer to take action, and that is what has enabled in an autonomous world. And it is obvious that every vendor and observability, if you take a look at our Gartner Magic Quadrant, they are 20 of them. Why is Dynatrace in the far upper right of that? It is because of our ability to deliver answers.

Foundationally, that's a great starting point. And as you move into agentic world, while every one of those vendors is going to be talk, well, I've got an agenetic -- have agentic system because you have to say that. The ability of those agentic each systems to actually take the right action is predicated on the ability to deliver the right answers. Then we would submit that Dynatrace is better than anybody else.

Okay. Okay. Perfect. And then shifting gear to the last -- the next few minutes. So there's a product and the product has evolved. Now let's talk about the organization because the organization needed to be evolved as well. And there's 2 aspects. It is the platform and platform pricing and there's go-to market. Those are like about a year to 2 years both of those initiatives. Can you speak to kind of how this is coming together for you on both kind of vectors?

So go-to-market was one and the other one was....

Pricing, pricing, yes.

Pricing. So the -- let me attack go-to-market first. So -- on the go-to-market side, we simply realize that it is the largest of largest organizations, the most strategic organizations that needed observability from Dynatrace the most. That is where we have the greatest differentiation. And those are the ones that are moving to end-to-end observability. Those are the ones that are driving AI observability. Those are the ones driving business observability. This is where Dynatrace wins.

So we restructured at the beginning of 2024 our overall go-to-market to really focus and attack that. And that's resulted in substantial benefit. For example, our pipeline we reported this last quarter in strategic accounts, these large accounts was up 45% year-over-year. The number of 7-figure ACV deals that we closed last quarter was up 53% year-over-year. So we are seeing enormous traction in the biggest of the big because that's where the complexity is, and those are the ones coming for end-to-end observability from Dynatrace.

So I'd say that, that has been a major evolution in a positive way for the overall environment. Pricing has been part of that. So covering the pricing component, it was funny. But when I first began and I would ask customers, geez, what do we need to do better? One of the elements that came back was, you need to do pricing and licensing better.

And it was because we had SKU-based pricing. And if you bought application performance management from us and you wanted to buy infrastructure management, we'd have to come back and add a contract and sell more, and that was painful and God forbid, you want log management because that was another contract, more painful.

So what we did was we put in place our Dynatrace platform subscription, DPS, as we referred to it. This is basically a -- this is an annualized commit. It could be a 3-year contract, but essentially an annualized commit that covers the entire platform. We've seen enormous traction in it, as you know, Raimo, and it has resulted now in 70% of our ARR just over the last 3 years, becoming DPS in orientation, more than 50% of our customers, 70% of ARR.

And it has substantially broadened the access to the platform. So for example, one of the reasons log management, I would submit to you, has grown so rapidly for us as we've eliminated the contract overhead of that. If you have a DPS contract, you have access to log management, just that simple. Turn it on, enable it, begin to use it and watch it grow and it makes it seamless for customers to then replace other third-party solutions.

Can I -- as we go through this now, like there's one thing that I'm talking with investors about that's kind of always raises the question, it's like, your product story is coming together. Your go-to-market is coming together. The pricing is coming together, but the overall growth numbers haven't changed.

Yes.

So what's the disconnect?

Well, the good news is we look at leading indicators, and consumption is one of those. We see consumption in the low 20s. And while we don't want to make the overall metrics more complicated than they need to be, which is some of the feedback that we've clearly gotten is, geez, don't provide too many metrics because we want to make sure that we're tracking the ones that are most important.

Make no mistake about it. Ones the most important is ARR growth. And the fuel to ARR growth is net new ARR and net new ARR comes from a number of metrics, but inclusive of new logo ACV and expansion, NRR and those sorts of elements. One metric that we did think was relevant to share was this consumption metric because as consumption grows, that provides the fuel to then lead to future upgrades and future expansion.

So we see consumption growing over 20% as a relevant leading indicator of where ARR growth should converge to. Certainly I'm not suggesting that ARR growth immediately moves to north of 20%. But we believe that, especially with logs and application security and some other elements growing well faster than that, that provides the fuel to future ARR growth.

And make no mistake about it, our objective is to reaccelerate ARR growth as we head into FY '27. And we're certainly not at the point of providing FY '27 guidance, but from overall strategic and conceptual perspective, that's what we're looking to achieve.

Yes, because at some point, it needs to show up like -- full...

Has to.

Yes, yes, I see it also in my client conversations on the Dynatrace clients like they love it. Yes. So yes. Okay. The one thing that you probably got feedback as well in terms of communications or where you're different is, if a client over uses on the platform side. Some of your peers would say, well, then I'll give you like the full like a higher price. And then that way, I encourage early renewals, have bigger discussions. You don't punish clients. And on the one hand, it's good, like because you want adoption. On the other hand, it kind of maybe takes away a little bit one off the upsell opportunities.

Takes a little [indiscernible]

They take a little bit. Like how -- talk a little bit about your thinking there.

And in the largest of enterprises, it has been our observation that you don't hammer customers with a stick. It just doesn't work very well. So we obviously are going to charge you overage if you go if you go over, but we haven't been punitive in that regard. So we don't charge 120% of your cost to force you to do an upgrade. We have customers that have 3-year contracts. And if they're 1 year in or 10 months into their first year and they're running at overage levels, the last thing that an IT ops team wants to do or CIO wants to do is go back to the legal department and say, I did a 3-year contract. Could you please renew this contract after 10 months?

So we have -- we -- our account execs obviously have all the incentive in the world to come back and tell you an expansion. So they can do that. And in many cases, that will happen. And in some cases, they'll just pay us overage for a month or 2 and then...

Give you a turn.

Just rotated into the next year. Either way, we're largely indifferent as to how that goes. Ultimately, that is going to show up in ARR. And that's -- we've played a long game, and the long game is ARR growth, and that's what we want to achieve.

Okay. And then what drove the decision to kind of try to smooth that overage out a little bit because it was...

Accounting, is the short form. We -- for those of you not tracking the short form, it is where we were showing ODC revenue, on-demand consumption revenue on an as-incurred basis, and it showed you precisely what the overage was in that quarter. Because we do rack on an overall ratable basis, given that as opposed to a direct consumption basis, that would suggest that we would have to do ODC in the same way. So we had to move it to an accrual basis, which flattened the ODC. So now you can't see the variability in ODC as you look at it, takes away one of those metrics. But on the other hand, it smooths the curve.

Yes. And then last question for me before I let you go. Like -- how do I think about that margin versus growth envelope now for you guys going forward?

We've committed to maintaining the margin level, but our #1 focus is accelerating growth. So we want to achieve both. You're not going to see or at least our current plans don't suggest a lot of margin accretion. We want to be able to use that powder to accelerate growth. We believe that the market is ready for prime time. AI is driving it. We're in the midst of this sort of tornado. We want to take advantage of that, and we want to lead in observability as we look at.

Perfect. That's a great closing statement. Thank you.

Yes. Thank you so much.

Thank you. Perfect. Thank you. Thank you. Good to have you have you again.

Yes. Thanks, everybody. Appreciate you coming.

Thank you.

Okay. Welcome to the [indiscernible] everybody. We're very happy to have Rick and Jim here to talk through the Dynatrace story. Thank you, gentlemen, and Noelle for attending our conference. Again, we always love to have you. We are delighted to be here. It's a great venue for our conference, isn't it?

Yes. And it's -- the good news is shareholders and investors like to come to it, and it's a great place to see. Thanks for having us.

Thank you so much. So let's start off with some good news because I think in this last quarter, you guys reported some numbers and some comments that were quite constructive. Obviously, 16%, 17% revs ARR growth, 20% CRPO growth. Your net new ARR of $70 million was up nicely year-over-year. So obviously, something is feeling good in the business to give you these kind of numbers. Maybe you could put your finger on 1 or 2 things that went right during this most recent quarter.

Well, I think, Karl, you just pointed a number of them out. We delivered strong performance in net new ARR growth at 14% for the first half, 16% for the second quarter. That is, of course, the fuel to drive overall ARR growth. We increased in addition to exceeding the high end of the guide for Q2, we further increased the guide for the back half of the year for ARR growth. So that was positive.

And in our view, we derisked the second half as well. So from the standpoint of sort of core metrics that organizations look at as to performance, we believe that we contributed in a number of those areas. On top of that, there were numerous other growth drivers, which we do speak about that are really the leading indicators, maybe a level down of how does the business feel a level below the core metrics of new ARR.

Let's talk about some of those.

And that gets you into, for example, our Dynatrace platform subscription DPS customers, that's now 70% of overall ARR. We see double the consumption growth of DPS customers as non-DPS customers -- so the greater the percentage of ARR on DPS, the greater the opportunity for further NRR accretion in the future and ARR growth. So that's expansionary. Logs, huge performance on logs now in just the last year, having essentially built a $100 million-plus consumption business or it is, let's just say, rapidly approaching $100 million or so in that region, growing at more than 100% year-over-year.

And that has been also expansionary as part of the overall end-to-end ecosystem. And then you end up with pipeline growth amidst the strategics very positive and then consumption growth underlying that, which we view as a leading indicator of future ARR growth. And that was in the 20% range, 20% plus range. So a number of these, let's say, core underlying factors we felt very good about in the quarter.

And Rick, let's hit on that consumption strength because as you talked about on the call that's one of the things that's driving early expansion, so what is driving that consumption strength in the quarter and hopefully since.

I'll give you that one, if you want it.

So I mean I think it a byproduct of getting customers onto a Dynatrace platform subscription contracting vehicle. As we've said from the beginning that once we get customers on this vehicle, it makes it much easier for them to consume the platform. They commit to a dollar amount. They get a unit price based on their commitment. And so they have full access to the platform with a full rate card. So there's no longer an issue of having a sales engagement anytime you want to have trial a new product.

And so now having that many customers, and it's been growing, as you know, over the last 3 years, now the core underpinning is now they can leverage more of the platform, and they are leveraging more of the platform.

Rick provided a statistic that customers that are on a Dynatrace platform subscription consume at 2x the rate of a SKU-based customer. They trial 2x the capabilities of the platform. And so I think what you're seeing manifested themselves in the half 1 results were changes we made in fiscal '25 to go on the offensive from a go-to-market perspective.

You're seeing it show up now. That wasn't going to happen overnight. And I would say the fastest-growing product that Rick mentioned with logs, you're seeing a lot of our expansions that we saw early, but those were customers that maybe weren't necessarily thinking of leveraging logs as a use case. They were able to trial it on their platform subscription, and it's led to some very significant expansion. So I think we're seeing the manifestation of that now in the results.

Okay, so let's hit on that log performance a little bit more. That was one of the highlights from this call that struck my attention. Similar question. What's behind that? To what extent is that incumbent log management companies like Splunk giving share to rivals like Dynatrace. I'm sure it's partly the investment that you've made in that log management product such that it's just getting better and better, more customer traction. Can you unpack that?

And how big could that be?

Well, there are 2 primary drivers to keep it simple to our logs growth. One of them is to reduce cost. I have seen, I don't know how many dozens of customers around the globe in the last few months. And the adjectives they use range from out of control to meteoric to these kinds of numbers on log costs. Why? It's because cloud is exploding. AI is exploding. It is exploding AI workloads. It is exploding cloud-native workloads that is creating more logs.

More logs mean more cost associated with those logs and an ability to manage that is important. And if you have an ability to optimize the use of logs, traces, metrics, all observability data types as opposed to only looking at logs, then you can get better outcomes for less money. So cost is a piece of it. The second I just alluded to, which are outcomes. Most of the -- well, many of the log vendors traditionally have not had end-to-end observability capabilities.

They've had logs. So how are you going to find a root cause analysis, right? You are going to perform a root cause analysis when you only have logs, you're going to use logs, but maybe that's not the right tool. Maybe that's not the right data set. Maybe you need traces, metrics and having all of that data combined in context to provide analytics then delivers a better outcome. And so it isn't just a cost equation. It is really the combination of cost plus outcomes that's driving end-to-end observability. That is driving tool consolidation. And in our target segment, which is Global 15,000, so the largest of the largest companies around the planet, that causes them to move to consolidating these elements with Dynatrace.

I'd add maybe something to provide additional context for it that -- so we really got the product and the packaging right last fall. So while we had a log solution, I'd say with the product and the packaging and the pricing, we got that right in the fall of last year. And then I think we've augmented that with the addition of the strike teams. So we have these product strike teams that are focused on particular product areas. One of them is logs.

And I would suggest to you that we have both the product, we have the pricing, we have the packaging. And we now have teams of people that are allowing our sales force to be much, much more productive around having these discussions, either leveraging logs on their own, meaning it's an extension of what they're already buying or in some cases, to Rick's point, broadening to an end-to-end observability story. So a lot of the building blocks that you're seeing for things that we've been putting in place has been very purposeful.

So, Jim, Maybe a question for you. You and Rick have talked about a lot of things that are going right in the business. Yet, how do we bridge that goodness with the guide for the second half, which you guided to a deceleration? Rick, you used the term derisked. Is it just conservatism, Jim? Or are there any factors that informed that second half guidance?

No, it's much more just -- the term I've used is prudent. And I'd start with what does the demand environment look like? The demand environment is incredibly healthy. Our pipeline is the strongest it's been in 5 or 6 quarters. So the pipeline is extremely robust. A consequence of some of the go-to-market changes we made, which is orienting more resources around these high propensity to spend customers, which are large, call it, Global 500 customers is, by definition, you're going to have large deal sizes.

We're seeing that play out. We saw that in the first half of the year. Our pipeline is relatively weighted from a mix perspective to these very large deals. And so end-to-end observability, which tends to be the play that is the most successful. There is a lot of pipeline in that area. The timing of that is difficult to judge. It doesn't mean we won't win it. It just means pegging it, does it happen in the fourth quarter? Does it slip into Q1? So we thought that we should build some kind of prudence into that. What I would tell you is that if we have close rates similar to the first half in the second half, we will deliver a much better outcome.

Okay. Jim, on the call or at least the call back, you also mentioned that there were some year-over-year compare headwinds this quarter or next. Can you elaborate on what those were? Is there any way to quantify like on an adjusted basis what growth might have been?

So that was more oriented around subscription revenue than necessarily ARR that -- as you know, that we used to recognize ODC revenue as incurred. And so you saw building over last year. From an accounting perspective, we had to change that in Q1 to a more ratable model. And so the variability that you were seeing in ODC revenue has gone away. It's now smooth.

So you're seeing a bit of a headwind just on a year-on-year compare perspective from ODC revenue. And then every company now again that even with a subscription revenue business, some customers may be what we call on hold, meaning maybe they weren't paying you. So you stop recognizing revenue for them. And then they get off hold and then you start recognizing, you do true-ups. And so last year, we had more of those in the back half of the year than normal. And so what I've suggested to people because they've looked at the back half of the year guide and they say, jeez, that seems like a pretty significant deceleration in subscription growth. And my comment back to them is that if you do adjust for those things that I just mentioned, I'd say the normalized growth rate for the business is more mid-teens, call it, 16%. And that's the way you should think about it exiting fiscal '24.

Okay, that's helpful. Let's switch subjects a little bit to the competitive environment. And I think one of the issues in the last couple of weeks that this group has been thinking through, there's always consolidation in your space, mostly to private equity, not so much strategics. But Palo Alto acquired Chronosphere, a much smaller player than you guys. But obviously, that created a little bit of concern in the Street that weighed at least temporarily on your shares as well as Datadog. Rick, what did you think of that acquisition? What's your perspective as CEO?

Who's Palo Alto Networks? I am kidding. Chronosphere certainly is a visible competitor. But from a direct perspective from Dynatrace, we just don't see them. In the market, they are oriented to metrics. They do not have a broad base of end-to-end observability as a solution and they have traditionally sold metrics increasingly into AI native companies and we're selling into the Global 15,000.

So partly because of the end-to-end observability nature of the solution and the breadth of our solution and selling into the kinds of customers we're selling to and to the personas within those customers to whom we're selling, it really is not aligned as a direct competitive threat. So we don't really see it.

Now having said that, of course, Palo has an ability to invest in that business. And as with all competitors, we will approach it with paranoia and a clear view as to what's happening over the course of time, and we'll make adjustments. One thing that it does certainly validate or one thesis that it certainly validates, of course, is the thesis we communicated a couple of years ago, which is that observability and application security are certainly converging.

So we do see that, but they have some headwinds and the headwinds are going to be breadth of portfolio. Another headwind is going to be the buyer persona of the CISO buyer for Palo Alto Networks versus an IT ops or CIO-type buyer for observability traditionally. And so that's what they're going to have to work through, I think, as they go forward.

Can we talk a little bit about some of your own efforts to step into the security space, not so much Palo Alto going the other way. But what has Dynatrace done to add security features to your already world-class observability platform?

Our application security business -- so our logs business is growing faster than any other business for us at the moment. Second fastest growth is application security. So we are investing there and investing in a significant way because we do believe that convergence. Having said that, we have been very disciplined in our strategy of application security. It is not our intent, I should say, hasn't been our intent to go compete aggressively with all the security vendors. We don't believe that, that is a winning strategy. The winning strategy for us in application security, we believe, to be investing in areas of security in which real-time runtime observability data matters to the security outcome.

And so that has resulted in areas and investments like runtime vulnerability analytics, which is our largest application security portion of the business. It is cloud security posture management, Kubernetes security posture management. It is cloud SIEM. These are areas where runtime analytics coming out of a broad-based data lakehouse consisting of security data types add enormous incremental and immediate value to the security outcome. So those are the areas in which we've been focused as part of the strategy to really evolve and leverage the 2 businesses together as opposed to try to construct a separate security business.

Okay. That makes sense. Rick, let's also talk about some of the ways that Dynatrace differentiates from some of these rivals, many of which sort of as you describe Chronosphere are very cloud-native, AI native. They don't have a presence with Fortune 200s where a lot of their infrastructure is on-prem. So can you elaborate a little bit on the on-prem cloud mix, how that perhaps gives you an edge and which way the wind is blowing in terms of that mix?

Sure. It is clear that in -- and I'll just pick a vertical for the sake of argument, but in financial institutions where we have very, very deep penetration really across the financial organizations, it is the case that they're going to have on-prem workloads for a lifetime to come. They're just going to continue to exist indefinitely.

Now of course, they're also bringing up cloud workflows and those are getting supplemented or they're supplementing the on-prem workloads. So it really is a combination of factors, but the on-prem workloads don't dissipate. And so the result of it is that we believe that this is a significant advantage for Dynatrace by being able to do both with a common underlying platform.

And that does give an advantage because now you're looking at the same dashboard, you're looking at the same capabilities, you're expecting the same answers irrespective of where the workload resides. And as it moves to the cloud or as you move some of those workloads from on-prem to become hyperscaler workloads, then you can use the same set of observability tools, capabilities and platform to oversee that transition.

Okay. I think another differentiator would be on the pricing front, where I think Dynatrace has been a little bit further along in being flexible on your pricing with DPS to customers, whereas some of the other large observability vendors are -- have a reputation for being quite expensive. So to what extent has that let's call it, more flexible pricing structure giving you a head-to-head edge?

I would say that it has. I'd say that the feedback that we get from customers almost universally of the DPS model is it is the most flexible contracting model that's out there. We don't charge overage rates. So if you exceed your commitment, we don't charge you a premium rate when you exceed that, others do. And now obviously, we will talk to them about if you're exceeding your commitment, it means that you're probably getting value.

And oh, by the way, we may be able to offer you a better unit price. So there is this kind of give and take around whether they want to do an early expansion or whether they want to go on demand. And so we get very good feedback around that pricing model. They like the fact that they can trial the platform. They don't have to have a sales engagement. So it's just that it's a kind of a perfect match for what the customer is looking for and what we're looking for.

One of the things that we've done that Rick started out that this notion of consumption and driving consumption, that's not a muscle that we've had, Karl. That historically, we have not been a very consumption-oriented company that I'd say now we have incentive structures focused on consumption. Our customer success teams are focused on consumption. They have a compensation at risk based on consumption.

Our strike teams, their compensation goals are consumption of that particular product that they're supporting. And so this muscle of get them on DPS, get your teams of people that work with customers around driving consumption, driving consumption will ultimately lead if the customer is getting value and they're consuming at a rapid rate to an early expansion. And so you're starting to see that play out. And I would suggest to you that some of the performance that we saw in the first half of the year was a manifestation of that.

Okay. Let's talk a little bit about AI. There's a couple of aspects to it that are interesting. I think one topic that our team is thinking through, and I'm sure investors are, is when will the AI phenomenon be a real pull-through at the observability layer? I think I'll share the consensus and then Rick you can rebut it if you don't agree, that most of the AI applications inside large enterprises are today, still early stage, somewhat lightweight.

They're chatbot-based, they're coding tools. They're not robust enough, and they're not really at scale in production to really need a lot of monitoring pull-through. So you haven't seen it yet. But you will, once the likes of UBS start building more robust enterprise-grade apps, then you'll see the pull-through. Does that feel right to you? Or are there ways in which you're actually seeing a benefit even today?

I think that is right, Karl. I think your articulation is correct. It is the case today that we have hundreds of our customers that have deployed us for AI workloads. So they are already using infrastructure monitoring. They're using log management. They're using metrics. They're evaluating their AI workloads today based on Dynatrace. What will absolutely accelerate is when those go regularly into production and begin to generate production level workloads, I think we'll see an acceleration of that.

On the side, you then have the AI natives who are the LLMs, for example, that are doing their own infrastructure monitoring and others with their AI workloads. And those are already moving at a very fast clip, and that's where the infrastructure monitoring really comes into play for those kinds of companies. But I think you have to look at it both from an AI native perspective as well as AI workload perspective within the enterprise, and you have to think about both in order to really understand the evolution of that space.

Can you talk about your outlook for Dynatrace to penetrate that AI native community? I think you called out some successes on this last call. But can you elaborate and describe to the audience exactly what you're doing to become -- essentially gain mind share in that cohort?

Many things. First, the Dynatrace focus has traditionally been the CIO down through IT ops. We're selling an enterprise-wide end-to-end observability solution that delivers answers, and those answers deliver insights to enable very rapid root cause analysis and analytics and resolution of problems. And that's fundamentally what we've done.

The evolution of the current environment is suggesting that developers are becoming much more involved in the observability decision, and that is abundantly clear in AI natives. So what we've done is over the last year, we've really spent a ton of time on our road map developing or expanding the Dynatrace platform to become developer-ready, number one.

Number two, we've expanded connections into the overall ecosystem. So this past quarter, we announced integrations with Atlassian, very important one with ServiceNow, with GitHub, NVIDIA. So the result of all of these is that we are now built more fundamentally into this ecosystem of agents. And that really results in an ability to deliver autonomous operations in the future through an Agentic ecosystem that others can't provide.

Yes. I think that gets at another question I had about this, and that is all the large successful incumbents like Dynatrace are going to have to worry about essentially, in your case, an AI-native observability player coming at you, but you're not going to sit still and wait for that day to happen. Your R&D team, I'm sure, in a lot of interesting ways, are AI enabling your core product such that you can retain that incumbency. Can you talk a little bit, Rick, about ways in which Dynatrace is getting in front of that risk and essentially innovating to make sure that you indeed are the AI-enabled platform going forward and not some scrappy start-up?

Sure. The most fundamental answer to that question is we're not starting from today looking forward to develop AI sort of capabilities. We have been utilizing our AI-powered platform for more than a decade. We didn't come up with it 2 years ago. We didn't start work on it 18 months ago. We've been doing it for more than a decade.

We build a completely integrated, massively parallel processing data lakehouse called Grail with all observability data types built into it in a causal way with context. That then provides the ammunition for our AI engine to analyze that to derive and deliver very specific answers. We believe that those answers are quintessential to enabling an AI ecosystem of agents to then take action.

If you cannot deliver answers that are deterministic and trustworthy, I would commit to you, you cannot take action on those outcomes because they are simply guesses. So the way we like to think of it is that Dynatrace delivers answers, not guesses. And by delivering answers through this integration underlying data foundation with an AI engine, we set ourselves up to actually add value into an AI ecosystem that others cannot do.

Okay. Let's finish with maybe a quick thought on all the go-to-market changes that the 2 of you have spent a number of earnings calls discussing. Rather than ask you to go back and describe all that, maybe I'll phrase it a different way, and that is you've now had a year to 2 years. So looking back, what in your judge -- give yourself a report card on those go-to-market changes. What do you think went really well? And where do you think you've still got a little bit of work to do?

Well, I'd say where it went really well was, one, I think the weighting of investment to large strategic accounts. That is the customer base that we really shine in. So fortifying resources in that area, I think, was a smart move. It resulted in pipeline growth. It's already resulted in deal closures. So I feel very, very good about that. Two, I would say we've made great traction in the partner ecosystem, notably with GSIs. The GSIs are now a source of pipeline, and they are enabling even pipeline that they didn't source, enabling us to get exposure to C-level leaders through their involvement.

So I feel very good about the weighting of resources to strategic accounts. I feel very good about the partner expansion. I also feel very good about this introduction of strike teams, evolving away from what was a specialist model with security now to the strike teams focused on consumption because at the end of the day, this orientation of consumption, I think, is an important measure for the health of the business. So I'd say if I were to say 3 things now the last -- obviously, all of these things are underpinned by having DPS as a contract vehicle.

Yes, got it. Okay. Any questions from the audience? We've got about 1.5 minutes. We successfully ran through everything. Gentlemen, thanks so much for coming to the event. You've helped to make it even better than it was last year. So I'm super appreciative. Thank you...

Yes. Thank you very much, Karl.

Okay. Thank you all.

I appreciate it.

All right, guys. So Ryan Mac, small and mid-cap software analyst here at Wells Fargo here for the 9th Annual Wells Fargo TMT Conference. The joke that I've been making, this is my third fireside on the stage is we should open the doors up. So I mean you just get a view of the ocean.

It'll be much better. Let's do that. That sounds good, although it was pouring down rain earlier, but now it's nice out.

That's what people keep saying. I mean, people are still used to perfection of how great it is here. This is my first year here. So I'm just like taking them all in. I'm blown away, but...

Pretty nice. You need to do the bluff path along the water.

Yes. And people have been telling me about the hike and everything. So I'm coming here for the weekend before next time. That seems like the pro move.

I think that sounds great. Now everybody is going to leave the room and go for a [ ride. ]

I mean...

Can't leave until we're done.

Maybe 1 year, we can just do a hike fireside.

[indiscernible]

Yes, I'll walk and talk. So look, guys, we'll be taking questions directly from the room, but if you have them, you can e-mail me at [email protected], and we get them in. Here from Dynatrace today is Rick McConnell. Rick, thanks for being here.

Just to start, we'd love to kind of hear about your year so far, a lot of change with AI, a lot of change with some of the go-to-market changes, but -- and something like the ODC and DPS. But overall, I would just love to hear kind of at a high level, like maybe what surprised you? What are you pleasantly surprised with for the year so far?

Well, first of all, very strong first half of the year. And I think the core messages from our Q2 earnings report that we just completed a couple of weeks ago were number one, really strong first half; number two, raised guidance for the second half; and number three, largely derisked that second half. So we felt good about those core messages.

In terms of the core drivers of the business, we like what we see going in. Log management is a key emerging business for us, now very close to $100 million in overall consumption and growing at north of 100% per year. Well, when logs was growing north of 100% per year at $20 million on a $2 billion business, it has limited impact. But $100 million consumption business growing at 100%, a much greater impact as we expect going into the future and a huge beachhead for us as we look ahead.

The overall strategic pipeline, up 45% year-over-year, very strong. So we feel good about the pipeline at the largest end of the segment, which is where we're really seeing the end-to-end observability and the tool consolidation. Our pricing method of our Dynatrace platform subscription continues to grow. That's now over 50% of our customers, 70% of our overall ARR. So we feel great about that.

And consumption growth is super strong, more than 20% and that we believe to be a leading indicator of future net new ARR. So core growth drivers are in place. The business is strong, very healthy as we look into the second half and customers are expanding. And I suppose the macro [ uber ] comment at all is that observability is becoming more and more critical day by day, especially with the expansion to AI workloads, you just -- you need observability. It's no longer optional. It's become mandatory.

Yes. A lots to work with there, but I think the last part is really interesting. So can you just tell me in your customer conversations, like how do you feel like there's a higher priority place on observability? Like what does AI have to do with that? Like how does that change, I guess, versus like a year ago or in prior years?

Well, many different ways, I would say AI is changing the calculus on observability. The most basic one is that more workloads mean more observability. So you really as a -- especially in our target segment in the Global 15,000 and at the high end of the Global 15,000, you simply can't manage software workloads manually anymore. The number of resources required to deal with alerts, to manage those alerts to then triage those alerts is extensive.

So the result of it is you need to be driving toward a methodology of automated processes to be managing software workloads. And this is where Dynatrace, in particular, comes in with our overall environment, which we can maybe get into, but some of the technologies underlying Dynatrace and the Dynatrace platform really lend themselves well to delivering an AI-powered observability platform that is increasingly driving autonomous operations.

And I've been to -- I've been privileged to have been in, I don't know, a dozen countries in the last 3 months, meeting with many dozens of CXOs. And I would say that not only is observability top of mind, but figuring out how they can leverage AI to automate outcomes to drive lower cost and better success in software are very top of mind.

I think that would be a great place to start on the AI theme is in terms of the Dynatrace architecture, you've been doing observability at the largest of scale for some of the biggest of customers. So as people think about like where can they start on their own AI journey with the products that they're coming out with, how are your existing customers, one, looking to utilize you today? And then two, like what about your technological background makes it a better choice to start with for your customers?

Yes. A partner asked me the other day and this particular partner was of the mode of, geez, we're -- we've sold AI into maybe 10% or 15% of our customers and the actual deployment of AI is maybe 10% or 15% of those. And his question to me was, what percentage of Dynatrace customers use Dynatrace AI? And my answer is 100%. And it isn't 100% using agentic AI with autonomous operations where everything is auto correcting. That's still to come.

But the foundation of AI, causal AI, predictive AI, generative AI, all analyzing an integrated data lake house of content, including logs, traces, metrics, behavioral analytics, business events, et cetera. That is then being utilized to deliver answers, not just dashboards, not just red, yellow, green alert, but this system broke here and you need to fix it in this way.

And that is becoming more and more crucial day by day. And so -- and it is that AI engine of Dynatrace that hasn't existed for 1.5 years or 2 years or since AI became a thing, an exciting new thing. It's been around for more than a decade. If you then add to that the next phase of AI for observability and Dynatrace, it gets super exciting. And we can go there if you wish.

The short form and to keep it as simple as possible is observability has gone through a number of phases. And I would say we're now approaching Phase 4. And to cover the first 3 phases, simply, I would do it in sort of single adjectives. Phase 1 was reactive. Something broke, you tried to fix it or you tried to figure out what was wrong and then you try to fix.

Phase 2, I would say, was proactive. It was about automated root cause analysis. You wanted to know the second something broke, you wanted to know what was wrong, but you had to manually fix it.

Phase 3 was predictive, and that's really where we are today. And that is taking all of the AI elements that we had before and applying additional machine learning and anomaly detection to anticipate issues to be able to resolve them before they became user impacting.

Phase 4, though, is really where we all get super excited at Dynatrace. And this is around autonomous operations, as I mentioned. Well, what does that mean? That means integrating this predictive element into an agentic AI ecosystem that is essentially focused on delivering auto prevention, auto remediation and auto optimization, these 3 things. And in order to do that to auto prevent, auto remediate, auto optimize, we recognize at Dynatrace that we are a core, a necessary input to that equation because we can tell you precisely what's wrong.

But we aren't always the solution to fix it. You may need to provision more storage on AWS. You may need to do a rollback of an application that was posted that had a bug in it, and that may be an operation for a GitHub or a Jira. You may need a workflow integration, and that would be with ServiceNow. So in this autonomous operations environment, what gets exciting is that we provide a core foundational element to what needs to happen, posted into an ecosystem of agents that then can take action through any number of these partners to then resolve the issue.

And maybe a final point on it is you say, well, you're never going to be able to resolve 100% of the issues in an autonomous way because you won't trust the answers. That is true, but I've had so many CIOs, so many CXOs tell me, Rick, if you could resolve 20%, 30%, 40% of my incidents, you would save me, especially in our target segment of the largest companies on the planet, you would save me tens of millions of dollars.

And who doesn't want that? I mean, as you go through the phases of observability historically, right, as you kind of outlined where you went from reactive to proactive in terms of like how to think about your observability footprint, like what does that mean for how do you think about like which vendors you use or one platform versus best-of-breed for observability? Because it seems like to me in the dynamic you outlined on a go-forward basis, right, you almost want to have like one end-to-end platform in order to do those use cases. So do you think that changes with more focus from AI?

Well, this is a lay-up question that's going to sound self-serving an answer. But yes, I mean, the short form is we have seen material consolidation in observability. It used to be the case that you would have one vendor for application performance monitoring, APM. You would have another one for log management. You would have another one for real user monitoring. You would have another one for synthetic monitoring and another one for infrastructure and so on.

And we -- there's a large airline comes to mind that we closed last year in the summer, and they had one of everything. And when they started on the journey with Dynatrace, the principal there even told me, gosh, I can't even imagine deploying Dynatrace because I've already got one of everything. How is that going to solve the problem? And in the end, they weren't getting the outcomes they wanted. So they ended up with an end-to-end observability road map that basically was Dynatrace, and it eliminated or supplanted all these other tools, deploying Dynatrace as a single integrated AI-powered platform instead.

And that gave them much better outcomes than they otherwise would. Well, why is that? Well, if you have the underlying data types of observability, things like logs and traces and metrics and really user data, and they're all in different data stores managed by different vendors, then you are out of necessity managing those on a manual basis to try to derive insights. And the more complex the business, the harder it is to drive those insights and the harder it is to piece things together. And God forbid, you have multiple incidents at the same time. And then what do you do? And how do you cross-correlate this data? It's impossible.

With the Dynatrace platform, we have a single integrated data lake house, which we call Grail, which houses all of those data types. We oversee and analyze that with a single AI engine called Davis. We evaluate that in the context of a single overall IT ecosystem topology called Smartscape. So the result of this is by providing a completely integrated platform, you have a comprehensive integrated picture that you can then act upon.

And in fact, this is the motion that we see our customers driving and especially the larger the customer, the more complex the environment. The more complex the environment, the more they need a single integrated platform. And this is the directional heading.

And if you look at a Gartner Magic Quadrant or a Forrester Wave or others over the course of years and you trended it, you would see that the point products are falling down into the left and platforms are very much present in the leader quadrant in the far upper right. And it is because, first, that's what customers are actually doing, they're betting with their wallets. And secondly, that's where you get the best outcomes.

Yes. I mean you always hear in software like, oh, we want one pane of glass. And it makes sense in theory and why it would be nice. But when you have like a more reactive use case, right, like archeologist, then it's okay to go platform to platform or vendor to vendor. But if you're trying to make insights and forecasting, right, that seems a little more difficult.

We'll come back to the AI piece in a second. But just on the consumption rates that you talked about, around 20% consumption growth rates that's higher than the current revenue rates. I'd love to hear how that's trending and what's kind of driving that higher level of consumption?

Well, consumption rates are up quarter-over-quarter. So our consumption rates are growing in part fueled by the log business that we discussed earlier. And those consumption rates are, we believe, precursors of the opportunity for acceleration of growth in ARR and subscription revenue. And that is what I wake up every day thinking about is how do I help the organization as a whole to reaccelerate top line.

And that is really with a keen focus on expansion of net new ARR. And the good news is we saw that with an acceleration of net new ARR in the first half and in particular, in the second quarter, a 16% net new ARR growth was very, very favorable result in the second quarter, 14% for the first half, very strong also.

So those -- that really is the fuel to a reacceleration of top line. And why consumption is important is it's important to remember that we report revenue on a ratable basis, not a consumption basis. So consumption growth doesn't translate to revenue growth precisely for us. It is with a lag. So if the platform is being consumed more and more and more, then ultimately, that should lead to a convergence of those rates and that ultimately upgrades and ARR and expansions would catch up because customers can't consume in, for example, the mid-20s of consumption while they're only growing revenue 15%.

I mean, at some point, it converges. And that's the expectation is that the faster we can drive consumption, the more demand there is for the platform. The more demand there is for the platform, the greater the opportunity for ARR growth down the road.

And that's the leading indicator you're probably most focused on, right? Like how much people are...

Yes. We've got 1,400 people in our services organization who don't think about net new ARR. Those people in our services organization, customer success, services, deployment, business insights, business metrics, these people are focused on consumption.

Excellent. So as you talk about a quarter-over-quarter improvement on consumption, what are some of the components driving that? Is it a better macro? Is it your customers doing more maybe with agentic AI? Or what is -- or like maybe they're adding more logs? Like what are you seeing to drive that higher consumption rate?

A combination of things. Number one, just growth of existing workloads. You need more servers, more logs, more whatever. Second is the inclusion expansion in new workloads, and those could include core level new workloads, consolidated workloads from other vendors or AI workloads, net new AI workloads.

And then a final category might be new products and logs would fit in, in that category, for example, of where we see logs growth at 100%-plus growth year-over-year in terms of consumption, all of a sudden becoming material, and that really is driving new opportunity for consumption growth as well.

Excellent. So I mean, consumption definitely seems like the metric on a leading indicator you should focus on. Investors have been looking at net new ARR and ODC revenue and subscription revenue. But as we think about the most recent quarter, there were some dynamics where like you had customers do early renewals, and that's great and net new ARR improved, but then maybe ODC was a little lighter than investors were looking at. But that's okay. I mean you're encouraging the right incentives for your larger customers. But can you just talk about some of those early renewal dynamics and what investors should think about there?

Yes. It's funny since the earnings call, we certainly have got investors that have come back and that have said, wow, ODC was light, which is your on-demand consumption revenue, which is essentially overage billings. And I would say our response to that is sort of twofold. Number one, light meant $1 million to $2 million on almost $0.5 billion of quarterly revenue. So...

We're nitpickers here. That's how we go.

That's rounding here. And you always want to exceed expectations, and I've got it. I understand that. But we blew out ARR, net new ARR relative to even internal projections, let alone guidance. And it was simply a quarter in which the cohort of customers that were renewing in that quarter decided that instead of paying overages, they would expand.

Well, every cohort in every quarter is going to be a little bit different. And we can't predict who's going to decide to pay overages and -- for a couple of months before going into the next year cycle and who's going to renew early. Overall, I would say, if I had to pick, I'd rather have the ARR than the ODC because ODC is, by definition, a onetime event and ARR is recurring.

So an expansion -- an early expansion by a customer, let's say, 1 or 2 years into a 3-year contract is a very, very healthy signal that they are intending to stay with Dynatrace, intending to expand the deployment with Dynatrace and probably going to be increasing consumption down the road rather than as a one-off with just overage revenue for a month or 2. So if we had to pick, we'd like to see the ARR conversion versus the ODC. But ultimately, it's the customers' choice as to whether they want to pay a month or 2 of overage versus expand, and we give them that option.

And so what do you think is driving that decision to renew early? Is it just they've realized, okay, we're going to have a lot more utilization? So...

If customers are expecting, and this is why the dynamic toward net new ARR is preferable, let's say. If a customer is expecting and willing to commit to a higher overall contractual commit through a DPS agreement, then they should expand early. And the reason is because they're going to get lower unit price. So it certainly is the case, the more volume you do, the lower the unit price. Now the commit will go up. So maybe your original DPS contract was for $1 million a year, and now you're consuming at a higher rate, you go to $2 million.

So you're going to spend more, but you're going to get more than double the capabilities off of that 2x improvement. So you might as well take advantage of the lower price point, increase the commit, make that higher commit. And the result is that you're going to move to an ARR expansion as opposed to an ODC single payout.

And so as I look at ODC versus the new ARR, that's just like a timing thing in regard to...

Just timing, I mean, ultimately, ODC as long as we -- ODC obviously ends up in subscription revenue. But to the extent that you continue to expand, that is a sign in and of itself that you have exceeded your commit for that 1 year. By definition, if you're paying overage in that year, you exceeded the commit for the year. And that is a healthy indication any way you look at it.

That's a pretty healthy signal. Yes. And since your DPS customers, 50% of your customers are on DPS, but 70% of your ARR, as you think about who's doing these renewals, those could be bigger customers as well. So like that would exacerbate the timing dynamic there if they had an early renewal.

Absolutely. And the largest -- the larger at this point on DPS contracts is because that contract vehicle gets them access to the full platform.

Excellent.

It also makes a lot of sense to be on a DPS contract for seasonal fluctuations. You take a look at commerce. And I mean it's timely because we're coming into a period now of the holiday selling cycle with Black Friday and Cyber Monday. Well, you look at our large commerce customers and their requirements for observability explode in the calendar fourth quarter.

And if you have exclusively a server-based pricing model, then how do you manage that? I mean do you quadruple the number of servers you need for a quarter and then -- I mean you can't do that with us. DPS enables you to do that because you basically just sign up for the platform for the annual period. And you have factored in the fact that Q4 may be -- calendar Q4 maybe a large multiple of the other quarters, and then that enables you to grow, to expand and then contract. It gives you much more flexibility. And that drives greater consumption as well. That flexibility enables our customers to expand way beyond what they would have done otherwise.

I'm going to move on from this dynamic, but just so I'm clear here. So like if you're that type of like retail customer running into the holiday season and your consumption is already running pretty hot, it might make more sense to like, okay, let's do the contract renewal now because we already know we're...

I mean, if you're coming up on the holiday selling cycle and you're running short on your contract, you might as well expand.

Yes. That makes sense to me. So just on one of the comments you made earlier about the log business. I would agree with you, at $20 million growing 100%, it's like that's great. I'll see it in a couple of years. And then now we're here. So -- but still...

That was our fastest business to $100 million. So I mean, we really just began selling logs in earnest in October of 2024. So it's really been just about a year that, that business has grown to that size.

So can you talk me through like what you think the next 6 to 12 months looks like for that logs business? Like it's a higher ticket item, right? So are you winning from a competitor here or your customers looking to do like get their logs under one roof with AI? Like what's kind of driving like the next leg of growth for logs?

There are 2 primary drivers to our logs business. One is cost, which is -- I had a CTO of a large Australian bank tell me that their existing logs overall cost was meteoric. I mean the word that he used was meteoric. And yet they didn't feel like they were driving any additional value from that. They're storing more logs, they're ingesting more logs, they're querying more logs, but not a lot of incremental value. And they very much wanted to get a handle on that. And they need to find a path where they can manage the cost trajectory.

The bigger element, though, I must say, is what I talked about earlier, which is your question, Ryan, on platforms, which is I'm not sure why, and I've been in this industry with Dynatrace for 4 years, not 10. But I have no idea why logs grew up on the one hand and observability data types and others on the other. It makes no sense. And the reason it makes no sense is what I described earlier, which is it is when you have all data types, inclusive of logs in one integrated data lake house that you can deliver the best outcomes, the more precise insights that are most actionable. If ultimately, your objective is really autonomous operations, that's when you need precise insights, you need precise answers.

And to do that, you really want logs because logs add value to that. Moreover, it contributes on the cost front, but you actually don't need to store as many logs if you have trace symmetrics in many of the other data types because the incremental insights that you get out of all of the other data types combined actually helps compensate for not needing to have a log for everything.

So it actually consolidates the number of logs that you have to track. It makes it much more intelligent. It gives you a better mapping and it drives better outcomes. And the result of all that is that our log business is growing because of those dynamics. And if we can save you a fair bit of money, and we can do so by driving a more integrated developed outcome out of an overall observability plane, then you're going to be inclined to move in that direction, and that's what we're seeing customers do.

So they probably have a logs provider today. And so there are some share gains as a part of this, but this seems like a more durable trend towards like shifting towards one platform than like 1 year of people shifting away from different vendors.

Yes. And it is because as you move to an integrated platform, it becomes much stickier. So if you're simply replacing like-for-like logs to logs with the sole objective being cost improvement, you're going to potentially run the risk of down the road, another vendor coming in and doing it for yet cheaper. And that then doesn't deliver the stickiness. In our case, it is -- I'm not sure I can even think of a case where we've done exclusively a logs deployment because that isn't why customers come to Dynatrace.

So the result of that is you are doing logs, traces, metrics, you are integrating all those elements, you are applying it to applications, infrastructure, real user management, log management, traditional use cases and beyond. You are even applying it to diverse personas. You're applying it to AIOps, but also developers, SRE teams, platform engineering. They're all using the same underlying data stores, the same underlying AI logic. And that is resulting across the board in better outcomes. So you become much more embedded and therefore, much stickier as you look forward. So I think the likelihood that it -- a log workflow comes to Dynatrace and then leaves later on is much lower as a result of that platform-based approach.

Excellent. And maybe due to logs or maybe due to more broad-based strength or something else, but I thought it was interesting that your new logo land size increased 30% in the quarter. I know you guys had a big shift towards upmarket in your go-to-market. But, yes, anything that can call out for why those new deals are landing bigger at this point?

It is -- it follows, I think, Ryan, very logically from all the rest of the discussion that we've had so far, which is that end-to-end observability is becoming more [ proficient ]. And whether it is a large bank, a large insurance company, a large package delivery company, many others I can think of, these are landing bigger. And the reason they are doing so is because they are resulting from a pretty substantial tool consolidation and the tool consolidation is driving the bigger land.

So instead of just an application performance monitoring, deployment that is land and expand on a single application, it is, no, I've got all these observability tools. I'm trying to make sense of it. I need to combine them. I need to converge them and then I need to attack it in that way. And that's what we're seeing, and that's driving the larger land size.

Excellent. And you talked about some pipeline strength with larger customers as well, but it's difficult to wrangle the timing on these things. Like -- is that just like enterprise buying, it's tough to pinpoint...

Yes. This provides some of the challenge in our guidance, to be honest, which is we delivered a very strong Q1, very strong Q2, a very strong overall first half. We raised guidance. But some investors have asked us, well, why not more strength in the second half guide? And the answer is well, trust, number one, that our internal plan is higher than the guide, obviously, without a question. But number two, that it is just the variability in these large lands, whether it is a large expansion or a large new customer land, it just adds more uncertainty.

Now I think we've done an excellent job of managing that uncertainty heretofore with very good results. And so as I mentioned at the outset, we believe that we have radically derisked the second half as a result of this. And with the strategic pipeline growth at 45%, we believe that we've got the pipeline to cover some of these machinations of these large deals, but it is a reality of our business.

And some conservatism around close rates in the second half part of these deals?

That's exactly it.

That makes sense. Two more AI questions, then we'll wrap things up. Is there anything about APM that makes it a natural starting point for customers who are looking to observe AI use cases that they're about to roll out?

I would say in the AI native, it's a more logical use case to start with metrics and logs and probably infrastructure. So that's probably where they land.

You started first. And then large language model self observability seems like a very early innings for that. But are you starting to get more questions from customers around what Dynatrace can do in that use case?

Definitely. It has not been our starting point as a company. We have sold to the CIO or the CXO or AIOps for enterprise-wide deployments. We have, unlike some others in our market, not typically sold to developers. But the evolution in the platform that we're delivering that we've been working on now for the last year that is slated for release very soon is very much oriented to expansion in the developer space. And the result of that is that really provides us with much more fuel around AI native as a use case and a target customer base for the next evolution of Dynatrace beyond just the CIO, AIOps deployment.

So we're very excited about it, and we bring, we believe, a lot of value in this agentic world in a number of ways. Number one, for AI observability use cases, for things like hallucinations and guardrails and all the integrations you need to have into AWS and Azure, GCP, ServiceNow, you name it, all of these vendors to provide a comprehensive deployment. Now having those capabilities really gives us the starting point.

We have already deployed capabilities for AI observability into hundreds of customers at this point. So they're already using it today. So we're super excited about that. And we think that, that establishes the foundation for an agentic AI evolution into the future, which is this ecosystem of agents that can really take action where we believe Dynatrace is, in many ways, uniquely situated to take that on because of the precision with which we deliver answers, not just dashboards and not just data, which is really our superpower.

And with developers more focused on those as a customer, your shift to DPS and consumption makes a lot more sense in terms of they can scale more quickly on the Dynatrace at this point.

Exactly.

We're out of time. Thank you so much.

Thanks, Ryan.

Appreciate it. Thank you, guys.

Thank you all.

So we're going to finish with a bang here right before lunch and then move on to the rest of the day. But yes, this morning is moving really, really quickly. I'm thrilled to have Dynatrace here once again. I know you guys forever, and it's just -- it's fun to see the evolution of the company and to think about opportunities. We talked -- we'll get into it more, but thinking about some of these incremental opportunities, I think, are so exciting for the future of Dynatrace. And it really feels like in this world where people are looking for names that could see an inflection, I think Dynatrace is certainly one that is capable of that. And so we're excited to spend time with Jim Benson, CFO. Noelle is down in the front row in IR, and thank you again for being here guys.

Jim, you guys are coming off of a really strong Q2 results. You didn't see any ARR deceleration, and you raised the full year guide after Q2. And so I want to talk more about that. But just could you start out with just how you're seeing the overall buying environment? Obviously, the beat and raise would be indicative of, I think, what you're seeing, but just maybe set the stage for some of the underlying trends that you're seeing out there?

Yes. I would kind of echo your point. We had a great Q2. We got a great first half. So we accelerated in net new ARR to 16% growth in the second quarter, 14% for the half. And you really got to kind of bring it back to -- we made a lot of changes 18 months ago. A lot of changes on the go-to-market side that we were very clear we're going to position us to go on the offensive for the opportunity to reaccelerate growth in the business. And so I think you're seeing that. You're seeing it show up in the results. You're seeing Q1 and Q2, producing. We're getting more customers, and we'll talk about it I'm sure as the discussion proceeds, we're getting more traction with our Dynatrace platform subscription.

We are getting significant traction now in logs. The go-to-market motion now 18 months in is starting to deliver with some level of consistency. We're seeing the underpinnings of the Dynatrace platform subscription as customers consuming the platform. They're consuming the platform at a very rapid clip, over 20% growth in dollars. And so we feel really good about the building blocks that we've been talking about. And I think you opened it. What you get investors get with Dynatrace is the story of balanced growth and profitability that we're a unique company that delivers both of those things. And I think you get optionality around a pivot upward on growth, which is really what we're striving for.

So maybe let's just hit this right now. When we think ahead, how should we think about really the timing of growth acceleration and really -- really based on some of these early indicators like DPS, logs momentum, pipeline growth, consumption trends. But just like how should we think about the timing of this acceleration?

So I think you're already seeing the -- it manifests itself in -- it starts with that new ARR growth. At the end of the day, that's where you're going to see it. And where we did see net new ARR growth in Q2, we saw it in Q1. So we're already starting to see the benefit of that. Now we've got to continue to put more points on the board, right? We've got to continue to develop more consistency. So the ambition of the company is to reaccelerate. You're starting to see it manifest itself in the results already. And we've got to execute. One of the things we talked about for our second half is that we are not demand constrained. The demand environment is very healthy. And we are weighted. The good news is we are weighted to a large number of very large deals. So we have a large -- now it goes hand-in-hand with go-to-market change we make. We're focused more on large enterprise accounts, not surprising that the pipeline is weighted towards large deals for the large customers. They do bring an element of timing variability. So we have to execute against that, but I feel very good about the building blocks that we've been talking about and actually seeing them in the results to date.

And really, I mean, the goal is -- and you guys have been very consistent. This is you think the business can grow at a 20% clip. I mean that's what you guys are sort of building this for with the changes in go-to-market, the product. You said EPS growth. And that -- I mean, that's the framework that we should be thinking about as we progress into the future.

Yes. I mean, I certainly don't want to get ahead of ourselves. I think the market supports the growth rate north of 20%. So the market supports that. And I'd say when you generally think about the broader market with more workloads coming online with AI and kind of continued evolution of AI and AI becoming more production level workload, you're going to see more of that. We got to execute against what we have in front of us here, which is green shoots. They're playing out. We've got to deliver a good second half. We're going to continue to see progression in our growth in net new ARR, and we'll see -- we are certainly not constrained. The products aren't constrained. I'd say the go-to-market is not constrained. We're in an environment where we have to execute.

Yes. Now you raised the full year after Q2. And in the past, you've been a little hesitant to do that early -- still relatively early in the year. What were some of the signals that -- because now -- because you talked about large deals. And one of the questions that we had from investors is like, okay, if there's a large deal uncertainty, they raise guidance, does that increase the risk of variability in the back half of the year? What gave you the confidence thought to raise?

I would say that we -- our go-to-market leadership has continued to advance and mature. Our CRO has now been in the company for 2-plus years. He's brought in many leaders on his team. And so I think we certainly upleveled the leadership. And so I would say the quality of the pipeline, the quality of the reviews, the quality and depth of our understanding of the fundamentals of the business is pretty strong. So our visibility is really good. Visibility gives you confidence. And so when we look at kind of where we're at, pipeline growth is better than it's been in 4 quarters. It's growing almost 2x the rate of our ARR growth rate. So it is very, very, very healthy. So that visibility, visibility with quality of pipeline and knowing this pipeline at a level of detail with a team of people, I'd say that are inspecting it pretty well, give us a lot of confidence to increase the guide. And what I would say is that we certainly have to execute against it. One of the things we talked about was that the pipeline is big enough that if we have similar close rates that we saw in the first half of the year, you'll deliver better than what we've geared. We did derisk the back half of the year knowing that there is timing variability with large deals.

Yes. Let's talk about why that pipeline is growing as rapidly as it is. I mean I think one of the presumption is the core economy more comfortable with AI rollouts, inferencing. Are you seeing anything from -- I mean, the pipeline would suggest this, but like what -- like what is driving that underlying confidence in these customers to think more broadly about monitoring in the future?

I think it's a couple of things. So the #1 sales play that we have been able to get progress in. We have 3 sales plays. We have end-to-end observability. We have kind of our traditional land with an application where we provide application performance monitoring or cloud data workload, which is a little bit more grassroots. The #1 sales play has been end-to-end observability. So you say, what's causing these large deals? What's causing these large deals is we focus on large enterprises with a very large, complex hybrid environment. So they have on-prem solutions. They have hybrid solutions, they have hyperscaler solutions, and they have basically an abundance of all of them. And they have fragmented tools. They have fragmented tools in their ecosystem.

And I think what's been happening is what started out as maybe an early theme 18 months ago was customers considering, I need to start consolidating these tools to get better economics. That's become a more pervasive trend, especially for these large customers. And so we've made great traction in being able to consolidate tools, save customers money, save customers money on software costs to consolidate fragmented tools, lower their software bill. And then you allow the environment to run more efficiently -- run more efficiently. And what you get with the Dynatrace platform is not just an efficient operation, but an ability to actually diagnose where exactly issues are so you can go remedy them and hopefully prevent them from occurring in the first place. And so your point about why are things building? I think things are building because customers are frustrated with what they have in place. So it's not just about, hey, I want to monitor new workloads. There is an element of that, right? But there's also an element of, I don't like what I have. I spent a lot of money, I have fragmented tools and I still don't manage outages very well. They have a lot of dashboards. They have a lot of alerts and a lot of people chasing and I need a new way of dealing with it. And I'd say we have a unique proposition in that regard, which is why large complex enterprises like Dynatrace.

So it sounds like it's multifaceted what's driving some of this pipeline. How much of it is customers thinking about AI native app build? Like just that -- because I think there's a lot of perception is some of that workload going elsewhere. When you talk to your customers, like banks, insurance, global companies...

The reality is everyone is experimenting with AI workloads, and they are in the enterprise. And there are many companies that have AI workloads that are in production environments, but it is still a small percentage. But there will be more, and this will continue to grow, and this will continue to build. And so one of the things that we have found is that people have asked me, hey, is the investment people are making in AI crowding out investments in other areas, Matt? And the reality -- because it isn't like the CIO is getting a huge budget increase, right? They have to figure out a way, where am I going to lower cost to be able to self-fund some of these things. I think that's where this end-to-end observability proposition comes in, which is they get a twofer. They can lower their software costs by consolidating fragmented tools and they can deliver a better result. And so I think we are the beneficiary of that. And what it allows the customer to do is they can free up dollars to invest in other initiatives that they have because we're able to save them money in the process.

Part of it, too, is it that customers feel more comfortable and now we're sort of -- we're well into the AI cycle at this point. But some of the AI budgets are more defined. And all of a sudden now, it's like, oh, well, as that increases before my -- we'll get into DPS in a second, but my consumption needs to increase to...

There's an element of that. That's the benefit of the Dynatrace platform subscription model. You get full access to the platform. You're not having some sales engagement where someone having to sell you something. You get a rate card, you get full access to the platform, you can trial anything you want. And so that certainly does benefit, whether it's an AI workload or even an existing workload.

So from a DPS perspective, I think it's now 70% of ARR and 50% of customers are on it right now. When you see the opportunity for that DPS pipeline, I mean, obviously, there's further expansion just within the customer base. But what is it that -- effectively, why is that [indiscernible]? Is it because it increases the usability of the platform, it increases the amount of ROI that customers are seeing and obviously paying for that?

I mean the #1 complaint that we received as a company before we implemented the Dynatrace platform subscription is we love your products. But you are very hard to do business with because we have to buy a finite number of SKUs for this. And then if we want to swap something out that we want to buy something else, it was always a sales engagement Matt. With the Dynatrace platform subscription, you commit to a dollar amount, you get full access to the platform over a term. And it's much easier for customers to buy what they want, use what they want. And we knew this was going to be the case. And we knew if they were going to get more value out of it, they would expand and use more of the platform. We're seeing that play out.

The DPS customers consume 2x the rate of a SKU-based customer. They consume 2x the number of capabilities. So they use more of the products, they use more of the platform. One of the things that we introduced just 6 months ago is, we didn't have a CSM motion that was actually measured on driving consumption because that wasn't the model before. The model before was largely sales sold something and then you had a CSM motion that was there as needed for the customer, more of a customer satisfaction role, and I would say, we're passive. We now are compensating our CSMs. We're now compensating our strike teams, which are focused on 3 product categories, logs, DEM and application security. They're measured, they are compensated on consumption. So what goes hand-in-hand get them on DPS, you now have teams of people that are there to drive adoption. You drive adoption.

We talked about consumption growing north of 20%. While the business isn't growing north of 20% right now for ARR and the business is not growing north of 20% on subscription revenue. What it tells you is that consumption at 20% growth is a leading indicator of what usage of the platform customers are using. It will pivot over time, it will lead to an acceleration. You obviously have to continue with those rates. And so I think we have the recipe now. The recipe with the go-to-market motion is maturing. And I'd say we are already seeing traction in that the recipe now of augmenting this Dynatrace platform subscription model with a consumption orientation and a consumption measurement, all of these things lead to more consumption and expansion of Dynatrace, which is good.

Yes. And another element, ODC, which is -- it's been a topic of conversation for the last several quarters. You saw customers recommit less ODC. I mean, I guess, fundamentally, why? And do you envision a point in the future? Because I think one of the questions that we get is Dynatrace, they give us a lot of transparency in these metrics. But is there a point in the future where just it's about subscription revenue growth and we...

Yes. I mean one of the things we've always tried to do with investors is to be super transparent, as you know. Life was simple 1.5 years ago, where investors just worried about ARR, they worried about new logos and they're worried about expansion, right? And that's what -- that was the recipe for the model. And then when we introduced Dynatrace platform subscription, an unforeseen thing happened last year, which is customers all of a sudden decided that when they were very early in their contract life cycle 1 year, most of our DPS contracts are 3 years, year in, consuming at a rapid clip, they went on demand until they paid us an overage. We didn't really expect that. And so we would try to be helpful for investors around we are seeing a phenomena for customers where early in their contract life cycle and maybe not choosing to do an expansion because they just went through a renewal maybe a year ago.

Now what we're seeing, Matt, is now that we're now seeing the second year cohort class, which is of DPS customers that are now in their second year of their 3-year contract reset. And if they're consuming at a very rapid clip, they're more incented now to do an early expansion. One, they're closer to their renewal date. You're within a year. When you're in year 1, you're 2 years away. Two, they're probably leveraging more of the platform after being on the Dynatrace platform subscription for 2 years. And so there's an economic benefit for them that they're going to get a better unit price. I use the example of you might have a customer that was on a 3-year agreement, $1 million a year. Maybe year 1, they were consuming it $1.2 million. And you say, you know what, $1.2 million, 1 year into the agreement, I'll go on demand for the $200,000. Now you're in year 2, that $1.2 million has maybe become $1.8 million. And you say, wait a minute, now I'm reaching a point where if I do an early expansion and maybe I commit to more like [ 2.5 ], [ 3 ] a year, I'm going to get better unit pricing. And so you saw that play out in Q2. You saw customers that chose that route. So I think what investors need to realize is that we haven't gone full circle or full cycle, I should say, the Dynatrace platform subscription customers. In fiscal '27, our next year, that will be the first year where you have customers that are going through their third year of their cohort. You'll have second years and first years. And so they're going to have a much more balanced list of customers that are either going to do an expansion or they're going to go on demand. Now obviously, we have to continue to drive consumption. You have to continue to make sure that motion works. But the recipe is working. We're just going to continue to play it.

So I guess from a goalpost perspective then, we -- ARR was the metric early on, and it felt like subscription revenue was kind of the new North Star. How would you tell investors to think about balancing all these things because the reality is it's helpful. The transparency is helpful. It does create a lot of questions.

Yes, it does. I mean if you really kind of boil it down, subscription revenue is both ARR that manifests itself in subscription revenue and its ODC. So at the end of the day, which shows up in the P&L is subscription revenue. I'd say the leading indicator of like how are you guys making traction is net new ARR. How is the company doing on generating net new ARR? I mean if I were to kind of boil it down and say, you provide a lot of metrics, but what metrics do you think I should really continue to focus on? I think net new ARR and net new ARR growth is a really important metric. We're starting to show traction in that. If you can accelerate, you continue to accelerate net new ARR, you will see an acceleration in ARR. ODC, it's 1% of revenue. It's not going to -- I think it was -- we needed to introduce it for investors because it was new. I would say it's 1% of revenue. And it's not going to move much -- around much more than that. And so it's just take it for what it is. It's going to show up in subscription revenue, it's going to be 1% of the revenue. And really, what you need to focus on is how are we doing around ARR and generating net new ARR.

If I were to simplify, that's probably the simplest metric to look at. And we've shared, and I think we'll continue to share possibly how is consumption going on? Like at the end of the day, getting customers onto the platform, the metrics that investors look at financially are, well, ARR, net new ARR, whether it be new logos, whether it be NRR. Those are all important building block metrics. At the end of the day, what drives them is consumption. If you can consume -- if you are getting consumption growing at a rapid rate, those metrics will pivot. And so we don't want to confuse investors. We want to make sure, as we always do, that we provide full disclosure. But if I were to really simplify ODC 1% of revenue, focus on net new ARR and ARR and that ultimately will measure the health of the business.

And what it sounds like is if you're seeing consumption grow at a 20% clip, that could be a...

Yes, you will see a convergence over time. If we can continue to have consumption grow north of 20%, you will see a convergence of ARR and net new ARR growth will start to match that.

So the other question that we had a lot is, can you help us think about the Q3 and Q4 seasonality of net new ARR relative to prior years?

Yes. So I'm glad you actually brought that up. So one of the things we shared on the earnings call was, I said, hey, I think that we'll be a little bit more weighted to Q4. And I think what people missed was the little. And so I'm certainly aware how the investor community, the sell side has modeled it. And I think the sell side has modeled it at more like 37% of your net new ARR will happen in Q3, and then 63% will happen in Q4. It will not be nearly that...

Extreme.

No. I mean last year, I think it was 48% in Q3, 52% in Q4. The year before, it was like 45% in Q3, 55% in Q4. It will probably be in between where we were in fiscal '24 and fiscal '25. So what's out there now is way too back-end loaded to Q4. It will be -- it will probably be more in the kind of 46%, 54% range.

Okay. That's helpful. Yes. It's always helpful to see when the dust settles, [ it help ].

And just to be clear that the underpinning of that was we were not demand constrained. All we did was try to effectively build some prudence into the timing of deals closing. And so the reason we wanted to orient a little bit more in Q4 was that if you have deals for Q3 that are slated to close in Q3, if it slipped or a customer decision happened in Q4, you maybe will see more of that.

The other question we had, and Noelle, you and I chatted about this before, but subscription revenue, you guided Q3, 13% to 14% in constant currency, which is a step down. I think you did 17%, I think, in Q2, on a constant currency basis. Walk us through the thought process around that? Because I think a lot of people are like, oh, is implying some like massive [ decision ].

I mean, as you probably know that in general, the model for subscription revenue is a ratable revenue recognition model. There's 2 phenomena going on with that. One, we changed the way we are accounting for ODC revenue, where ODC revenue used to be revenue that was recognized as incurred. So we had very large Q3 and Q4 ODC revenue. Now it's ratable. So you're going to have a tough compare in the second half of the year. Think of it as it's not operationally, the business is growing more in the mid-teens. And so you're going to see both in Q3 and Q4. It's not a matter of you're not fueling it enough with net new ARR. It's a matter of you got a tough compare on ODCs from the year ago period. And then I'd say, like all businesses, every now and again, you go through periods where it's handfuls of millions where you have onetime revenue adjustments. We happen to have more onetime revenue adjustments last Q3 and Q4, and so there's a little bit of a difficult compare. So if I were to simplify it, those growth rates are more in the mid-teens. So exiting fiscal '26, the business is going to be growing more in the mid-teens.

Okay. Okay. That's helpful. And then I guess the other question that we had is despite the acceleration in the business, NRR hasn't moved, which is a trailing metric. But just kind of walk us through how we should think about that. And you don't guide to it, but how don't we think about that metric progressing?

So if we're continuing to be successful with where we've been, and we continue to see net new ARR growth like we saw in the first half, and that becomes the new normal, where you're growing in the kind of the teens because call it, 65% to 70% of our net new ARR comes from expansions, the NRR metric will trend up. But I think what people don't fully appreciate is because it is a trailing 12-month metric, it doesn't move like a lot one quarter to another. So it should inflect upward over time if we continue to drive net new ARR growth. And ultimately, that number, which was stable. We actually were pretty pleased that it was stable Q1 to Q2. And I think every quarter, if we continue to see expansions the way we've seen them in the first half of the year, you'll start to see that inflect up. But again, every quarter, it will be modest. It will be like 30, 40 bps a quarter. But investors have asked me about where will I see it more your net new ARR growth, where is it going to come? Is it going to come more from expansions? Or is it going to come more from new logos? It's going to probably come more from expansions. Therefore, you'll see it more in NRR over time.

And I think that's a direct manifestation of a lot of the account rep changes that...

Our go-to-market changes were very oriented around getting deeper penetration with our existing customers. Now we don't want to lose sight of new logos, they are still important. We have a little over 4,000 customers. We target the Global 15,000. So there's a lot of room to run on capturing new logos. So they're important, but reps are focused on bookings. And they can maximize bookings. If they can maximize it through expansion of the new logos, they'll do it whatever is easiest.

So reflecting back on some of the changes that you made in terms of reallocating some of the accounts to some reps, 6 months quotas that allow you some flexibility to change. What grade would you give you guys internally on some of the execution of some of these changes? Do you feel like you've executed to sort of plan?

Absolutely. I would say that what we outlined, we have exceeded our internal expectations for execution against all those areas that -- we've seen 45% increase in our strategic account pipeline. We've seen 10 to 15 deals of over $1 million a year that we're closing in Q1 and Q2. Everything we talked about that we were making changes in last year, we're starting to see green shoots from them. They're already in the results. And the 2 6-month quotas, I think we've seen an improvement in linearity. We said that we thought that there would be an improvement in linearity because they're incented to sell all year, not just at the back end of the year.

So I think we have executed exceptionally well against all of those changes. We just got to continue to put more points on the board. One of the things I've said is we -- what I would like is we got to get to the point where it's not good quarter, not so good quarter, good quarter. We've got to build consistency where every -- and right now, we put 2 in a row. We've done Q1, Q2 of very, very healthy kind of teens growth rates. The guide for the second half does not suggest that continues. But I kind of told you that I think that that's because we're a little bit guarded in these large deals. We'll see how we do. Obviously, our internal plan is more ambitious than the guide.

Yes. Do you -- having a March year-end, you benefit from theoretically -- you get the year-end December close and then your March quarter. Historically, do you see much of the December enterprise flush?

Modest. I would say it's not huge. It's like a -- you do see that potentially, but it is. We don't plan for huge budget flush, especially with a lot of these deals that we're talking about. They're not necessarily budget flush oriented. These are C-level decisions that you're making around I actually want to do a consolidation of tools. They don't necessarily coincide with a December end decision. Usually, decisions coincide more with whatever the customer's time frame is for how quickly do they think they can actually execute against the consolidation and a transition.

Unfortunately, we got 90 seconds left, and we didn't even talk about logs. We didn't talk about DEM. We didn't talk about a lot of things. But I guess, when we sit back, I just -- I look for these opportunities because I think, ultimately, acceleration is rewarded by it. We're seeing that in a number of other software companies. When you sit here today and you think about that opportunity, and there's -- it feels like there's many, many levers that could get you there. How would you leave us thinking like around the most important -- like if we were to just look at 1 or 2 things, what are the most important...

So I would say that we -- you mentioned logs. We're rapidly approaching kind of our first milestone, which is $100 million. That is $100 million on its path to something well above that. So we are early days in logs. There is a huge opportunity for us to go and drive acceleration within logs. So I'd say logs. I think the go-to-market change we've made, they will just continue to mature that we are 18 months in, we're seeing it in the results. We're getting traction with partners that will continue to grow and mature. I think we'll see more traction in that regard. I think this focus now in the company around driving consumption with CSM teams and the strike teams, consumption ultimately will fuel expansions. And so between logs, the go-to-market changes that are -- they're not just maturing anymore. I'd say they're in place, and we're starting to see the benefit of those, combined with a recipe of driving more consumption. I think those 3 things are going to be the catalyst for growth for the company.

Yes. Well, with that, we're out of time, but really from all of us, best of luck. And we think these...

Thanks for having us.

Thanks, guys.

Greetings. Welcome to Dynatrace Fiscal Second Quarter 2026 Earnings Call. [Operator Instructions] Please note, this conference is being recorded. At this time, I'll now turn the conference over to Noelle Faris, Vice President of Investor Relations. Noelle, you may now begin

Good morning, and thank you for joining Dynatrace's Second Quarter Fiscal 2026 Earnings Conference Call. Joining me today are Rick McConnell, Chief Executive Officer; and Jim Benson, Chief Financial Officer.

Before we get started, please note that today's comments include forward-looking statements such as statements regarding revenue, earnings guidance and economic conditions. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q and annual report on Form 10-K. The forward-looking statements contained in this call represent the company's views on November 5, 2025. We assume no obligation to update these statements as a result of new information, future events or circumstances.

Unless otherwise noted, the growth rates we discussed today are year-over-year and non-GAAP, reflecting constant currency growth, and per share amounts are on a diluted basis. We will also be discussing other non-GAAP financial measures on today's call. To see reconciliations between non-GAAP, GAAP measures please refer to today's earnings press release and supplemental presentation, which are both posted in the Financial Results section of our IR website.

And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and good morning, everyone. Thank you for joining today's call. Dynatrace delivered very strong second quarter fiscal 2026 results, exceeding our guidance across every metric. ARR grew 16%, subscription revenue grew 17% and pretax free cash flow was 32% of revenue on a trailing 12-month basis. This overachievement in performance was due to successful execution of our strategy to capture the growing demand for end-to-end observability and large-scale multi-cloud tool consolidations, including ongoing growth in our logs business. Dynatrace's consistent execution gives us the confidence to raise our ARR revenue and operating income outlook for the full year. Jim will share more details about our Q2 financial performance and guidance in a moment. In the meantime, I'd like to devote my remarks to why we believe AI-powered observability is mission-critical to software reliability and performance, especially in an evolving agentic world. And I will also provide an update on our key growth drivers.

To start, the Dynatrace's platform has evolved through multiple phases from reactive operations to automated root cause now preventive operations. Our vision has been consistent over the past years, to enable a world in which software works perfectly. By definition, that means that software must always be available. And when issues do occur, the software must self-heal. Preventive operations is about anticipating and taking action on issues before they become end-user-impacting. Customers are increasingly seeking not just answers followed by manual resolution, but rather answer-driven automation to deliver and operate software that works optimally. The Dynatrace's third-generation platform was built from the ground up to handle precisely the level of complexity and scale of modern cloud and AI-native environments, including the following core elements. Grail, our massively parallel processing data lake house, is capable of analyzing billions of interconnected data points in near real time to deliver comprehensive situational awareness. Smartscape provides deep contextual insights of topology and metadata through a directed knowledge graph. Davis delivers reliable causal and predictive AI insights to produce deterministic cancers. David's Copilot automatically generates remediation proposals, and automation engine helps orchestrate and manage intelligent automated responses across the digital ecosystem.

These technologies are being part of a fully unified platform rather than a series of point products with fragmented data stores enable true end-to-end observability, which is crucial to delivering accurate analytics and recommendations. In this way, our AI-powered platform is enabling the next phase of observability for Dynatrace, which is autonomous operations.

In this business transformational phase, we take preventive operations to the next level by leveraging an ecosystem of agents, both from Dynatrace and third parties to take action to maintain software reliability, security and performance. It's about deploying intelligence that enables self-healing systems to keep software operational and performant with less human intervention. Moreover, worldwide spending on AI is forecast to be nearly $1.5 trillion in 2025 according to Gartner. As organizations broadly adopt agentic AI themselves, complexity will grow further, driving even greater need for a more scalable autonomous approach. We see Dynatrace and the evolution of observability becoming a bridge to the agentic world for enterprises.

As stated perhaps most succinctly, we see Dynatrace as the AI-powered observability platform or autonomous operations. With this evolution, Dynatrace will be able to orchestrate and supervise both internal and external AI agents to auto prevent, auto remediate and auto optimize. We believe that Dynatrace is unique in our ability to deliver such an observability environment. One of our superpowers lies in our ability to pinpoint the so-called needle in the haystack in understanding software availability and performance. This has always been Dynatrace's biggest differentiator. And organizations will only allow autonomous action if it's based on precise reliable answers, not loosely correlated data points.

We'd like to think of this as answers, not guesses. Based on this determinist acknowledge, we can then confidently conduct agentic platform-based orchestration through both Dynatrace and third-party agents to take action. In order for an autonomous approach to be effective, it has to be built on a foundation of genuine end-to-end observability that provides deep analytics and insights, ultimately enabling an automated response. Our ability to analyze all observability data types, locks, traits, metrics, really user data topology and even business events in context is essential for generating the most accurate and trustworthy answers.

Additionally, the ability to oversee all domains, including infrastructure, apps, log management, user experience, application security and business observability provides the most comprehensive perspective of an organization's IT ecosystem. Whereas metrics and logs are often the data types of choice for infrastructure management, faces a long-time strength of Dynatrace become increasingly important for end-to-end inspection of agentic systems.

Combination of full stack visibility and domain breadth allows customers to operate more efficiently, reduce overall costs and increase productivity as well as the pace of innovation. Perhaps most importantly though, we believe these elements together yield superior outcomes. And customers are rapidly extending these outcomes beyond technical analytics of software performance into true business observability.

There's also a vastly growing demand for organizations needing to observe AI-native workloads. Customers adopting agentic AI will need to understand the complex interactions among agents and know exactly what to do when something unpredictable happens, including the avoidance of hallucinations. In order to have that level of visibility, all telemetry, especially traces and logs must be captured, enriched with context and analyzed in real time at massive scale to prevent or instantly remediate issues. We are enabling AI to observe AI workloads through deep end-to-end observability.

In sum, Dynatrace is rapidly progressing toward a future where our AI-powered platform doesn't just observe, but empowers organizations through knowledge, reason and action. This is why organizations that are leading the evolution of AI are partnering with Dynatrace as a foundation for smarter, faster and more reliable IT operations.

So let me now highlight some recent developments with third parties helped bring autonomous operations to reality. Last Monday, Dynatrace and ServiceNow co-announced a multiyear strategic collaboration to advance autonomous IT operations and scale intelligent automation for joint enterprise customers. We are bringing together Dynatrace's AI-powered observability platform with ServiceNow's AI platform for business transformation to provide proactive self-healing IT environments. This partnership enables IT management and operations with real-time trustworthy autonomous actions across the software delivery life cycle.

We also announced our integration with Atlassian to help customers fully understand issues and act quickly by embedding real-time production insights directly into incident management processes. Automatically tying incidents to root cause empowers organizations to operate more efficiently and proactively in managing complex digital ecosystems.

And finally, we joined GitHub's model context protocol registry. This integration helps speed up debugging efforts during development and leverages Dynatrace observe production insights to increase agent software improvements. This also further enables us to extend left to reach cloud and AI-native development and platform engineering teams.

I'd like to turn next to an update on 4 key growth drivers for our business, all of which continue to trend positively. First is the massive opportunity that we continue to see in log management. We believe the logs market remains ripe for disruption given the rising cost of legacy solutions that offer little to no expansion in business value. As we have stated in the past, we have taken a very different approach to logs. Traditionally, logs were separated from other observability data types. Instead, Dynatrace provides a unified data model inclusive of logs, allowing for cross data analytics without manual stitching, resulting in faster root cause analysis and more accurate observability insights. Log management is our fastest-growing product category and is rapidly approaching $100 million in annualized consumption, continuing to grow more than 100% year-over-year.

In addition, as more customers look to migrate their existing logs of Dynatrace, we're investing to increase the speed of those migrations. Last month, we announced a partnership with Crest Data Systems to deliver a seamless automated migration experience for customers moving to the Dynatrace platform. It's enabled us, for example, to meet an aggressive time line for a global financial services company by automating 70% of their dashboard migrations. Second, the investments we made last year to align our sales coverage around strategic accounts, pipeline and partners continue to pay off. Our fourth quarter pipeline for strategic accounts is up 45% versus last year. Bookings through strategic GSI partners double year-over-year. And we saw a 53% increase in Q2 ACV from 7-figure deals compared to last year. Here are just a few examples of large wins in the quarter. An AI-native revenue intelligence company and new logo selected Dynatrace to be their end-to-end business solution for mission-critical workloads, displacing multiple tools. Our biggest new logo deal in APAC is one of Japan's largest banks. Fragmented tools and the complexity of their architecture were making it difficult for them to reduce mean time to resolution. With Dynatrace, it will now have an end-to-end view of their ecosystem to resolve issues more quickly.

A major U.S. airline expanded its existing relationship with us 18 months after adopting Dynatrace to further consolidate tools, including logs after seeing significant improvement in incident resolution and the benefits of end-to-end observability.

A third growth driver is the Dynatrace platform subscription licensing model, or DPS. We reached a major milestone in the second quarter with 50% of our customers and 70% of our ARR now utilizing DPS. When we launched DPS over 2 years ago, our expectation was that customers with full access to the platform would leverage more capabilities and extend Dynatrace more broadly into their IT environment. This thesis has played out, with DPS customers adopting 2x the number of capabilities and it nearly doubled the consumption growth rates of those on a SKU-based model.

And finally, overall platform consumption is a strong indicator of future expansions and is the primary compensation metric for our customer success team. Total Q2 consumption growth was more than 20% and continues to outpace subscription revenue growth.

To wrap up, we are pleased to have delivered a strong first half of the fiscal year. The observability market opportunity is more critical than ever given the rapid evolution of cloud and AI native workloads. We have a differentiated AI-powered platform that is enabling autonomous operations in an evolving agentic AI world. We deliver significant customer value driving accelerating platform consumption. We continue to see momentum in our core growth drivers. And we have a compelling business model which has enabled us to deliver a sustained balance of growth and profitability. Jim, over to you.

Thank you, Rick, and good morning, everyone. Q2 was an excellent quarter across the board. We surpassed the high end of our top line growth and profitability guidance metrics once again. As Rick mentioned, this strong performance was driven primarily by our ability to capture the growing demand from enterprise customers for end-to-end observability and large-scale tool consolidations. Among many highlights, we continue to demonstrate traction in key growth areas. This includes momentum in large deal activity and pipeline, accelerating consumption and adoption across the platform, notable strength in logs, continued adoption of DPS and a growing number of early expansions, including several 7-figure deals in the second quarter.

Additionally, our partner ecosystem is maturing with growing traction across GSIs, hyperscaler and strategic partnerships.

Let's review the second quarter results in more detail. Annual recurring revenue, or ARR, ended the quarter at $1.9 billion, representing 16% growth, consistent with Q1. Q2 net new ARR on a constant currency basis was $70 million, up 16% from a year ago, driven by both strong expansion and new logo bookings across the geographies. Execution was particularly strong in North America and Asia Pacific, with many deals influencing driven by our GSI partners. For the first half of the year, net new ARR was up 14% from a strong first half last year.

In Q2, we added 139 new logos to the Dynatrace platform with an average ARR per new logo of over $140,000 on a trailing 12-month basis. We continue to target landing with high-quality new logos that have a higher propensity to expand. The average land size in Q2 was particularly robust with the new logo ARR growing well over 30% year-over-year. We continued to see accelerating consumption and adoption of the platform with our average ARR per customer over $450,000, highlighting the criticality and business value we provide to customers.

The strategic relevance of the Dynatrace platform is further reflected in our gross retention rate, which remained in the mid-90s. Net retention rate, or NRR, was 111% in the second quarter, in line with the prior quarter. As Rick mentioned, our DPS licensing model continues to gain traction, achieving a major milestone with 50% of our customer base and 70% of our ARR now on this vehicle at the end of Q2. DPS has become our de facto contracting model.

With access to the full platform, customers are adopting Dynatrace more broadly across their IT environments, resulting in increased consumption.

Turning quickly to usage volumes on the platform. Q2 was another quarter of robust consumption of the platform, with the annualized consumption dollar growth rate accelerating and continues to track north of 20%. Further, DPS customers continue to consume at nearly 2x the growth rate and leverage 2x the number of capabilities compared to SKU-based customers. Contributing to that consumption rate, lags remains the fastest-growing product category growing well over 100% year-over-year and rapidly approaching our $100 million milestone. We believe there is plenty of momentum in runway into Half 2 and beyond.

Increased consumption on the Dynatrace platform can sometimes accelerate usage above a customer's original DPS annual commitment, resulting in either ODC revenue or an early expansion opportunity. The decision to consume on-demand or renew early is customer-dependent and will vary based on that quarter's customer cohort behavior and influenced by the remaining duration of their contract. In Q2, we saw more DPS customers expand early versus going on demand and contributing to our strong net new ARR result. ODC revenue came in at $7 million for the quarter, just shy of our expectations. The key takeaway, however, is that the company's emphasis on driving platform adoption and consumption serves as the foundational growth engine, whether it's fueling ODC revenue or supporting early expansion of net new ARR, both contribute to subscription revenue with ODC reflected immediately in ARR over time.

Moving on to revenue. Total revenue for Q2 was $494 million, and subscription revenue was $473 million, both up 17% and exceeding the high end of guidance by nearly 100 basis points, driven by strong net new ARR bookings.

Turning to profitability. Non-GAAP operating margin was 31%, exceeding the top end of guidance by 150 basis points, driven mostly by revenue upside flowing through to the bottom line. Non-GAAP net income was $133 million or $0.44 per diluted share, $0.03 above the high end of our guidance.

We generated $28 million of free cash flow in the second quarter. Due to seasonality and variability in billings quarter-to-quarter, we believe it is best to view free cash flow over a trailing 12-month period. On a trailing 12-month basis, free cash flow was $473 million or 26% of revenue. As a reminder, this includes a nearly 700-basis-point impact related to cash taxes.

Pretax free cash flow on a trailing 12-month basis was 32% of revenue.

Finally, a brief update on our $500 million opportunistic share repurchase program. In Q2, we repurchased 994,000 shares for $50 million at an average share price of just over $50. Since the inception of the program in May 2024 through September 30, 2025, we have repurchased 5.3 million shares for $268 million at an average share price of just over $50.

Moving now to guidance. Our conviction and growth drivers continues to strengthen, fueled by secular tailwinds of vendor consolidation, cloud modernization and AI workload proliferation. Our go-to-market momentum and funnel of large anchor deals continues to grow with the pipeline of strategic enterprise ACV, up 45% year-over-year. Consumption growth continues to significantly outpace ARR growth, driven by customer adoption of DPS, leading to broader upsell and cross-sell penetration. Log Management continues to be a significant source of growth both in our installed base and with new logos. We are balancing these leading growth indicators and our strength in the first half of the year with a prudent approach for the second half with 2 primary factors in mind. First, the weighting of the pipeline towards larger, more strategic tool consolidation opportunities often creates increased timing variability and longer duration to close. Second, while observability demand remains resilient, the macro and geopolitical environment, particularly in EMEA remains dynamic. And with that as context, let me summarize our updated full year outlook.

The underlying strength in consumption growth, coupled with the strong first half performance, gives us the confidence to raise our full year ARR growth guidance by 100 basis points at the midpoint to 14% to 15% growth in constant currency. Seasonally, we expect net new ARR to be weighted more towards Q4 than last fiscal year due to the mix and timing variability of large deals in the funnel.

Moving now to revenue. We are raising our total revenue and subscription revenue growth guidance by 75 basis points at the midpoint to a range of 15% to 15.5% growth in constant currency. Given the Half 1 mix shift towards early expansions and ARR, we now expect OTC revenue to be in the low 30s.

Turning to our bottom line. We are raising our full year non-GAAP operating income guidance by $8 million, translating to a non-GAAP operating margin of 29%. We expect free cash flow margin of 26%. While we do not guide to free cash flow on a quarterly basis, we anticipate free cash flow to be more weighted to Q4 than historical levels.

Finally, we are raising non-GAAP EPS guidance to a range of $1.62 to $1.64 per diluted share, representing an increase of $0.04 at the midpoint of the range. This non-GAAP EPS is based on an expected diluted share count of 307 million to 308 million shares. Looking to Q3, we expect total revenue to be between $503 million and $508 million. Subscription revenue is expected to be between $481 million and $486 million. As a reminder, we saw a notable increase in OTC revenue in Q3 and Q4 of last year. And with the revision to estimated ratable RevRec treatment this year, this will result in a headwind to revenue growth rates in our third and fourth quarters this year.

From a profit standpoint, non-GAAP income from operations is expected to be between $143 million and $148 million or 28.5% to 29% of revenue.

Lastly, non-GAAP EPS is expected to be $0.40 to $0.42 per diluted share.

In summary, we are very pleased with our Q2 performance and strong momentum in the first half of the year. The strategic adjustments and investments we made last year in our go-to-market strategy are taking hold and evidenced in the latest results. We're starting to see momentum in large deal activity in pipeline, accelerating consumption growth across the platform, ongoing traction in logs, broader DPS adoption and a maturing of our strategic partner ecosystem. We have a proven track record of consistent execution and delivering a balance of strong top line growth and profitability.

While we're maintaining a prudent approach to our near-term outlook, we're confident in the foundational elements driving growth in fiscal 2026 and remain committed to investing in initiatives that we believe will generate long-term value.

And with that, we will open the line for questions. Operator?

[Operator Instructions] And our first question comes from the line of Fatima Boolani with Citi.

Jim, I was hoping you could spend a little bit of time on the net retention rate metric. And if you could help peel back the onion so to speak on some of the puts and takes there. And really, the spirit of the question is, why is the metric lagging in contrast to otherwise very favorable momentum that you have shared in your prepared remarks on renewals, on expansion, on accelerating customer growth as well as signs that you're seeing that customers are now expanding earlier? So just wanted to get maybe more granular understanding on why net retention rate, it looks like it's stuck in the mud when all other factors in the business are pointing to more favorable momentum?

It's -- happy to take that, [indiscernible]. I'd start with -- we had a really strong net new ARR quarter. It grew 16% for the quarter, and it grew 14% for the half. So the business momentum is quite healthy in growing net new ARR. I think you know NRR is a kind of a trailing 12-month metric. And so it's going to take multiple quarters to significantly move NRR as a metric. So NRR stabilized Q1 to Q2. So we feel really good. I mean, 1 of the things we talked about in the prepared remarks is we're getting really good traction with the go-to-market changes that we made a year ago. It's showing up in the results. It's showing up in growing pipeline. We are poised to benefit from continued end-to-end observability tool consolidation opportunities. Consumption continues to grow at rapid pace. So we're very optimistic about the underpinnings of the business.

These metrics, NRR, if we continue to see the performance that we are seeing in consumption in these other areas, you will start to see movement in NRR, but it will happen over time.

Our next question comes from the line of Matt Hedberg with RBC Capital Markets.

Congrats on the strong quarter and increased guide. I had a question. You guys have spent a lot of time focused on go-to-market improvements really over the last several years, and it really feels like it's paying dividends right now in terms of large deals. I'm curious, when you think about sort of some of the capacity adds that you've added historically, could you talk to the level of productivity you're seeing there? And secondarily, with a strong Q2, I'm curious to see if the 6-month quotas are doing what was intended, sort of improving linearity for the year?

Happy to take that, Matt. It's actually 2 very good questions. So you're absolutely right. We've been building on these go-to-market changes since basically Q1 of fiscal '25. And as you know, we talked about that we were making investments in the top of the pyramid where we had, on average, roughly 8 to 10 accounts per rep with very large customers. We made investments there to lower that to 4 to 5. We're seeing it in close rates. We're seeing it in pipeline. So yes, we are seeing a productivity lift from the investments that we made there. So we're very, very pleased with that.

I'd say relative to the 2 6-month quotas, just to remind you, we did that for 2 reasons. One, give you an opportunity if you want to make a midyear adjustments either a little bit on go-to-market or even on maybe compensation plan design; and two, it also gives you an opportunity to improve on the seasonality of bookings. And so we saw a little bit of that last year, where it's our second year of going through it. So I think it's actually bearing out what we thought, which is it's showing an improvement in linearity of the business. And so this is not a matter of, hey, there was a lot of pull-ins from Q3 per se, but I just think there's an incentive for the sales organization twice a year to be in accelerators. And I think that's what you saw. So I'd say both things are playing out as we were hoping.

The next question is from the line of Brad Reback with Stifel.

Great. Rick, you alluded to the over 20% consumption growth in the base, so either for you or Jim, how should we think about the convergence of net new ARR and subscription revenue growth towards that 20%? What are the puts and takes as we look out over the next year or 2?

So Brad, I'd say the puts and takes are, we are -- as you know, we are a ratable revenue recognition business. So we -- when we book something, the subscription revenue gets amortized ratably. And so we are not a business that has revenue recognition on a consumption basis. If we were, these growth rates that we're talking about for consumption for the company would be in the 20s. So it does take time. You have to put more 20-plus percent growth rates. Obviously, there's an element of your contract terms in your contract terms and burning through commitments and going through expansions. And so it won't happen overnight. It will happen over time. So there will be a convergence. I think the important thing for investors to watch for is us continuing to give you an update on how is consumption tracking. Consumption ultimately, other than bringing in a new logo, consumption is the underpinning for sales to go in and upsell a customer, and we're seeing it play out. We're seeing it play out with early expansions. And as examples, clearly that with DPS, they're able to trial different things on the platform logs notably.

And if you try a logs, you're under EPS contract, you had a very large global airline that we had a very big contract with that we just booked maybe 1.5 years ago for a 5-year deal. This customer did a huge expansion because they trialed a product category that was not really part of their initial configuration. And now you have a huge upsell literally 2 years into a 5-year deal. And so the more you look at consumption and the more we focus on kind of getting our teams aligned on consumption, whether they be the CSM teams or strike teams for logs or [indiscernible] or security, that ultimately is going to be the underpinning you'll see over time a convergence of those growth rates with subs growth and ARR growth.

I might just add, Brad, that while we don't recognize revenue based on consumption, it absolutely is a key leading indicator. The thought process is quite simply that we want consumption to be growing faster than ARR because it is an opportunity then to utilize fully DPS contracts as we use those contracts then renewals and expansions occur thereafter. So it is the metric of choice for our customer success organization and is where we are pressing the organization to essentially affirm our performance for customers.

Next question is from the line of Eric Heath with KeyBanc Capital Markets.

Maybe just a clarification, Rick and Jim, just given the focus on consumption and that's accelerating, I mean should consumption be the key metric that we focus on over ARR and subscription revenue as an indicator for future acceleration looking into fiscal '27? And then just curious on logs and how that contributed to the $1 million ACV deals you did in the quarter.

So I'll take that. So we have a handful of metrics. What's my favorite metric? We have a handful of them. So I would not say it's 1 metric. Certainly, ARR is very important. But ultimately, you need to get your go-to-market motion going, bring customers on the platform once they get on the platform, have your customer success and strike teams drive more adoption. So ultimately, the underpinning I would say, of growth will be consumption. So I do think it's something we're going to continue to want to talk to you about because that is something -- it doesn't show up, like it is not a metric that we -- you see in the financial results. It's not a subs revenue, it's not ARR or anything like that, but it ultimately fuels an expansion.

And so it is an important metric to focus on. It's not the only one. There's other metrics, obviously, that we share. And I think your other question was on logs, and we are rapidly, and I say rapidly, very rapidly approaching $100 million. It is by far the fastest-growing product category that we've seen a doubling of customers from a year ago that now spend over $1 million with us. We've almost seen a 4x increase in customers that spend over $500,000 a year with us. And we have a lot of customers now that are still under $100,000 that we have a huge opportunity to continue to expand with. So we're very, very happy with the progress we're making in logs.

Yes. Just to add on to the logs piece, growing more than -- well more than 100% year-over-year on now what is getting to be a much larger number, as Jim said, approaching $100 million in consumption. And it is really key to emphasize what we said in the earlier remarks that not only are we saving customers a fair bit of money for legacy solutions what they're doing today, but by incorporating logs into the overall observability mix and framework, we are delivering markedly better outcomes. Because you have low traces metrics, really user data all in the same data lake house, it results in better outcomes. And that's what we're seeing across the board for the customers that have deployed at scale.

Our next question is from the line of Mark Murphy with JPMorgan.

This is Noah Herman on for Mark Murphy from JPMorgan. The constant currency net new ARR results really stood out positively this quarter. Based on the guidance framework, it seems like seasonality between the first half and second half of the year is more equally weighted, whereas in prior years, it seems more like a 40-60 split? So can you just maybe unpack that a little bit, the seasonality dynamics we should expect going forward?

Yes, that's a good question. I mean, you're right. We've historically seen more like 40-60 or 42-58. I think it was Matt that asked earlier around our 2 6-month plan designs. I do believe with these plan designs, you will -- I don't think you're going to necessarily always have balance between the first half and the second half. But I think you're going to get closer to that because there's an incentive of the sales organization to improve linearity. We're actually seeing that. I would also say, to be fair, as I said in my opening remarks, we are not demand constrained. So the pipeline is extremely healthy. This is the -- I think, the fifth consecutive quarter of an acceleration in our kind of 4-quarter rolling pipeline. So pipeline trends and the demand environment is quite healthy.

I think what we've done for the back half of the year is we built some prudence into the back half of the year because as we have focused more on large, high propensity to spend customers, the good news is we're seeing a significant improvement in the pipeline, but that is also coming with very large deals and very large deal sizes. So the timing variability for those deals is difficult to judge. And so we've appropriately built some prudence into the back half of the year that maybe deals fall out of kind of the back half maybe into the first half of fiscal '27.

This is similar to what we talked about maybe a year ago. And I would say the pipeline is even more weighted to large deals. So we're very pleased with the pipeline. I think we just built some prudence. So we'll have to see how we execute. But I'd say I'm very optimistic with the kind of the overall go-to-market improvements we've made and the pipeline that we're seeing across the business.

Our next question is from the line of Patrick Colville with Scotiabank.

Rick and Jim I guess when I think about the big macro trends in IT right now, it's accelerated public cloud migrations. It's an increased trend of multi-cloud AI. All these trends, in my opinion, should play well into the Dynatrace story? If I look at results this year, net new ARR constant currency this year versus the back half of last year, we're in a much better spot. So I guess, as it relates to these kind of macro trends, are we seeing -- have we passed an inflection point for Dynatrace to really kind of ride this title wave of those macro trends? Or is this a case of these net new IRR has been -- has whipped around in the past and you don't over-index on these last 2 quarters?

Yes. I guess what I would say is kind of some of the remarks I just made, which is the demand environment is very healthy. So to your point about macro trends. I think we're seeing that play out in what is a significant increase in the overall pipeline and pipeline health of the business. So I'd kind of anchor you on that. And I'd answer you on we had a very strong Q2, a very strong first half. Is this, hey, we don't think it's going to be as good in the back half, that's -- I don't want that to be a takeaway relative to this guide. I think we've built some prudence into the fact that as more deals become larger, that we just built some timing variability to this. And we'll see how we progress in the back half of the year. But it is -- I don't think it's a demand environment element. I think the demand environment is quite healthy. And I think we are poised to benefit from that. We just built some prudence into the execution of these large deals.

Yes, Patrick, I would say a very strong first half, a solid increase in the guide. We've provided some of the metrics that are leading indicators for us, elements like strategic account pipeline up 45% year-over-year, large deals from the first half up 53% year-over-year. I think these are all good indicators that are corroborating the evidence that we're seeing in what's happening in the hyperscale results and the ongoing demand for cloud and AI native workloads.

Our next question is from the line of Jacob Roberge with William Blair.

And congrats on the solid results. You talked about building some prudence in the back half just related to those large deals that you have in the pipeline. Can you talk about what some of the learnings have been from the past 2 years on these larger platform deals and whether you're starting to see an improvement in win rates and close rates as you've been able to kind of tweak and adjust the model?

It's a very good question. I mean, obviously, every year is going to be a little bit different. I think when we started, Jake, I want to say this might have been in Q4 of fiscal '24, where we began to see this emergence, and we didn't call it a trend. We said it is emergence of very large deals with customers that were considering vendor consolidation. And if you recall, we kind of rolled the table in that quarter. We actually -- we had an unbelievable close. I'd say we had a really strong close last Q4. And I'd say what was an emerging trend became kind of a continued trend. And I'd say this is the momentum, the sales plays that we have, this has been the #1 sales play for the company. And it's the #1 sales because ultimately, that's what customers are looking for. Customers are looking for someone that they can consolidate what are the disparate set of tools. So I think we're learning that this trend is real. I think our sales force is well equipped. I think the company is well equipped to benefit from this. And I'd say our win rates are quite high because I think we have a very compelling proposition. So I think we're in a good place.

I think it's just a matter of you got the timing variability of these things varies because of the size of these deals. And so you have to go through a kind of extra level of approval. And so I'm optimistic of our chances and our win rates, but we're just building some caution just since the timing.

Jake, I would say at a very tactical level, the interest that we see from CXOs of major organizations around the globe is increasing at a very rapid rate. I have literally done dozens and dozens of CXO meetings around the globe over the prior 3 months. The interest and mission criticality of observability has never been higher in my observation. So that continues to drive things.

And what I would say is they're all interested in 1 or more of 3 things. They're interested in end-to-end observability, which is driving tool consolidation opportunity for more efficiency, better outcomes, lower cost. Secondly, they're interested in AI observability and deploying observability for AI workloads. And thirdly, they're interested in business observability, extending observability overall to include business events that give them a better handle on the business well beyond what's just happening technically in their software stack. And these are core themes that really have evolved, I think, over the prior year.

Our next question is from the line of Matthew Martino with Goldman Sachs.

Great to see the momentum in the business. Rick, you highlighted an AI-native win in your prepared remarks. Can you share a bit more on what attracted this customer to the Dynatrace platform. And are you starting to see more potential opportunities within the AI space, if you contextualize that for us?

Yes, it's a great question. So let me sort of parse it into a couple of components. First, you have the companies that are our typical customers that are deploying AI workloads. Those customers we have in the hundreds already. They're deploying AI workloads using Dynatrace to provide observability. What you're getting at a little bit are the AI native companies that have developed against AI workloads. And that is where that is evolving rapidly. We are now deeply embedding with AWS services like Bedrock, Azure services like OpenAI Foundry, Google services like Vertex, NVIDIA's AI infrastructure, et cetera. We are targeting more with our third-gen platform developer capabilities and this is expanding interest in Dynatrace. And overall, what they're most interested in is getting deterministic answers that enable agentic action. And this is what I talked about earlier in the prepared remarks, but you cannot take action in an agentic world if you don't trust the underlying answers. And so this is where we say answers, not guesses. You have to know what the answers are in order to be able to take action. And I think this is what is increasingly attracting AI-native companies to Dynatrace because that is foundational in how they need to operate the businesses autonomously as they look forward.

Our next question is from the line of Ittai Kidron with Oppenheimer.

And these results, guys. Couple of small ones for me. First of all, Rick, do you have a point of view, clearly, you're making very good progress with DPS adoption, 50% customers, 70% of ARR. But you have perhaps an updated point of view on where those metrics could peak you guys, number one? And number two, when you look at the capability uptake and expansion of non-DPS customers, is there a deterioration in depth, not only because customers are doing less, but because the remaining cohort are, by definition, less and less attracted to the value proposition for whatever reason that you're selling?

Yes, I'll take that. So I think what we said before relative to like where do we think ultimately it will go as far as DPS penetration. And there are certain industries that DPS is problematic, and that's in like government industries that they have to actually buy finite [indiscernible]. So we're working to see if there's a way to work around that. But I would say what we've said is that we think that we should be able to get 80% to 85% of our business on to a DPS contract.

Now if we can remove some of those barriers that I mentioned, you could go even higher. But think of it as we kind of said 80% to 85% of our business. And I don't think there's any barriers relative to customers that are on SKU to DPS. One of the things that we've done to remember is we have been focusing on customers that have been going through new customers won 80-plus percent of them go to DPS. And for renewals, we were only focused on moving customers on a renewal to DPS if they were doing an expansion. So if you were doing a like-for-like renewal, we were not moving it to DPS because we did not want to introduce friction into the process.

We have adjusted that effective this half that we are now going to be -- for customers that are even going through a like-for-like renewal, we were having teams of people that have got to help in what I would say affordability of customers moving more to DTS. And so I think you're going to continue to see progress. I think we're going to have -- there's going to be a longer tail here between the 70% that we're at now in the 80% to 85%. But again, all the proof points that we talked about, you get them on DPS, they can trial anything on the platform. We've proven that they have 2x the consumption growth rates. They have 2x the number of capabilities that they had, and they have much, much higher NRR. So there's a good value proposition to continue to move them. And I think we're focused on all the right things.

Our next question comes from the line of Ryan MacWilliams with Wells Fargo.

I believe you mentioned more early DPS customer renewals in your remarks. I'd love to hear more color if early renewals of DPS customers are impacting the 3Q subscription revenue guide and the OTC guide as well? We'll just hear about those dynamics.

Yes, you're right. You picked up on -- Q2 was a quarter where, again, very strong net new ARR quarter. And I'd say a big piece of that is we did see customers that were on a DPS contract that renewed early. I mentioned a large global airline. They were one, we had many of them. And again, you go back to consumption. You get them on the platform, you get teams working with them on driving adoption and consumption and ultimately, good things will happen. And that's what we're seeing. And you're right, there is a dynamic between whether a customer does an early expansion or whether they maybe go on demand, we can't really influence that at the end of the day. What I will say is we did make some compensation changes for our sales force in fiscal '26 where they get paid more for an ARR generating expansion than they do for an OTC.

And so I think, inherently, they're more incented to drive an expansion. So our expectation is, I think that motion will continue. I think we're getting in front of it with customers earlier when they're running hot on their consumption and trying to see if we can put something that's compelling for them and give them better unit price if they increase their volumes, and you're starting to see that play out, and I expect that will continue.

The next question is from the line of Sanjit Singh with Morgan Stanley.

Congrats on the 16% constant currency net ARR growth. I had a 2-parter and I apologize for it, but sort of around the same topic. Because was wondering if you could sort of sort of unpack the strategic collaboration with ServiceNow? And what's your hopes for that relationship over the next year from a commercial perspective? And then secondly, more broadly, when we think about making that evolution to that more proactive self-healing type system, when you think about capabilities around ITSM, which you're partnering with the leaders there, but also when you think of like, okay, if we need to drive code fixes, how do you think about sort of the DevOps platform? Is that another area for partnership or a potential further organic expansion of the Dynatrace platform?

Thanks, Sanjit. I'll take those. So first, on the ServiceNow partnership, we are delighted with that strategic collaboration that we announced a couple of weeks ago. You can think about it as ServiceNow connecting and automating workflows, we then, as Dynatrace, provide the precise answers to inform those workflows. So it really is an incredible opportunity. Even over the past couple of weeks, I've met with, I don't know, half a dozen customers. Every single one of them mentioned the ServiceNow relationship with Dynatrace and wanting to leverage it to better connect our solutions. We do loosely coupled connections today, but this collaboration with ServiceNow enables us to really engage much more deeply on the product side to provide a much better experience for joint customers. And there's a huge overlap in our customer base with ServiceNow customers. So that's point number one.

We are also pleased that as part of that announcement, we're deploying ServiceNow, ServiceNow is deploying Dynatrace for digital -- or some of their digital operations. So that makes us essentially customer zero for -- on both sides for these integrations. So we think that, that will be a wonderful proof point to customers as to how to best use these technologies together in a very symbiotic way. So that's on the ServiceNow side as.

We look at sort of more proactive integrations around code and others, we talked about GitHub. We talked about Atlassian. Our view of the world is quite simply that we have the answers that are trustworthy and precise. We will enable those answers to become exposed through a series of APIs, whether through an MCP server or otherwise, who are either Dynatrace agents or third-party agents in the ecosystem, be they through Asian GitHub, hyperscaler, ServiceNow to then take action as appropriate to then deliver autonomous operations. And that is precisely what the evolution is that we're seeing in observability, 1 from reactive to proactive, to predictive, to now autonomous. And this is our vision. This is the directional adding of observability, and this is where we can really deliver for customer software that as per our vision, works perfectly.

The next question is from the line of Howard Ma with Guggenheim Securities.

And I want to extend my congratulations on a strong quarter as well. My question is, do you think the sales comp change to incent ARR over on-demand consumption, is that the primary reason for customers opting to early renew? And is it the primary reason for the lower ODC expectations in the back half? And on a related note, are the expansions tied to the early renewals above your expectations?

So it's tough to gauge whether compensation is the only driver. I certainly -- compensation does drive behavior. But at the end of the day, the customer has to be willing. And so I think what we're -- now that we're a year into this, I think we're much more proactive with customers and understanding what's going on within their environments from a consumption perspective. So I think it's a good thing that the sales organization is very tightly coupled with the customer around how their consumption is driving. And working with them is there a win-win where we can extend our business with them and give them more favorable unit pricing as a result of that. And so I think it's -- yes, compensation probably does drive some of behavior, but I also think that ultimately, it's much more proactive with customers in their journey and their life cycle around what they're doing around observability.

I mentioned logs being an area, new areas, new use cases, sales is looking for those things and doing an early expansion helps with that. And whether or not it exceeded our expectations, the answer to that is yes. We absolutely exceeded our expectations that we are -- we've seen more of that than we even expected.

Our final question comes from the line of Andrew Sherman with TD Cowen.

One for Jim, how would you compare and contrast your visibility now versus a year ago, given where you've come with the go-to-market changes? Do you have a better visibility? Sounds like certainly better sales execution and close rates? Anything else we should consider as we look into the second half?

That's a great question. I would say visibility and confidence is greater now than it was a year ago. A year ago, we were kind of adding a lot of sales reps. We were kind of changing a bunch of things. We were maturing that process, and we were beginning to see the evidence of that at this time last year. We're 1.5 years into it now. I think we are well established. I think the -- our geographies are performing at a very high level. I think our visibility and focus on growing pipeline and seeing that pipeline close is better than ever. Having said that, going back to my point around when you have large deals like this, you factor in, what is the -- your timing certainty. So I feel really good. I think we have good visibility. We have good conviction that we're going to have a good back half to the year. We'll let us see how it plays out.

All right. Well, thank you all for your engaged questions and ongoing support as always. [indiscernible], we delivered a strong first half of the fiscal year, and we are confident in the foundational elements underpinning our growth. We look forward to connecting with you all at IR events over the coming months, and we wish you all a very good day. Thanks for joining.

Ladies and gentlemen, thank you for your participation. This does conclude today's teleconference. You may now disconnect your lines, and have a wonderful day.

It's day 3 of Goldman Sachs Communacopia and Technology Conference. It's day 3, but year 4 of this rebranded converged conference, and it's been a fantastic success. And Rick has been a part of the conference from the version 1.0, version 2.0, 3.0, 4.0, here we are. Thank you for your support. Thank you to our clients. It's really heartwarming to see people from all over the world. I mean people from Australia, Asia Pacific, Europe, Canada. So all over -- thank you for your continued support of the platform. Real delight to welcome you back. And I think we met when you first made CEO of Dynatrace, you joined the company.

4 years ago.

4 years ago, I still remember that we're all wearing our COVID masks, and we had to get certified to -- tested to be part of the meeting. I still remember vividly that very first meeting, very memorable. Boy, you've come a long way and the company has come a long way.

We have.

This has been tremendous story over the last few years. So...

Yes, sub-$1 billion of ARR when I joined, now approaching $2 billion. So we've made good progress over this period, and we're in a great market.

Great. So can you recap for us kind of the big milestones that you've accomplished in the last 3 years? And then cast for us a picture of what Dynatrace looks like in the next 4 to 5 years.

Is this the one question you're going to ask for the next 30 minutes that I can. You get [Technical Difficulty] -- the whole meeting. That's a pretty open-ended one.

Yes. So last year, I'll give you an example that our CEO interviewed the CEO of Salesforce and we had a lot of questions. Presumably, we asked one question and Mark took 25 minutes. Well that was all about...

I'll try not to do that.

You are welcome to do it. It's okay.

The -- probably the best way to answer this, I would say, are the reasons that I joined Dynatrace 4 years ago are very consistent with the reasons that exist today to be investing in Dynatrace and the reason that I'm so excited to be part of it. The first is the observability market is very strong. And in a world that is increasingly cloud-based, that is driven by AI workloads and beyond, the need for observability capabilities and observability functionality are increasing, not decreasing.

It is becoming more complex to manage the huge amount of data and rapid increasing complexity of that data manually. So you just have to have automated tools, automated capabilities that enable you to do that and ever more in an AI world. So market is clearly a core driver.

And number two, incredible customer base that we have. These are the biggest of the big companies around the globe. I have just completed a 2.5 or so month roadshow through 7 countries on 3 continents and the feedback from our customers in terms of the value that Dynatrace is delivering is just overwhelming. So that's an incredible factor.

Our platform is absolutely ready for prime time. It is really, I believe, being constructed as an extraordinary platform to provide an AI lens that hasn't existed for 2 years, but really more than a decade into an integrated unified data set. And that data set by being fully integrated in a single data lake house provides exceptional value add in delivering an end-to-end observability experience.

And finally, from a financial perspective, it's a very durable financial model, 19% subscription revenue growth last quarter, 33% pretax free cash flow. If you add those 2 numbers together, operating at roughly a Rule of 50. We've operated consistently in that sort of range. And so the combination of those, I think, 3 or 4 factors are what we've really leaned into over these past years to really go generate the business that we have. And we see all of those 4 factors as really being drivers for the years to come. And if anything, it's accelerating, not decelerating.

As you look at the road ahead, how do you see the business positioned in light of a market that is not quite consolidated, although I have to say that we're starting to see some signs of stabilization in your business and other companies' businesses, the market is still kind of a little fragmented. And it's confusing for me, at least maybe it's not confusing for clients as to where it is that Dynatrace plays, where it does the company XYZ plays.

Can you lay out for us how you view your addressable market and how you see the company's opportunities 4 to 5 years out? And how does this market look like at some point when you're done sorting out APM versus search versus observability versus infrastructure monitoring? It's like a lot of things that are going on in that. Who wins?

If you look at the Gartner Magic Quadrant or the GigaOm Radar or Forrester Wave as a few external lenses, the good news is Dynatrace is in the prototypical upper right quadrant of all of them. And it is due to the strength of the platform and the capabilities that I described. The real opportunity, I think, as we look ahead that is really going to separate companies further is really an evolution of observability, and I would say, 3 dimensions. And these are 3 dimensions that I've just heard over and over and over again from customers really over the last few months of my ability to meet with CXOs globally.

The first evolution is toward end-to-end observability. And end-to-end observability really means a consolidation of tools and an integration of these capabilities in a single overall solution or if not a single solution, then certainly a radical reduction from 15 observability tools to 2 or 3 or something like that. And we, at Dynatrace, certainly have been a consolidator in this arena.

And end-to-end observability really includes a few different levels. One level is the data level, integrating logs, traces, metrics, real user data, behavioral analytics, all of the fundamental core observability data types in one data store, one data lake house. And really, only Dynatrace does this.

If you look at any of our competitors, they're using fragmented data stores, they're manually tagging data. And when data flows increase in size and complexity, it becomes impossible to manage that. The second layer of end-to-end observability is really around domains. It's applications, infrastructure, log management, real users, all using the same lens to the same data.

And then third and finally is personas. You want not only IT ops, but developers, SRE, platform engineering, you want all of these groups to have access to the same underlying data store so that they can then provide similar answers, similar insights. And if you really do end-to-end observability right, you get two enormous benefits. One, you get better answers, better outcomes. Something goes wrong, you're able to fix it more rapidly based on better insights, more tuned to resolving the problems that you've got. And the second thing is usually it comes with a 20% or 30% cost reduction, which large enterprises like as well. So end-to-end observability is one pillar.

Second pillar is AI observability. This is both using AI to deliver better answers as well as being used or being able to be utilized for AI workloads, which are expanding quite rapidly as well. And we may come back to this if you take us there, Kash, but this really gets us into tell us about Agentic observability and Agentic AI observability, what does that look like? And why does Dynatrace potentially win in that environment.

And then third and finally is around business observability, which is that increasingly, organizations are looking to us not just to say, is my software working and is operational, is it performant, but tell me how my business is operating? Financial services are telling me, I want to know how long it takes to make payments? Is it working better than yesterday or worse than yesterday? Airlines are asking us to help them build control towers that define how long does it take a bag to get from the plane to the carousel? And is that doing better or worse than yesterday?

Cruise lines are wanting to know what the customer experience is based on whether you could get in your state room consistently or could I find you onboard ship. Retailers, on and on and on, business observability is becoming core based on business events and business evolution. So end-to-end observability, AI observability, business observability, I would say these 3 categories are really separating the competitive environment and especially when you look at overall company size and complexity and extraordinary volumes of data, that is where Dynatrace most differentiates from others in our space.

Rick, how far along are we in this sort of end-to-end observability sort of consolidation phase? I mean you talked about all the tool sprawl out there. So maybe give us a mark-to-market and how early we are in that journey.

I mean I think we're -- it's a great question. I think we're in the third inning or something like that. We're still in the early third, probably in the first third of evolution. In virtually every customer or company we talk to, there are still many, many observability tools all over the place. Some have been launched on a centralized basis that they're trying to consolidate against, especially in log management. Others have been grown internally and yet others are deployed departmentally. And they're trying to get a handle on it.

I was speaking, just to give you an example, with an airline customer of ours, and they used to describe the incident management process before deploying Dynatrace. And they would say, we get 30 or 40 people in the room when our mobile app went down. Well, if a mobile app for an airline goes down, everybody in this room would panic because I don't know where my gate is, I can't buy a ticket, it would be horrific. I mean, just imagine. And what would you do? That's a bad thing.

And yet they would describe the incident process is getting all these people in the room, not my problem, not my problem, not my problem. It's not in logs. It's not in traces. It's not here or there. It's not in infrastructure, et cetera. And it wasn't particularly efficient. And what they really were trying to do in this example is consolidate the data, the domain and the personas to be able to get this end-to-end lens and observability to deliver better outcomes.

And I'm proud to say that with Dynatrace, they've seen an extraordinary evolution in success in the number of incidents, the amount of time it takes to address an incident. British Telecom was an example also where they reduced incidents using Dynatrace by 50% of the remaining incidents reduced the amount of time it took to resolve an incident by 90%.

And these kinds of metrics you really only get from a consolidated end-to-end environment. But those organizations that have moved to this sort of state are the ones that really, I think, are much more aggressively taking on the opportunity of improved overall software operations.

Yes. Very interesting. I want to touch on the log management opportunity. Grail has been a very exciting part of the Dynatrace story for a while. But at the same time, it seems like you have security vendors going after this opportunity. You have observability competitors going after the opportunity. So what's Dynatrace's right to win in this category?

What a great question. I would say that logs is one of our biggest opportunities as a company. It's certainly one of our biggest growth drivers. It will be our fastest business, fastest new business to $100 million in consumption, not quite there. We'll report to all of you when we get there, but we're well in the way to achieving that goal. And the opportunity is immense.

What do companies want from Dynatrace vis-a-vis logs? The answer is twofold. One, I come back to the end-to-end observability comments I made, which is it is all about outcomes. It is about answers that can be trusted and acted upon. And the more data you have, the more data types you have, the better your insights. I felt this 4 years ago when I joined Dynatrace, I feel it today.

The way the market grew up to have logs separate from other observability data types just by way of company deployments didn't make any sense to me because having logs as part of traces, metrics, real user data, other analytic data types gives you more data to be able to ascertain what the real root cause issue is. And if you have an automated AI engine that is inspecting all those data types, you're going to get better outcomes.

If on the other hand, you're using a separate log vendor from an observability vendor, a core observability vendor, then you are doing all of that manual correlation yourself, and you're probably not getting meaningful contextual outcomes. So first and foremost, I think organizations are looking to simplify their overall environment of vendor and vendor management, but they're also very much looking for better outcomes.

And you're going to get better outcomes if you have all the data types integrated into one overall data lake house, and that's why moving logs in with your observability data types is a significant advantage. The second piece of it is cost, which is getting into details, there are log management vendors out of there that have had, if not a monopoly, a near oligopoly for a long period of time. And I was down in Australia a couple of weeks ago, and I had a large Australian bank say their cost on one of those particular vendors was [ Meteoric ] and with limited value, with limited incremental value that is not commensurate with the increases in cost of the overall line management system.

We can provide a pretty material reduction in cost while producing better outcomes for observability logs. And this becomes a significant advantage, and this is why we are seeing such immense growth. Log consumption for us is growing more than 100% year-over-year. It grew 36% quarter-over-quarter for us on increasingly material numbers, we're very excited to see, and we see that evolution becoming durable.

So if I could just interrupt very quickly there. What is the technological breakthrough that is allowing you to displace the traditional vendors? And what is it that they have not done that Dynatrace has been able to do that is allowing you to get that price performance advantage?

Yes. So the breakthrough that we really delivered was Grail. Our underlying data lake house, which stores all observability data types inclusive of logs in context in one location is what enables us to then apply our AI engine to that data analysis. And in doing that, that's what gets you better outcomes. And so that was quite fundamental.

So it was the maturity of Grail to the point where it was able to handle logs at extraordinary scale, which really for us happened in about October of last year. So it's really been -- in some ways, we're still in sort of the first year following our delivery of that capability. And it is since then that we've seen the really marked increase in log capability on the platform. And so -- that was the primary driver.

And then I would say there are other elements just in terms of cost and pricing models. We didn't have an innovator's dilemma problem in pricing. We didn't have to say, well, we're going to reduce prices by 30% and take a 30% reduction in revenue. We could -- we could come out with pricing models that enabled us to grow and grow with the market.

So for example, one of our pricing models is called queries included or included queries model, where you can specify a number of days, and we'll give you unlimited queries on the log data set during that period of time. It could be 15 days, 30 days, whatever you want. And that just eliminates the uncertainty regarding, oh my God, I'm having to throttle usage of logs within a company of enormous scale, which is very difficult to do and instead say, have at it.

And then third and finally, our architecture with Grail and the overall platform makes no distinction between cold storage, warm storage, hot storage. And you see other vendors in the space sort of like, well, with more than 30 days, it's cold storage. I can't access it. Others are warm storage, which maybe I can access it, but it's delayed. For us, storage is storage, and we're going to access and provide essentially hot storage access to logs at all times. So the performance is exceptional relative to others on the market.

I want to switch to kind of the go-to-market changes that you've made over the last kind of 1.5 years. Can you give us an update on the progress that you've observed and where we stand with that evolution?

Yes. The -- we've added a number of people in the sales force over the second half of last year. This is our fiscal year. So that would have ended March 31. And those people, we still have roughly 1/3 of our sales force is within their first year of tenure. So we did this on purpose because we felt that the market opportunity justified the expansion in the sales force.

Those individuals are still in their first year and then it usually takes 9 to 12 months to get up to speed. So to become fully productive that those individuals, as we get into the second half of our fiscal year, we really expect to start showing growth and productivity.

[Technical Difficulty], right...

Yes, which is once we get into the December quarter, you'll really be in the second half of this fiscal year for us, and that we expect...

That's telling me Kash, your models are wrong. We need to take our numbers out for that.

Yes. No, I'm not going to comment on that [Technical Difficulty] Kash, but what I would say is to give you a very tangible example of it, it used to be the case that we had reps, strategic reps that would have 8 customers. And well, these are mega customers. And yet, when we looked at it, they were making their number on 4 of them. And the -- this is just using averages, obviously. But then the other 4 would be highly productive accounts, and they just didn't have the time to get to them.

So we felt that there was more territory capacity to expand to that, and that's where we've added the reps, and that's where we expect to see the productivity enhancement as we get into the second half. That's part of it. Another part of it is selling logs. We talked about that. So it is an expansion of the portfolio to really sell across the board. And we're seeing, as I mentioned earlier, a good traction on that.

And thirdly is partner evolution. We're seeing like one of our global system integrators has a pipeline that is 2 or 3x what we expected it to be. So we're seeing more and more capability out of the partner channels in particular, in GSIs as well as hyperscalers.

And maybe talk about the kind of push upmarket into these strategic IT 500 accounts in context of potentially longer deal cycles? Because I think over the last 2 quarters, you've disclosed some pretty punchy statistics around pipeline growth, 40%, 50%. So maybe just talk about that dynamic.

It is -- as I mentioned earlier, Dynatrace wins at the largest organizations because we have the most differentiation there. It's not to say we lose at the lower organizations, but where we most win, where we have the biggest differentiation is at large organizations because of data magnitude, volume and complexity. And that's where organizations are using other vendors, other partners for observability move to us.

So as we look at the opportunity to come, it really is of significance for us to be leaned in, in the partner community to be leaned in on the evolution of this particular set of cohorts to drive it. And what happens as a result of that is deal sizes grow. And as deal sizes grow, you have more variability because if you are delivering $50 million, $60 million, $70 million of net new ARR in a quarter, depending on the quarter, and you have $3 million, $4 million, $5 million deals. Last quarter, we had 12 7-figure ACV deals.

The loss of 1 or 2 of them has pretty significant downside risk and the gain of 1 or 2 extra has pretty significant upside risk -- upside opportunity, I should say. So there's more variability. And as a result of it, where we are conservative in our guidance because of that variability and that does cause or drive some of that conservatism in our portrayal of guidance so that we're assured that we can hit the numbers that we provide in the market.

I want to shift to DPS with the last 11 minutes. I love DPS. I spend a lot of time here. But 45% of customers, 65% of ARR. I guess what has been the main driver of DPS adoption, key learnings to date that you can implement moving forward?

So for those of you not as familiar with the story, DPS is our Dynatrace Platform Subscription. This is a new mechanism that we launched 2 years ago or so in our pricing model. It was in reaction to customer feedback that our prior licensing model was cumbersome and arduous to expand because we did it based on host units and you might buy 10,000 host units and you came back and you needed 2,000 more, and it was a new contract or a contract addendum and it was not very fluid.

What the Dynatrace Platform Subscription does is it gives you access as a customer to the entire platform for a specific amount of consumption commit over an annual period, sometimes it could be a multiyear contract.

And what it has enabled is that it has enabled a customer if they -- in my example, if they needed 12,000 host units immediately, they had it. It was there. They just start using it as opposed to contracting and coming back and iterating through it. And it also gave them access to the full platform. So maybe they were only using application performance monitoring, but now they have access to infrastructure monitoring, log management, application security and beyond.

So the result of all this is that DPS customers are showing consumption growth that is 2x the consumption growth of our non-DPS customers. Moreover, DPS has much more rapidly accelerated and penetrated the installed base than we saw previously. Now, as you say, 65% of overall ARR is already on DPS.

So we believe that the result of this is consumption being a huge driver of future opportunity and one of the primary growth drivers. And in fact, consumption for us, which we're now starting to communicate more broadly is so compelling that we're starting to share those numbers. Consumption for us growth -- is growing in excess of ARR growth and subscription revenue growth. So as I mentioned, subscription revenue growth was 19% per quarter, 19% in Q1 year-over-year.

So that would indicate to you that consumption growth is in the 20s. And that's where we see it growing. That is a huge leading indicator to future opportunities to then provide upgrades to customers because their consumption is growing into their DPS contract, sometimes beyond it, you have to repackage it or renew or expand your DPS contract.

So consumption is really an important growth driver in precursor. So if you take together the log opportunity, the consumption opportunity, the pipeline numbers and DPS and you put those 4 elements together, it gives you a pretty good sense of the growth drivers in the business and the opportunity we believe we have.

How are you incentivizing the sales force to help ramp consumption within their customer base after having demanded a DPS contract?

We have strike teams now that we have deployed that are in our -- the combination of sales and customer success organization that are compensated on consumption exclusively. In fact, our entire services organization at this point -- or I shouldn't say our entire organization, but the vast majority of our services organization, customer success managers, customer success engineers are all paid on a variable basis based on consumption, and that is a change that we made this year. So...

And we're just 2 quarters in.

Yes. So we are on a major pivot to really driving consumption. And it is the combination of this consumption plus DPS model that we believe really has an opportunity to unlock future revenue potential in the company, both in the installed base as well as new customers.

And can you talk about -- there's a bit of a wrinkle with some of the on-demand consumption piece versus renewals. So kind of where are we in that journey?

Yes. How much time you got to answer this question?

7 minutes.

7 minutes, I'll do it in one. What is -- again, for those of you who are familiar with the story, in a DPS contract, you get basically annual chunks at it. So let's say, it's $1.2 million annual contract, we would recognize revenue on that in our model ratably, $100,000 a month over a 12-month span. If you achieve that $1.2 million in consumption as of month 10, then you have 2 months where you need to make a decision. Either I'm going to pay you 2 months on actual consumption until the DPS contract renews at the $1.2 million beginning in year 2, which you can do or you can renew the contract.

The incentive to renew the contract is you usually up the commit. If you up the commit, you get a lower unit price. So it benefits you by renewing and then getting a lower price point at a higher volume. And we would have said that -- well, everybody is going to -- we wouldn't said everybody is going to -- we would thought that the vast majority of customers would renew that to get the lower price point.

But when you're dealing with customers the size of our customers, the mega customers around the planet or the mega companies around the planet, they put in a 3-year DPS agreement, they're like, I don't want to have to go through another contracting process when you're in on a 3-year contract. They're more than happy to just pay on a consumption basis for those couple of months and then allow the DPS contract to renew. So it is a combination of -- subscription revenue is really a combination of ARR commitment plus the sort of subperiod consumption elements that exist in the DPS contract.

That's helpful. I want to flip back to the AI piece with the last 5 minutes that we have here. You talked about the explosion of data and complexity driving demand for observability in the age of AI. Can you help frame for us a bit either qualitatively, quantitatively, how much of a tailwind that can prove to be for Dynatrace in sort of the near to medium term?

Because you've got the product angle in terms of AI observability, but then you also have the knock-on effects of more data complexity driving increased demand for IT infrastructure monitoring, APM, so on and so forth.

Yes there are -- it's important to sort of bifurcate when we talk about AI observability that into 2 pieces because they're different. The first is the ability to observe AI workloads. And we already have hundreds of customers, existing customers that are observing AI workloads with Dynatrace today. And observing those workloads to some extent, is just like observing any other workload, plus.

And the plus is you also want to know things like, is it hallucinating? What are the guardrails? What's happening in inference? So there are added elements to observing AI workloads beyond just the normal workloads that you would observe that we put into the model. And that is a significant opportunity as we see explosions of AI workloads that even our existing customers, let alone AI native companies.

The second evolution of AI observability for us is we really do believe that the vision -- the long-range vision for Dynatrace and what we believe quite fervently is the ultimate outcome that organizations want out of observability is a true autonomous AI observability platform that basically can take corrective action before an end user ever sees an issue.

It shouldn't be about incident reduction and MTTR or mean time to resolve issues. It should be, wow, look at that, we eliminated incidents altogether in this category of problems because we picked it before anybody ever saw it. The way to do that is through deep insights and an understanding of the appropriate answers that are trustworthy. And for that, we believe you need Dynatrace.

And it is because of that whole integrated platform structure that I talked about that delivers answers, not just dashboards based on causation, not correlation so that you can determine with certainty what the issue is. Every one of our competitors are going to be talking about Agentic AI. But I would submit to you, as I tell our customers as humbly as I can do it, that you cannot take a Agentic AI action if you can't trust the answer because in order to take action, you have to be sure that you're fixing the problem that actually was created.

So you have to start with a trustworthy answer -- if you start with a trustworthy answer, then you can take action. Moreover, we believe it will be an autonomous ecosystem, not just Dynatrace. We're certainly not saying we're going to take every action. In fact, quite the contrary. We see a problem in the system. We can push that through an MCP server. That can be picked up by Jira to fix a line of code, by GitHub, by ServiceNow, by Hyperscaler. So you may need to provision more storage. You may need to do an application rollback. You may need to fix a line of code. I mean there could be a variety of outcomes that would be taken by other agents.

And so our agents can determine what the issue is, what action should be taken to then submit that to allow other agents to take action on those trustworthy insights. And it is that, that is so exciting for us, I think, at Dynatrace because it is our foundation that really enables that to be a closed autonomous ecosystem that really could be quite compelling.

I'm curious, like as you guys move from simplistically like root cause identification to like autonomous remediation, how does Dynatrace make sure that they're capturing that incremental value from a pricing perspective?

It's a great question. Ultimately, we need to make sure that we're delivering the metrics and the value proof points to ensure that, well, it isn't just my software is working so much better, but what does Dynatrace do to contribute that? And this is where we see it to some extent in consumption across.

DPS should help, right?

And DPS should help. And by the way, those consumption numbers are really not -- they're not just in DPS. We're seeing consumption expansion across the DPS and the foundational elements. So really across the platform, that is probably the best indicator to the answer to your question.

Final few seconds. Anybody has any questions? Just I have one question. AI natives, are they trying to build something on their own because they're so smart and they've got all the technical expertise?

I mean...

The exclusion of entertaining Dynatrace in their IT...

Sure. Presumably, they could. But I think the number of customers at this point that are going to build their own observability system with the level of complexity that we've designed into the Dynatrace with integration at data layer, domain layer, personas, autonomous AI observability engines and capabilities, I mean, that is just unrealistic. So I would never say never, but it's tough.

I mean even the hyperscalers, I get asked about all the time and would the hyperscalers do it. The problem is Dynatrace delivers in a hybrid cloud environment. So it's on-prem, off-prem. It delivers in a multi-cloud environment across hyperscalers is one of the hyperscalers really going to build a hybrid cloud, multi-cloud environment for observability. I don't see that. So I think it's going to be in the vast majority of companies willing to take that sort of action.

On that note, thank you so much for your support of the conference, and thank you to our clients and enjoy the rest of another 1.5 days.

Well, thanks, everybody, for joining. Thank you.

Absolutely.

Thank you for joining us for the Dynatrace fireside chat. Fatima Boolani, your resident software analyst here at Citi. I'm very excited to have Jim Benson, CFO of Dynatrace; and Dan Zugelder, Chief Revenue Officer and Head of the go-to-market organization at Dynatrace for what I think is going to be a really fun conversation, lots to talk about.

So I think a good place to start is taking us through some of the highlights and milestones out of your recent quarter's results and some of the things that are worthwhile reemphasizing and reiterating, and I know we'll have a lot of threads to pull on from there.

Well, I'll start with that. Well, let me first say, welcome back. I know it's kind of a -- you're back, but then you're back on maternity leave again. But welcome back.

Thank you.

So I'd say relative to the quarter, and then I'll talk more thematically about what's going on in the company, I'd say relative to the quarter, which was for us at our first quarter was a really strong start to the year. We saw 13% growth in net new ARR. We saw continued traction in our DPS subscription model with now over 65% of our business on this contract vehicle, 45% of our customer's consumption, which is usage of the platform continues to accelerate.

We had a really strong logs quarter. We talked quickly about $100 million consumption ambition. We are well on track to be able to execute against that. So call it thematically, strong start to the year. I'd say the building blocks that we've been talking about over the last 18 months, you're going to see them manifest themselves in the results that I'm sure we'll talk about it here in a few minutes.

A lot of the substantive structural changes that Dan made on the go-to-market side, you're starting to see some traction on that. We continue to see traction in the areas that I mentioned. And the areas that Dan has been focusing on are starting to show up in the results.

So I feel really good about where we're at around the things that we put in place. I think we put some good points on the board. But I think we've got to build more maturation in these areas. We've got to build more consistency. I'd say the theme for us is when we put all of these changes in place, it was the theme of going on the offensive.

So these were structural changes that we felt were needed to better scale the company. And admittedly, these things were not expected to pay productivity dividends right away. So we're still in the maturation period, and I'm sure we'll talk about that a little bit more. But I feel really good about the traction. We got to continue to execute against that as the year progresses. And -- but I view this year a bit as a stabilization year that -- and hopefully, we can pivot because the opportunity is there to a reacceleration in the growth of the business. So I'm very confident and very optimistic about what we've done. I just think we've got to continue to drive more consistency.

Jim, I'm going to double down on the comment you made around DPS. That has been a very consequential change in the business. I think 2.5 years out on paper, but really a year and change of getting reps with customers and selling.

So a pretty significant part of your story and the evolution of the financial model and the business model. So can you -- generally, for those who of us kind of initiate it, walk us through some of the mechanics of DPS.

And Dan, I would love for you to chime in on, hey, I think we're in year 2 for most of your customers you've signed between a 1- and 3-year PAUSE. So let's say, on average, it's 2 and change. So we're kind of in the midst of an impending renewal cycle. Would love to get some of your perspectives on how that's transpiring now that we're a little bit more mature with the DPS conversations and the selling motions.

Perfect. So I can start, and then Dan, you can comment. So you're right, it was April of 2 years ago is when we started it. And just to make sure people are level set on what the vehicle is, is it's basically customers signing up to a dollar commitment for a term. A year or in most cases, 80% of our DPS contracts are multiyear. So -- and it is -- so it's a consumption drawdown model. But because of our revenue model is a ratable revenue recognition. So if you commit to $1 million contract for a year, you ratably recognize it through the year, regardless of what consumption is.

It gives you access to the platform, all capabilities, which was a point of friction for customers that when they wanted to add a capability to Dynatrace, it required a go-to-market kind of activity, you remove that. So you commit to a dollar amount, full access to the platform, full rate card. And the thesis that we have with that is that customers, if they have that vehicle will consume faster. They will consume more capabilities. They will have higher renewal rates. They will ultimately have higher NRR rates.

All of those things have been true. So we're now kind of, to your point, 2.25 years into the journey. We now have 65% of our business on it. So to your point about where are we on the journey, last year, fiscal '25 was the year you had your first cohort of customers that went through there, their first, call it, reset -- annual reset.

So this year will be customers that are going through their second annual, so you'll have some customers. So your first cohort class will be going through it this year. That will be their second year. And then obviously, your fiscal '25 customers that you put on to the DPS contracting vehicle will go through their first year.

So I'd say we're not as far along as you suggested, but I'd say we are kind of -- we've advanced where we were last year by 2. So we are now in a position where more customers are on it. There will be more customers up for renewal probably at 2x the rate of what we had last year. So they're either going to go through a period of maybe having an on-demand consumption opportunity or, in some cases, having an opportunity to actually have an early expansion.

I mean, Dan can probably comment further on where we're at in the journey around how do we go from where we are now with -- to the next leg, which is trying to get a greater percentage of our customers on it.

Yes. When you design something, you have your hypothesis of what it's going to do, but sometimes the field sellers, they had to see it happening. And I think seeing the consumption, at first, it was a fairly slow adoption in the first quarter or 2 as they were understanding. And then all of a sudden, they started seeing customer adoption and consumption go up in a number of products.

So you had this huge buy-in from the sales force. So you saw kind of slow adoption in this, and now more rapid adoption of rolling this out to our customer base. But we don't -- we're not satisfied with just 65% because it's been so successful, because it's giving us the foundation for growth and so much of our customer base, we have -- we want to accelerate that.

So we are doing a couple of things to accelerate even further. One is we did not incent the sales team. When somebody wasn't doing the expansion, we did not incent them to take them from SKU to DPS. Some customers did because they liked it, and we offered it, but there wasn't -- we weren't driving it.

It was more organic from the customer's...

Exactly. It was reactive if I want to call it that way. Now we've changed -- just as of April 1, we've changed. With the customer comes up, it's not going to expand. It happens that we will incentivize the sales team to move them from SKU to DPS. So that's one lever that we have.

We also have a fairly long tail of customers that we just have our renewals team do. And these customers are actually a lot of them are SKU. And we just did a renew like-for-like. And now we brought in a team of people that are DPS experts, that do renewals, that convert and educate a customer on why you would want to do DPS. So that's a long tail motion.

So we have -- clearly, we have a growth motion that we've been doing already. That's got us to the point where I'm now. We have the larger like-for-like motion that we incentivize, and we have our long tail motion, all in an effort, we believe, to get us to 80-plus percent of our customers. And we believe that's the win-win.

Our customers consume better, get more value, and it puts us in a position to expand.

I think, Jim, one of the things that you've realized in managing the business is the reality is sometimes doesn't match our Excel spreadsheets, right? And what I mean by that is there is a contractual commitment on a drawdown model, a DPS. But incidentally, a lot of customers tend to blow through those commitments, right?

And then you have this persnickety concept of on-demand consumption, which is something you all have talked about. So how much of that has influenced the model from a financial perspective in the last 6 months, again, as DPS has hit more of a critical mass in the model in the business?

And I understand you've sort of reoriented and tweaked some of the incentive structures around ODC, we'll refer to it as ODC, going forward. So just a little bit of a walk down memory lane on, hey, this ODC concept has come up, how that has impacted numbers and how we should think about the impact of ODC on the business over the course of fiscal '26?

Yes. So well, I'll start with the -- to your point about the memory lane, the memory lane in fiscal '25, and we were very transparent about it, was our initial thesis for DPS was everything we talked about we thought was going to be, you get them on this as a contracting vehicle, they'll consume faster, they'll consume more of the capabilities, all of these things.

The -- our thesis was that they would -- when they did all of that, it would lead to an early expansion. That was the original thesis. What we found in fiscal '25, which was the first period that we had these cohorts coming up for their annual reset, what we found was you had a number of customers that didn't necessarily do an expansion. They actually were okay going into an overage.

We call it on-demand consumption and not an overage because we charge a premium for it. So that surprised us a bit. We thought there'd be a handful of customers that would do that, but it was more than we thought. And so we saw this behavior of a certain subset of customers that were maybe they had gone through a 3-year expansion the year before, and they are now burning through their commitment for the first year of that.

And I think what we realized and going through it is some customers will like, " I just renewed this a year ago. I am not going to go through an early renewal. I'm happy to go pay on demand." So we saw this behavior of customers that were okay going on demand.

Now...

It's then punitive for them either way.

It was not punitive because we didn't charge them an overage rate. It's a very customer-friendly model. Now I admit it is not a stick model that forces them to do an early expansion. But our whole premise was we want them to consume more of the platform.

So we're somewhat indifferent. We get revenue from it either way. And so we saw this -- it became a source of subscription revenue. And I think we did $19 million or $20 million worth of business that we did not expect. And the way to view that is that $19 million or $20 million is basically deferred ARR.

And so we learned from that, and we now believe that there's a component of customers that will go through this on-demand consumption. So I think the thesis that we had before is still in place. I think the one distinction is there's going to be a subset of customers that are willing to go on demand. And then there's going to be a subset of customers that are willing to do an early expansion.

I think fiscal '26 is the, I don't know, a year of what percentage of them because you're now going to have a growing number of customers going through their second year and whether they do -- whether their growth rate relative to consumption behaves the same, are they going to do on-demand consumption again or are they going to go into an early expansion?

Again, we're somewhat agnostic from an incentive perspective, which you talked about. We did change the incentive structure on the sales organization where they used to get paid the same amount whether it was an on-demand consumption booking, we would call it, or an ARR generating booking. Effective April this year, we moved to a model of $0.25 on the dollar for an on-demand consumption booking and $1 for an ARR generating booking.

And we did that because we really want the sales organization hunting for new ARR. We have a motion of people in the company, whether they be strike teams or whether they be our customer success teams that are incented to drive consumption. Those are the teams that should be driving more adoption. We want sales to get credit because, obviously, those are customers that are growing and expanding. But we wanted there to be more of an orientation around drive more committed bookings.

And Dan, you could maybe comment on where 6 months -- 5 months into it.

I think we feel we struck a good balance. We feel like the sales teams know that commitment is their primary, but we also have the CSMs, the strike teams, everybody in the company. And one of the things we'll probably refer to is this consumption mindset within Dynatrace, which is relatively new, but it's bringing in the consumption mindset about customer success as customers consuming.

By the way, we believe they get more value and they position us for growth. But for us, we want them to be -- have a skin in the game for consumption. And if customers go over and aren't willing to expand, they get something. It's not without any compensation.

But primarily -- and we've seen it work well because I hear our salespeople talk and they're like, "No, no, I want an expansion." So they definitely are incentive to go in position a customer care. By the way, there's something in it for the customer is, well, we're going to drop their unit cost as they expand. So the customer wins as well. It's not just, hey, force them to do it. We're providing a carrot along the way.

But I think we've struck a balance that customers don't want to stick. They like a carrot. The sales teams get a carrot to drive consumption. They get some compensation for there. So we feel pretty good about -- almost 6 months in that we've struck a good balance from a customer side, Dynatrace side and a field sales side.

Dan, you said 6 months, so it triggered my antennas. This time last year, one of the more novel changes to the go-to-market incentive structure was introducing biannual quotas -- or implementing biannual quotas for the sales organization. At the time, I think you all were appropriately conservative in saying, "Hey, we don't expect this to have any material change right out the gate, but now we're here in." We're -- you're better where you're stronger.

How has -- how is year 2 of having a biannual quota implemented and cemented in the organization impacted downstream KPIs like funnel creation, deal size, deal size growth? Anything you can share on that, that can give us confidence that now the biannual quota system is really hitting its stride in a very positive way.

Yes. I mean, I think there were 2 or 3 desired outcomes from it. One was to try to change our seasonality mix a bit. We were very back-end loaded, and we felt that, that introduced some business risk as well as just some revenue potentially delayed. So we wanted to change our seasonality. We believe, right now, we're already seeing some of the early signs that that's working. So that was one.

The second thing was agility, the ability to make changes halfway through the year. As you know, it's hard to foresee a year down the road. There are certain things that happen in the business, and we want to introduce an ability to have a little bit more agility to make some tweaks along the way that would drive the company's strategy.

So we have done that. We already have planned. We won't get into that today, but some tweaks that we're making going into the second half of the year in October, which we think will have an impact, but maybe these are tweaks. There are changes, but it allows us not to have to wait until April to do those. So that's number two.

And I think the third thing that we wanted to introduce is the ability is to set, to manage cost, to set proper quotas. So when you're setting a quota to forecast a year out by -- at the account level, it is -- if you ask any go-to-market, it's a pretty difficult thing to do. But 6 months is a much more manageable thing.

So you're able to set proper quotas to give people the right incentives, but also don't have the haves and have-nots where you underset somebody's quota and overset somebody else's. So it gives you the ability to be more accurate.

You actually drive costs down that way by doing that because you want people getting to plan, but you don't want some people 500% and other people at 20%. So you want as many people -- I always say that 80 to 120 as you can get. That allows us to do that. We're already seeing that compression of those results getting closer in that range.

So those are the 3 things. We're definitely not moving away. Everything that we wanted to do were leasing signs that it's playing out.

Jim, back to you. Just one of the questions we get a lot is this divergence that we're seeing on the subscription revenue growth trajectory versus the ARR. To borrow your term, it's a deferred ARR. That's sort of transpiring right now.

So it's sort of this short-term nuisance, if I can use my own word, to the model. To ask it more simply, when should we start to see a little bit more equilibrium in the ARR and subscription revenue growth trajectory?

So I think I said it kind of the front end. I kind of view fiscal '26 as a maturation year, as a transition year where a lot of the building blocks that we put in place, we got to see them continue to mature. We mentioned some of the changes Dan made. Those need to continue to mature and go from -- they've generated a lot of good pipeline to actually we're closing the pipeline.

We talked about strike teams and having -- those strike teams have only been in place since April. So I view this year as a lot of maturation, building more muscle around driving consumption within the company. To Dan's point, that's a new muscle. That's not something we've ever worried about before.

We never had people compensated on consumption before. Because DPS as a vehicle by its nature is consumption-driven, we needed to have an incentive structure in place to have more people have consumption as a North Star.

So I think what you're going to see is you're going to start to see the convergence of ARR and subscription growth stabilized kind of to the levels that I've talked about. Hopefully, we do a little bit better than that. But then in fiscal '27 start to be -- to kind of connect again. And you'll start to see them mirror one another. And obviously, our objective is to show a reacceleration in the growth of the business exiting fiscal '26 because then you're going to have all these changes we've made.

So I'd say the structural part is done. The maturation part is what's in process. And so I feel good about it. So it's like all these nice building blocks of DPS kind of segmentation changes, we haven't talked about partners, but a lot of work that Dan and team have done around leveraging partners to drive more velocity, driving more consumption, logs being kind of this new area where we have the right product with the right pricing and packaging now matched with a strike team that can actually make it happen, I just feel very good about all the ingredients.

It's just a matter -- they equal -- they all need to mature, including our consumption motion, to be very frank. That's a new muscle. So that's something our new Chief Customer Officer is trying to put in place, which is driving more of a consumption mindset with that team. So different phases of maturation across those things. I think where -- the goal is for that to stabilize growth for fiscal '26 to be in a position to reaccelerate in fiscal '27.

Yes. And just to further on that, I mean, we didn't downplay it, but we certainly -- I mean, we made some very significant structural changes to the go-to-market. It was a tribute. We did share that we were open, but I think sometimes when you see the extent of the people transformation, leadership changes, we brought in a -- what we feel like is an A-team from a sales leadership team, but that was my entire direct team is 9 out of 10 was changed.

Over the course of what times?

In the course of -- from July 1 of '23 to...

Yes. His leadership team when he joined and his leadership team now, 9 out of 10 are new. Not all of them were external hires. Some of them were developed from within. But pretty significant change.

And then you do the segmentation work that we shared, you do the partner work that we test. So that's the work that we see in fiscal '25. We were able -- we were happy about -- we were able to execute through those changes.

But as we go now, we're looking and we're starting to see the green shoots of those things starting to play out, especially in the enterprise, I mean, where we invested a lot of capacity. We brought in new people that understood how to sell to the Citibanks of the world and so forth, so that you can capitalize on that opportunity.

Jim, you and Rick have not been shy about expressing that there is a quality over quantity bias in terms of how you think about customer and customer acquisition. You did the large account segmentation project as well, among other things, last year in the go-to-market.

But the installed base is fantastic. It's the gift that keeps on giving. You have diehard Dynatrace customers who continue to come back to the well, right, and that's important. But just from a logo growth perspective, that's potentially an area that you've also expressed a need and a desire to improve.

So what are some of the steps you are taking or have been taking to really energize the new logo growth velocity? And how does the strengthening of relationships with the GSI and partner community play into that? And I'd love to have you slap some numbers around that as well and how that's done.

Let me start, and then I'll have Dan comment specifically around kind of some of the targeted areas that we're driving. It shouldn't be lost on people that the segmentation changes that we made, that the initial benefit from that was going to be expansions because this segmentation change was oriented around getting the right resources on the right accounts with the highest propensity to spend.

Those happened to be -- we had -- in the enterprise or the strategics, we had 8 to 10 accounts per rep existing. Now they have 4 to 5. So the beneficiary we were going to see of the segmentation work was going to primarily be on the expansion side to start. And so I would say fiscal '26 is probably going to be a bit more expansion weighted.

I'm not going to apologize for that because I think it's where the most productivity will come from. We equally want to ensure that we're bringing in, to your point, the generation of new logos that can be the next set of customers to do large expansions with. And I've purposely been talking about quality of land over quantity because what we don't want is to land new logos not at the right profile, not at the right size, because we don't churn a lot of customers, but where we do churn them happen to be at a lower dollar value. And so it's a little bit of a balance around making sure you're bringing in the right quality of new logo.

But Dan, you can comment a little bit around what we're doing to...

I mean, it's a very important point, meaning we want to retain them. So we know that the customers that we land a little larger that their retention numbers are far better. A small 100,000 land does not really stay. It's not a lot of revenue upfront, but they also don't have a high retention rate, too, because they're not getting the TLC.

So we want to do that. I think our -- we have a pretty significant change that we started implementing in April 1 around new logos, and that is to ensure that each segment of our business, we have 3 segments, strategics, our enterprise business and commercial, each one of them have their land play. And I think that's one of the maturity things that we have learned to is that our land play with our strategics is not the same land play in our commercial.

So we've refined that. We feel -- especially when you start looking at pipeline, hey, we're starting to build the pipeline of new logo business that will enable -- we are fortunate, I think, that we can depend on our pipeline. We see it. It's proven itself out. Even times when we see things that aren't good, we see that in advance, and we're -- we have a good mechanism to see into the future.

So ultimately, we are a believer that each segment has kind of a different land motion. And each one of them has its own play that will be effective. So we're seeing that play out.

And maybe to put some -- I know you asked some numbers, and it's like we were -- it's like you didn't give me a number, that we've historically had kind of a 1/3 new logo, 2/3 expansions. I do think that's probably the right long-term model.

I'd say we're probably going to be more expansion heavy this year, so that you're probably going to be more like 30%, 70%, plus or minus a little bit. But I think we'll get back to maybe the more -- but I think it's because the go-to-market changes that we made were initially going to benefit expansions.

And you're seeing the -- I'd say the next wave is how do you drive a better balance between expansions and new logos. And that's kind of the mix. And as Dan knows, as a go-to-market leader, there's always tweaks that you're doing around how do I drive the right behavior, am I incenting enough for customers, because it's hard to bring in a new logo. It's hard to bring in a new logo, then expand with a customer that already knows you and values you.

And so there's probably going to be some tweaks to the incentive structure that we're going to want to do. Maybe some sales plays, as Dan mentioned. But I think the -- I think this year is going to be a very good expansion year, a little bit lighter on the new logo side. And I think we'll be in a more balanced position next year.

And it will be a good new logo dollar year. So we feel good from a new logo dollars. I think the long tail or the number of new logos is I think one of the other things we're trying to work on. But we will have a very good year-over-year new logo dollars.

That means the size of them that we're bringing on are going to be larger. We feel very good about that number, which is not a bad number, but it's not necessarily both. We want to see the number of new logos and the new logo dollars. I think we feel confident in the new logo dollars. We're still working on the total number of new logo.

The other thing that's probably worth mentioning, just not to belabor it, but maybe 30 seconds more is the motion of new logos maybe in the past was that you landed with an application owner and then you expanded. The world has kind of evolved where people have a lot of tools.

I mean, the reality is people aren't naked relative to observability. They're either doing DIY or they have some commercial tooling solutions. And so sometimes with new logos, they are interested in someone that's going to be able to make it easier for them and consolidate things for them.

Those types of lands take longer because the customer need is, "I have a lot of tools." I mean, we have some examples of customers where we went through that, that they want to consolidate tools. And so we want to make sure that, again, we're in a position for those customers that are the sweet spot for Dynatrace we can land.

Well, I think that's an important distinction because what I was actually going to ask you, and I'm glad you brought this up, but it's not necessarily, and you can correct me if I'm wrong, that the cost of large customer acquisition has gone up. It's just the sales cycle conversation or the sales engagement has, I don't want to say, elongated because that sort of has a pejorative context.

It's just it's going to take more stakeholders for you to engage, and that's why the -- when the new logo lands, they land big. And I believe some of your disclosures have been around 140,000 or 150,000 in ARR lands, which is...

130,000 to 140,000, yes.

I'm great inflating a little bit. But -- which is outside of the historical band of the 90,000 to 120,000 that you very habitually did a couple of years ago. So it's not necessarily that it's much more expensive to get after these accounts. It's just taking a little bit longer to cajole a lot more constituents internally.

We've been very open, a play that is very effective for us, both at existing customers and new customers is an end-to-end observability play. It's what customers like about Dynatrace because whether you're in the cloud, whether you have on-prem, mainframe, whatever you are, we can handle a very diverse set of workloads.

And so our play even for new logos, were in there saying, "Hey, we can help you to consolidate," even if we're not the incumbent, and they like it because of the versatility that we have from on-prem, off-prem, different mainframe to mobile. So with that, I think it has given us larger lands, but it has a sales cycle to it as well.

I want to talk about net retention rates, again, in the context of transitioning to more the DPS motion as the primary conduit of customer activity. How should we take net retention rates at face value? What should we consider? What are some of the kind of the mitigating forces on net retention rate?

So as we said that net retention rates are certainly higher for DPS customers than non-DPS customers. I would be remiss if I didn't remind folks that we actually saw a slight improvement in net retention rates in our Q1 period. We went from 110 to 111.

It's a trailing 12-month metric and was probably not going to move materially up or down a lot in the near term. But everything we're doing around driving consumption with DPS, ultimately, will manifest itself in if customers are consuming and getting value, you will start to see that show up in NRR.

Now it's a journey, right? You got to consume for a period of time before it turns into an expansion. So some of the North Star metrics that we are looking at internally is consumption. What are consumption growth rate is doing? And I -- our consumption growth rates are like 150% of where our ARR growth is.

So we are showing very, very healthy consumption growth. You continue to grow at those rates, you have to, over time, see an expansion. And so I think you will see it. But again, I'd say the new muscle for the company is driving consumption.

I'd say in the past with the old model, SKUs, it didn't really matter. Now obviously, customers don't want shelfware. But now it does matter. And so I'd say it's a muscle that we're building. I think it's something within the company that we talk about at every all team. We now have incentive structures in place.

So we now have a customer success team that's measured on consumption. Some of Dan's team is measured on consumption. And so it's a muscle we're building. And ultimately, this muscle of driving more consumption and adoption will show up in NRR.

I know we're out of time, but I think it's incumbent upon me to ask you the question around your operating rigor and operating performance and cash flow performance. You talked a lot about maybe indexing more to expansionary business over the course of year '26 -- near term.

So by definition, that necessarily means you're going back to a customer that is already familiar with you, is already an avid user of the platform and the portfolio. So can we take away from that fact that there is incremental leverage to be had in the business because it eliminates some of that net new customer acquisition costs? So tell us -- or tell me, rather, where I'm maybe not right in that assumption.

No, you're right as far as leverage in the model in certain areas. So it's areas we're going to try to drive leverage in the model. You'll get more productivity in sales and marketing for the reasons you just said. We're going to drive more productivity and leverage in G&A.

But we are intentionally not wanting to continue to accrete margins the way we have historically because we want to reinvest it in R&D. And so there's a bit of a balance that -- we're not going to go below our current threshold, which is around 29% operating margins. I think we talked about 32% pretax free cash flow margin. So think of those as floors.

And there's optionality. We can drive leverage if we want. There's certainly room in the model, but we do think there needs to be reinvestment. That reinvestment we want in R&D. We did do some reinvestment within sales. Dan reinvested some of the dollars that he already has in these strike teams. And so there is some reinvestment that we think that will yield better productivity per resource for the company.

Time flies when you're having fun. Good place to end the discussion. Thank you so much.

Thank you.

Fantastic conversation.

Thank you. Buh-bye.

Greetings, and welcome to Dynatrace's Fiscal First Quarter 2021 Earnings Call. [Operator Instructions] As a reminder, this conference is being recorded.

It is now my pleasure to introduce Noelle Faris, Vice President of Investor Relations. Thank you. You may begin.

Good morning, and thank you for joining Dynatrace's First Quarter Fiscal 2026 Earnings Conference Call. Joining me today are Rick McConnell, Chief Executive Officer; and Jim Benson, Chief Financial Officer. Before we get started, please note that today's comments include forward-looking statements such as statements regarding revenue, earnings guidance and economic conditions. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q and our annual report on Form 10-K. The forward-looking statements contained in this call represent the company's views on August 6, 2025. We assume no obligation to update these statements as a result of new information, future events or circumstances.

Unless otherwise noted, the growth rates we discuss today are year-over-year and non-GAAP reflecting constant currency growth and per share amounts are on a diluted basis. We will also discuss other non-GAAP financial measures on today's call. To see reconciliations between non-GAAP and GAAP measures please refer to today's earnings press release and supplemental presentation, which are both posted in the financial results section of our IR website.

And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.

Thanks, Noelle, and good morning, everyone. I'm thrilled to be joining you from our new corporate headquarters in Boston. It's a vibrant modern space that is a direct reflection of our collaborative and innovative culture, and I am excited to host customer and investor meetings here in the future.

Moving on to our Q1 earnings.

Dynatrace had a strong start to fiscal 2026. Subscription revenue grew 19%. ARR grew 16%. The -- and pretax free cash flow was 33% of revenue on a trailing 12-month basis. These results continue to demonstrate our ability to deliver a powerful combination of top line growth, profitability and free cash flow. The strength of our AI-powered observability platform continues to resonate with customers as they look to standardize observability on a single end-to-end platform to deliver precise answers, deterministic insights and intelligent automation. Jim will share more details about our Q1 financial performance and guidance in a moment. In the meantime, I'd like to share my thoughts on what we see as the durable drivers of growth in the observability market and why I believe Dynatrace is well positioned to benefit from them.

In the last several weeks, I've met with dozens of customers around the globe and there is increasing alignment around 3 key approaches to unlocking value with observability, end-to-end observability, AI observability and business observability.

Let me start with end-to-end observability. The rapid rise of cloud modernization and AI workloads has caused a massive explosion of data and complexity. Hyperscalers are now generating more than $265 billion in annualized revenue, growing in the mid-20s. And this immense shift to the cloud is creating a level of scale too large for humans to manage. Meanwhile, traditional observability solutions used by organizations to manage digital workflows are often siloed and do not deliver the holistic picture needed to optimize results. And dashboards and other visualization tools require substantial manual oversight and response. Organizations are consequently looking for an end-to-end observability platform that provides deep analytics and insights ultimately enabling automated response. This is precisely the differentiating power of Dynatrace, allowing customers to take a proactive approach to address these challenges and deliver radically better outcomes.

End-to-end observability first requires unification across observability domains with organizations increasingly seeking a single solution for applications, infrastructure, log analytics, real user monitoring, application security and other areas. By providing a unified platform, Dynatrace provides a complete picture of digital services rather than customers having a state them together manually. End-to-end observability also necessitates a common data layer. Dynatrace customers benefit from the power of GRail -- our massively parallel processing data lake house that houses all data types, logs, traces, metrics, real user data and more in context to provide accelerated insights at enormous scale.

And finally, end-to-end observability mandates accessibility by all personas. With Dynatrace developers, platform engineers, SRE teams, IT ops and even executives can now all leverage the same data in a unified platform to enable the group to work better together to remediate, protect and optimize cloud-native workloads. Organizations are also able to extend left to take advantage of observability insights much earlier in the development process.

This brings me to the second application of observability, AI observability. Dynatrace, we have been using AI to deliver insights for over a decade, and we continue to innovate aggressively in expanding our capabilities. We utilize multiple AI techniques in our platform. Causal AI for root cause analysis, predictive AI to apply anomaly detection and machine learning to anticipate issues and generative AI to make the platform accessible to a wider array of end users. And customers are increasing their use of the platform to observe their AI workloads. For example, 1 financial software customer deployed agents to automate many different finance tasks. Prior to the launch, they leverage Dynatrace's AI observability to validate performance of their new agent capabilities. A large insurance company has been building an internal AI platform to increase the efficiency of their engineering teams. They utilize Dynatrace to help ensure their AI platform is functioning correctly and cost effectively.

Furthermore, we have built our third-generation platform with GRAIL at its core to seamlessly unify observability, security and business data. This foundation empowers intelligent decision-making and action, enabling enterprises to transition from human oversight to intelligent autonomous systems. We recently announced significant advancements in our platform, evolving its ability to serve as the knowledge, reasoning, planning and actioning framework of Agenetic AI and provide trustworthy precision and adaptability. We believe that Agenetic AI advances the fulfillment of our patient by providing a clear directional heading that drives the core of our operations. And we are driving toward an Agentic AI ecosystem in which our AI agents will interoperate with third-party AI agents to take appropriate action.

Importantly, deterministic answers are critical for Agentic AI to work properly. You have to trust answers to take action on them. which is precisely the confidence that we believe the Dynatrace platform provides.

The third way customers are driving outcomes with observability is business observability. We think of business observability as the ability to deliver meaningful business value beyond technical analytics, root cause analysis and the mean time to resolution. Because we include business events as a data type in Grail, we can provide a broad set of insights like business process optimistion, revenue impact and real-time analytics for any observability source. For example, a large airline uses Dynatrace to assess gate operations and baggage handling. A cruise ship operator focuses its Dynatrace insights on the passenger onboard experience. And financial services firms are interested in time to open an account or mortgage or to make a payment. Business observability is about identifying the key performance indicators a customer wants to address and leveraging an end-to-end observability framework to optimize their attainment. And this is where Dynatrace can increasingly become a force multiplier for businesses looking ahead.

These 3 enterprise use cases for observability represent a strong growth opportunity for Dynatrace. And we are investing in sales and marketing initiatives across those areas.

So next, I'd like to share several proof points of our go-to-market momentum from the first quarter. First, the investments we made during fiscal 2025 to align our sales coverage around strategic accounts with a higher propensity to spend is evident in the 12 7-figure ACV deals closed in the quarter. Additionally, our strategic enterprise pipeline has grown nearly 50% year-over-year with the pipeline contribution of deals greater than $1 million, more than doubled over that time frame.

Second -- we continue to see strong traction with our partner ecosystem, most notably in the growth and contribution of GSIs. Partners were involved in 10 of the 7-figure deals we closed in the quarter. And GSIs played a role in more than half of those. Our largest GSI partners ARR contribution in the first quarter has more than tripled year-over-year.

And finally, the recent traction we're seeing in labs is a direct result of our broad-based sales execution in this area, combined with the investments we've made in building out strike teams to drive adoption. In Q1, our logs consumption increased 36% sequentially and well over 100% year-over-year. Given this traction, we remain confident in our ability to achieve $100 million in annualized logs consumption by the end of this fiscal year. Given the noteworthy traction of logs in the first quarter, I'd like to take a moment to discuss logs in more detail and why we believe we are positioned to win material share in this space.

In particular, logs have rapidly become a core element of end-to-end observability as I mentioned before. And our third-generation platform provides the core capabilities to deliver meaningful value as customers expand in this direction. Dynatrace's log management solution has multiple advantages. By combining logs with other data types, logs actually add increased value in delivering deeper, more contextualized absorbability insights. Moreover, unlike traditional solutions Grail does not require rehydration of locks. So they are always available and don't require manual categorization and separate complex pricing.

And finally, we are able to offer our log solution at a lower cost, including unlimited querying over a fixed time window, maximizing insight while controlling spend. Once customers experience the value of our log management solution as part of their Dynatrace platform deployment, they often rapidly expand their usage. A major airline that became a customer within the last 18 months as a multi-vendor competitive takeout with end-to-end observability has now already exceeded an annualized logs consumption of several million dollars. In fact, many of our 7-figure ACV wins in the quarter were with customers looking to modernize their log management solutions, consolidating logs from multiple vendors as part of a broader end-to-end observability strategy. A Fortune 100 retailer expanded their deployment with Dynatrace to provide a precise view of the customer journey from online ordering through pickup.

A global leader in logistics and transportation engage us to unify their data to reduce operating costs and increase efficiencies. And 1 of the largest insurance providers in North America is going all in with Dynatrace to help them improve their customer experience with our unparalleled visibility into their enterprise-wide environment. All 3 of these customers have a planned annualized logs consumption of at least $1 million.

Finally, analysts continue to recognize Dynatrace as an industry leader. Last month, Gartner named Dynatrace a leader in the 2025 Gartner Magic Quadrant for observability platforms positioned highest in execution. This is the 15th consecutive year that Gartner has named Dynatrace a leader. Moreover, we ranked #1 across 4 of the 6 use cases in the 2025 Gartner critical capabilities for Observability Platform report; and second, in the other 2 use cases, a very strong achievement. Plus, we were named a leader and outperformer in the 2025 GigaOM radar for Kubernetes observability. We are proud of these achievements and committed to the ongoing innovation and customer engagement needed to earn these accolades year after year.

To wrap up, the observability market opportunity is stronger than ever. We have a significantly differentiated AI-powered platform that provides the foundation for end-to-end observability, AI observability and business observability. We deliver significant customer value and we have a compelling business model, which has enabled us to deliver a sustained balance of growth and profitability.

Jim, over to you.

Thank you, Rick, and good morning, everyone. Q1 was indeed a strong start to the fiscal year. Once again, we surpassed the high end of our top line growth and profitability guidance metrics. Notably, and as Rick mentioned, we had a strong expansion quarter with a dozen 7-figure expansion deals, many of which have planned log management deployments. The building block fundamentals that serve as leading indicators of future growth potential, continue to create traction in the company. Specifically, we are seeing growing momentum in large deal activities expanding tool and vendor consolidation opportunities, building execution with our partner ecosystem, most notably with GSIs, further penetration of our Dynatrace platform subscription licensing model and accelerating consumption and adoption of the platform logs notably.

Let's review the first quarter results in more detail. Please note the growth rates referenced will be year-over-year and in constant currency unless otherwise stated. Annual recurring revenue or ARR ended the quarter at $1.82 billion, representing 16% growth. Q1 net new ARR on a constant currency basis was $51 million, up 13% from a strong first quarter last year. Expansion activity was robust and particularly strong in our North America geography and our GSI channel. In Q1, we added 103 new logos to the Dynatrace platform. Our average ARR per new logo was over $130,000 on a trailing 12-month basis and in line with our target land size. Once customers experience the value of the Dynatrace platform, they have been quick to expand their usage.

Our average ARR per customer continues to increase, reaching nearly $450,000, highlighting the ongoing adoption of the platform and business value we provide to customers. As we have shared previously, given the significant cross-sell and upsell opportunities in our enterprise customer base, we believe the average ARR per customer opportunity could be $1 million or more over the long term.

The strategic relevance of the Dynatrace platform is further reflected in our gross retention rate, which remained in the mid-90s. We Net retention rate, or NRR, was 111% in the first quarter, an improvement from the prior quarter. Our Dynatrace platform subscription licensing model or DPS continues to gain traction and adoption. We now have over 45% of our customer base and over 65% of our ARR on DPS. DPS customers with full access to all our platform capabilities, adopt roughly 2x the number of capabilities than those on a SKU-based model. They also consume at a much faster pace with consumption growth rates nearly 2x those on a SKU-based model.

We have seen particularly robust consumption growth with customers leveraging logs management, our fastest-growing offering. This strong consumption sometimes accelerates use of a customer's original commitment, resulting in either early expansion or on-demand consumption, which we refer to as ODC revenue. In Q1, ODC revenue was $11 million. Historically, ODC revenue was recognized in the quarter it was incurred with quarterly revenue variability driven by DPS expiring commitment dollars that are much lower in the first half than the second half.

Now that we have a full year of history with ODC revenue accounting principles require us to estimate the amount of ODC revenue that we expect to receive over the next 4 quarters and recognize that amount ratably over that same period. The result of doing so, yields a onetime cumulative true-up benefit of $7 million in Q1. The simple way to think about it is we delivered $4 million of in-quarter as incurred ODC revenue and $7 million of revenue accrual -- going forward, ODC revenue will have much less quarter-to-quarter variability and for fiscal 2026 should be in the range of $8 million to $9 million per quarter, give or take, depending upon weather and how much our incurred ODC in the quarter varies from our accounting estimates.

Moving on to revenue. Total revenue for Q1 was $477 million, growing 19% and exceeding the high end of guidance by approximately 200 basis points. Subscription revenue was $458 million, up 19% also exceeding the high end of guidance by nearly 200 basis points, driven primarily by the incremental ODC revenue I just mentioned.

Turning to profitability. Non-GAAP operating margin was 30%, exceeding the top end of guidance by 150 basis points, driven mostly by revenue upside flowing through to the bottom line. Non-GAAP net income was $126 million or $0.42 per diluted share, $0.04 above the high end of our guidance. We generated $262 million of free cash flow in the first quarter. Due to seasonality and variability in billings quarter-to-quarter, we believe it is best to view free cash flow over a trailing 12-month period. On a trailing 12-month basis, free cash flow was $465 million or 26% of revenue. As a reminder, this includes a 700 basis point impact related to cash taxes. Pretax free cash flow on a trailing 12-month basis was 33% of revenue.

Finally, a brief update on our $500 million share repurchase program. In Q1, we repurchased 905,000 shares for $45 million at an average share price of just under $50 -- since the inception of the program in May 2024 through June 2025, we have repurchased 4.4 million shares for $218 million at an average share price of just under $50.

Moving now to guidance. While demand remains strong, we continue to take a prudent approach to our outlook with 3 factors in mind. First, we are still early in our fiscal year. And while Q1 was a strong start, we do not want to get ahead of ourselves. Second, we have a growing pipeline with an increasing number of larger, more strategic tool consolidation opportunities. These types of deals come with increased timing variability and longer duration to close.

Lastly, the fluidity of the macro and geopolitical environment remains a constant. With that as context, let me summarize our updated full year outlook that we detailed in this morning's press release. We are maintaining our full year ARR growth guidance of 13% to 14% in constant currency, while passing through the incremental dollars from the weakening of the U.S. dollar since our last call. Full year ARR is now expected to be roughly $2 billion. While we do not guide to ARR quarterly, we continue to expect first half and second half constant currency net new ARR seasonality to be roughly consistent with last year.

Moving now to revenue. We are raising our total revenue subscription revenue guidance by $7 million in constant currency to account for the revised ODC revenue estimate accounting treatment. This required revenue recognition approach effectively record some revenue from fiscal '27 into fiscal '26 and was not factored into our prior guidance. Total revenue is now expected to be between $1.97 billion and $1.98 billion, and subscription revenue is expected to be between $1.8 million and $1.9 million, both up 14% to 15%. This revenue guidance includes $35 million to $40 million in ODC revenue.

Turning to our bottom line. We are maintaining non-GAAP operating margin of 29% and free cash flow margin of 26%. While the weakening dollar is a tailwind to the top line, it is a modest headwind to margins, given our expense mix is heavily euro-weighted.

Finally, we are raising non-GAAP EPS guidance to a range of $1.58 to $1.61 per diluted share, representing an increase of $0.02 at the midpoint of the range. This non-GAAP EPS is based on a diluted share count of 309 million to 310 million shares. Looking to Q2, we expect total revenue to be between $484 million and $489 million. Subscription revenue is expected to be between $464 million and $469 million, old growing 15% to 16%. From a profit standpoint, non-GAAP income from operations is expected to be between $140 million and $145 million or 29% to 29.5% of revenue.

Lastly, non-GAAP EPS is expected to be $0.40 to $0.41 per diluted share. In summary, we are pleased with our strong start to the fiscal year. We have a proven track record of consistent execution and delivering a of strong top line growth and profitability. While we continue to take a prudent approach to the near-term outlook, we remain optimistic about the fiscal 2026 growth building blocks, and we remain focused on investing in growth initiatives that we expect will drive long-term value.

And with that, we will open the line for questions. Operator?

[Operator Instructions] Our first question is from Koji Ikeda with Bank of America.

Really nice performance here. I did want to ask you a question on the guide. Jim, you gave a lot of color and I appreciate that in the prepared remarks. But why not raise the constant currency guide DPS is sounding strong, logs is sounding strong, ODC is ramping nicely. And so just wanted to hopefully get additional color there on the guidance.

And then 1 additional question on the guidance methodology. Could we, as investors just always anticipate in fiscal 1Q going forward that we will not be getting updates to the currency AR guidance?