Dynatrace, Inc. (DT) Earnings Call Transcript & Summary

Welcome. Thanks for joining us here and for those of you who made the track here to Vegas to see us in person, and then also those of you who have joined us online. Thank you very much. My name is Noelle Faris. I am the Vice President of Investor Relations here at Dynatrace, and we've got a packed one-hour investor session, and I'll just set the expectations around lay of the land and what you can expect. So we're going to start it off with Rick and Bernd. They're going to give brief overview, just to sort of level set folks, especially for those who weren't here in person, just on some of the things we've been talking about in the last sort of 1.5 days. And then we're going to invite the members of the leadership team on stage, and we're going to do a moderated Q&A session. So I did solicit questions for that, and we consolidated it and I think that's really great topics to cover. But we are going to give you guys an opportunity here in the audience to ask questions at the tail end of this session. And just really quick, too. The intention of this session is not to be an extension of last week's earnings call. We really want to try to kind of keep the dialogue focused on the things like market opportunity, go-to-market strategy and sort of R&D road map. So with that in mind, I will quickly before I turn it over to Rick, do the needful and I promise, I'm not going to read that. I couldn't if I tried. But you guys know the drill. We may make some forward-looking statements during today's session, and we disclaim any obligation to update those statements. So they are considered to be as of today, February 5. And so with that, I will turn it over to Rick McConnell.

Thank you. Good afternoon. Oh, come on. Come on, I know lunch has happened. Good afternoon. All right, there you go. You have socks. So you're ready to go. I'm going to spend just about 5 minutes, 7 minutes upfront here. And as I was looking at this presentation, it occurred to me that virtually every one of you in this room could at this point, give this presentation for me, but I'll do it anyway. And it is to get us all on the right mindset of what are the core messages. What do we really want you all thinking about in terms of our opportunity at Dynatrace. So let's kick things off. As we have said many times, the cloud is a huge factor. Why? It's a huge factor because it results in enormous quantities of data, massive increasing its complexity and foundationally it is, as we believe, impossible to manage that amount of data manually, just impossible. And of course, AI and other factors are contributing to that complexity to that amount of data and to the difficulty in managing environments the way organizations used to. Now one of the elements progression that we see is the orientation from data and dashboards, red, yellow, green indicators. I can't tell you the number of customers that I've met with across the planet. That has basically said, "Let me show you my network operation center." You walk into a network operation center, it's filled with dashboards. And my question is always the same, which is, what do you do when something goes red? And the answer is, "Well, we call a big meeting, and we try to figure out what to do next." And that process kicks off a long array of activities. Dashboards in the current world, we would say, are not enough. Obviously, you want dashboards to provide indicators, but you really need insights and answers. As Dynatrace, as we say, we want answers and intelligent automation from data because ultimately, it is those insights and answers that lead to automation that provide for auto remediation to enable you to manage your environment. Our vision, as we've stated it since really the day I arrived more than a few years ago at Dynatrace is to help create a world in which software works perfectly. Well, if something breaks and you have to fix it, obviously, didn't work perfectly. So auto remediation and getting in front of issues before they happen is critical to being able to manage these impairments. We start with Grail. Massively parallel processing, data lake house, all data types. We extend that to include Davis, multiple AI techniques. We are the only observability company on the planet that has and utilizes all of these techniques to try to create automated response. We add to that automation engine. This enables us to action those insights. And finally, increasingly, here to perform this week, what I hope you really seen is the shift left or as one would say, expand left or extend left expansion to other personas. Not just central IT ops, but also do include SREs to include platform engineering, to include development teams. We believe that holistically, it can't just be about end-to-end observability because we capture all data types. It's got to be all data types, but for all teams using a consistent solution that enables them to instantiate or execute their observability strategy. And that's what we're really after. All data for all teams, common platform that ultimately yields auto remediation capabilities through automation because you trust the answers that come out of that environment. And then i'll end with just the this notion of -- so where does growth come from for Dynatrace? It clearly comes from the market factors that we talked about in earnings call last week, of course, AI cloud, as we discussed it earlier, of tool consolidation because there are too many tools. For those of you walking around here at Perform, who've talked to customers, kind of breakout sessions, I'm hoping that one of the elements, one of the trends that you heard was the desire to consolidate more and more with Dynatrace. I certainly heard that. I hope you did as well. But there are also several key growth drivers for Dynatrace ourselves. AI ops, but not just AI ops, which we've been using for more than a decade, also AI observability. Make no mistake about it, we want to be the observability solution for AI observability workloads. Because of the magnitude of data, we believe we can do that better than anybody else. And we are investing aggressively to go after that. Log management, absolutely critical, enormous market, we believe it is incredibly ripe for disruption. Companies are worried about how much they're spending on it and the value they're getting from it. We believe that at a better price point based on our included queries pricing model, plus the ability to integrate logs into your overall observability framework, you can get to a better answer. We talked a lot about our go-to-market strategy, expansion of the number of reps focused on segmentation. Dan will be up in a minute along with Laura, and they can talk more about that. And finally, DPS, pretty odd topic these days. that is really driving enormous consumption growth, almost double the rate of consumption that we're seeing elsewhere with our legacy pricing models. 35% of customers on DPS, 55% on the ARR and continuing to grow, huge catalyst for the opportunity ahead. We're excited to take your questions. Before we do that, I'm going to have Bernd talk for just a few minutes and then we'll open up the panel, and we look forward to your questions. Thanks very much.

Thanks, Rick. Hello, good afternoon. So Dynatrace has always grown on the heels of growing complexity. And actually, this is the #1 reason why I'm so psyched about the whole AI hype. Think of it because, yes, it's just bringing the next exponential growth and complexity sort of we've all discussed about containers, micro services, Kubernetes, and thought this is complicated and complex with 50,000 pods or whatever per cluster. We are now planning towards supporting the 1 million out there because when AI is moving from simple chatbots to the rig interface, to fine-tune models to multimodal to agentic AI, it is just piling up and without having any observability, traceability, what's going on there, you can't control AI from both technical reasons, cost reasons, experience reasons, also for responsibility reasons. So in order to do that, actually, the data volumes is higher. The data that you have is heterogeneous. And the systems are larger. So how do you tame this? And this is, I think -- I don't think only I know it. We are in the best position actually to solve the challenges of today and even more those of tomorrow because we are the only ones who actually not just surface data of different types, we actually put all the data into context and only data in context allows the smart AI that we call Davis AI because we are also the only vendor who put 3 types of AIs together, predictive, causal, maybe you should know that causal AI is actually learning instantaneously and then all the generative AI is everyone else is doing. So -- and by having the context and now look at this from infrastructure, from applications from the AI stack, end user experience. And this is all the differentiator. Even the business level because we have business events that actually customers really love and put that into context, not only for the use cases of observability because workloads need to be also secure. And by the way, the whole area of security is in the [stone age] of automation. And we believe that this is our huge opportunity, having that context and bringing vulnerabilities, security posture, hyperscaler posture as well as all the data for detection and response in proper context allows our customers to automate like never before, including with their growing -- ever growing exponentially growing number of workloads that they are running. And this is setting up our future that I believe is very bright. This is all on the heels of key components because with what Rick Goszo had brought up GRAIL is massive parallel processing data lake house is it that we are the only ones who provide true contextual analytics. And this gives answers not only, oh, here is an outlier of data, but actually, here is an impact because here is a change that calls there, that calls there, that calls there. So we put the actual symptom to the root cause in context like no one else. This is also why we are the only ones to help with a reliable automation because only Davis causal AI gets a real-time view on the IT infrastructure and systems and therefore, also because it causes, not just correlates, understands the dependencies in real time, can give you a precise answers so you automate further. And this is also where sort of I explained already the Davis AI, the artificial intelligence part. And the last part is, I mentioned, sort of the importance for security that do drive automation forward because today, the whole security areas way too siloed, way too much manual. This is the key point. And this is also where Dynatrace here as a platform has the advantages to not only bring the data together, bring the different data types together, but also de-silo the approaches on top of that as a platform with an automation engine with predictive AI, enables to automate in a way to remediate faster or to prevent, but also to collaborate, and that's an important point because we not only care about one audience, we care about multiple audiences there. And this is actually the queue to the next sort of slide here because we care a lot to figuring out sort of where are the future budgets of our customers. Obviously, you all know this now everyone invests into AI, but how do you build AI apps. It's actually the cloud-native teams and the AI native teams basically hook up the services because there is no standalone AI app, and there is all cloud-native apps want to have AI. So those basically extend. So what this means is that we have actually realized that it is the best potential for our growth actually to extend our audiences as also Rick already alluded and provide Dynatrace to an additional type of audience that we never catered before, particularly the developers, particularly the cloud and the AI native developers. And this is why we have created new experiences in Dynatrace and continue to do so. So we rapidly have released new apps in the past quarters and continue to do so throughout this year. So you will see a whole blast there as well. But also with that, we have a focus on all the announcements that we also provided yesterday on exactly that audience, that creates this model, new digital services. So basically, where the budgets are. In this audience of cloud and the AI natives, what do they want in order to automate actually. So first, to take on more responsibility is about production. Those responsibilities include not only availability but all the security as well. This is why these audiences of cloud and AI natives actually expect that observability and security features convert. And they also expect that it is easy to automate. And this is also where we have seen massive inroads with customers who are taking these cloud and native approaches, for instance, to integrate Dynatrace into the entire software delivery life cycle on one hand to even observe the life cycle, but on the other hand, also to create the process of platform engineering because platform engineering provides one hand the way more automated approach to deliver software, but at the same time, also allows more self-service to developers. And as we probably all know, developers are key for us to be early in the life cycle of new digital software projects. And this is also why the announcement here have focused also on developers. And I'll now quickly walk you through those 5 key areas. So the first one is that we have announced preventive operations. So what does this mean? I mean Dynatrace is already the best in automatic root cause analysis. And on the heels of this, you can remediate first. But preventive operations is actually taking additional predictive AI features and combines that with actually recommendations on how to remediate and accelerates, therefore, even the ability so that you can detect problems before they occur and so you prevent them from happening at all. And this prevention is key also because you have as a company always to be resilient. And governments around the world force enterprises actually to level up their compliance. Compliance shifts from point-in-time compliance to be continuous compliant. What does it mean? Containers compliant means you have to automate. So -- and this is where we are helping customers to automate 80% of all the repetitive tasks. The next point is because compliance and resilience already integrates some converges, sort of if you need more evidence here is it that observability and security is converging, it is that actually the security area of cloud native wants to be deeply integrated into their processes. And this is why we have actually extended Dynatrace here also to have in addition to the vulnerability, real-time or vulnerability analytics in Dynatrace in the detection and response functionality and also the cloud security posture management because we believe that these 3 components is exactly the package that cloud and AI natives need. So now with this additional extension of personas to also security teams within the sort of DevSecOps processes, we also see that reaching out to the developers needs actually help because, I mean, you all might know shift left. Shift left means the developers take on more responsibility. We think that's not the right approach because enterprises and executives care about productivity of the developers, right? And how do you get that? Not by let everyone do what they want and also this kills any compliance, so the best way for all of them is to keep our productivities by extending to the left. What this means is that you still have central teams, but this is the more modern SRE type of teams, who maintain consistency and provide self-service to the developers and the developers have then the tools they need in order to leverage observability for their troubleshooting for their optimization for AI, for security, for self healing, it's easy like never before, but it remains on one Dynatrace platform. So this drives productivity a lot because we know, for instance, the just announcement of Live debugger, reduces MTR, 40% eliminates feature flakes 80%. So there's lots of value. And then finally, we also announced the extension of AI observability. So now over 40 different technologies, plus also the ability to report on guardrails so that we can help customers not only with the technical and security aspects of their AI implementations but also of the more biased hallucination kind of responsible areas. So if you bring all this together, think of this what we have here. We have the scale to all deal with the modern large-scale applications that all move towards AI, but we also have the platform that allows the teams, the different that are involved in our customers actually to collaborate properly, to be successful with Dynatrace like never before. And finally, we are also here in the best position to leverage all of our data to bring it up to an executive level with business observability because executive cares a lot. So with this, this was my summary. I'd like to call out the rest of the team. Thank you.

Okay. So I think thank you, Bernd. That was excellent. Good recap of the last day and a half. So I guess, why don't we start there Bernd with just what -- there were a lot of announcements. And so are there any ones that sort of stand out in terms of -- from an investor perspective, potential for more growth opportunity.

Yes. So to me, definitely, the most important is the resonance of the focus on the cloud and AI natives. This is where everyone sort of eyes how do I get my AI powered services faster up and running and sort of this is where those announcement fits clearly because actually, all of them cater to the audience. And I don't do the run down now, but sort of that's exciting. What I also found exciting is actually that already yesterday in exchange the whole thinking of extend to the left was picked up right away by the presenter, which also tells me that for us sort of reaching out to this additional audience is really very welcome.

Great, great. And so maybe Steve, kind of adding on to that, there were a lot of use cases that -- and customer examples that were shared, just in terms of product adoption, where do you think we've got an opportunity to kind of further expand within our customer base.

Well, I mean there's lots of opportunity, as Rick was talking about with consolidation, and I was talking about that a little bit the workloads are growing. Consolidation is not just about I want to deal with fewer vendors or simplify procurement. It's that they really need a different type of system and approach, and they want to bring those worlds together. So there's observability convergence. There's the expansion into cloud native. There's been a lot of interest in terms of the business views as well because I think that's something this industry struggled with a little bit, and we have unique capabilities in the business events to bring that forward. That's been a counting the times award has been set over the course of the last 2 days, that one might be near the top. And of course, there are certain areas that we have a greater opportunity to penetrate faster. I think we've really seen an uptick in logs over the last couple of quarters and really starting to see that catch win.

And so maybe jumping to GenAI. Obviously, it was a big topic of conversation and everybody's talking about it externally as well. But what does it mean for Dynatrace in terms of just the acceleration of GenAI? And where does observability sort of fit into that. Bernd, if you could take that?

Yes. So as alluded before, for us, it's a fantastic opportunity because GenAI will be both occurs in the blessing and the blessing is that it does help and provide fantastic value for many use cases. But also, it will cause issues as every other technology. I mean I mentioned before, just the number of instances, but another example would be think of now codes being generated with GenAI as everyone now tries to do more of this. So we generate code that no one understands anymore exactly why it was built this way, then we use another AI to secure, then we use another AI to fix it, then we use another AI year to review it. Very well this lead. This is a recursive problem. So now then you have an issue in production to use another AI to look at this. How will this work, you basically can't do anything without observing that whole miss sort of that is piling up here. And If I could argue, okay, then even observability feeds data into AI, of course, yes, that's Dynatrace, right? So this is what we are doing, and this is why it's a fantastic opportunity for us.

Yes. I'd like to add on that just really quick because if you look at Dynatrace versus some of our competition, one of the things that we've always excelled at is the ability to understand complex environments and discover them where sometimes we've had competitors or do-it-yourself, where they've gotten a little bit of a benefit from they build the service so they know the service. They know exactly what metrics to instrument and it's all very manual, but it was okay because it was just that manual visibility that they required. You start doing what Bernd was saying, you have complexity, all of a sudden, when you don't know how the code was written when you don't know some of the intent you need capabilities that Dynatrace uniquely brings around the ability to do the auto discovery, to learn the environment. That's a really key important area that I think the more GenAI is used to build apps the more developers themselves are using it, the more you need something like Dynatrace to discover and provide that layer of intelligence beyond just the simple instrumentation.

I would just add that generative AI from Dynatrace, we would argue, is not like any generative AI from any other observability provider because it is accessing underneath a deterministic data layer. And if you think about that, where do the problems occur in hallucinations, where do the problems occur in GenAI. They occur when the underlying data store can't be trusted. In our case, the data store can be completely trusted because it's constructed with causal and predictive AI. So generative AI or copilots accessing a deterministic data store in the form of GRAIL is an incredibly powerful and massively differentiated solution.

Great. so then we'll shift from Gen AI, and I want to talk a little bit more about the personas that was a lot of the top of conversation, especially from a left to more of an extend left. So maybe can we talk about how Dynatrace has evolved to expand the use of the platform to a wider audiences. And maybe we'll lead with you, Bernd, but please, anybody else who wants to jump in on that.

Yes. So pretty much the entire history of Dynatrace. We always worked our path operations, operations, operations team. And with being coordinative sort of on our sales, they have already internally extended to the lift a long, long time ago. And now finally, customers are ready to do so. So -- and this is why it's not the perfect point in time to actually help customers to all to go through that process to sort of not just have global operations and say, okay, you have to fulfill my rules, but actually make it collaborative effort on a so-called platform engineering approach to allow developers and site reliability engineers, DevSecOps to collaborate together on this. And this is why I extend to the left and not just shift there because you can sort of -- you use observability and security centrally, but also equip develop us with their self-service so that they can fulfill their tasks. Okay.

And this will be the last one for Bernd, and we're going to shift into go-to-market. So one of the questions I've been getting in the last -- since earnings call and then yesterday during our cocktail reception with some investors was this whole notion of kind of the R&D road map and a lot of focus on logs. And maybe if you can expand around what does that mean in terms of SIM. Is that something that you consider in the future?

Yes. So that's a very good question actually. I like that one. Yes, because I've spoken with so many customers on the topic of SIM and all of them told me, yes, this is outdated, and they need something that is more automated. And this fits all this out of the point I made earlier that this whole security area is in its stone age of automation. And this is where we are really setting out there to do something different than just sum, but actually bring this to a massive different level. So in a nutshell, take the words cloud application detection and response. What this means is we are bringing with the help of all of the contextual analytics and DI that we have together, all the vulnerability security area with the security posture area with the data from not just logs, but obviously, lots of logs too, but they had all at the traces. We had all the metrics. We also had the user behavior. We add topological context in there. And they use all that together to actually automate the security issues for customers. And this, of course, includes the hyperscalers, even across hyperscalers because this is how modern applications are being built, and this is what the audience wants to automate today. So the answer is, yes, we go into that direction, but take a massive leap forward.

Great. All right, Dan. At the beginning of this year, we rolled out and this group knows some go-to-market changes around focused on sort of segmentation, investment in partners, expanding your sales motions. So maybe if you can give just a quick overview of sort of where do you think we're at and towards in terms of the progression of that? So maybe even to be U.S. centric, what inning would you put us in.

Probably third or fourth inning. I think we tackled -- we're very open about this. I think we're very open that we had a sequence that we were going on. And first, we had an IT 500 priority. We felt that we would add sales capacity density there that we were also, though, I think it's important to note is that we're changing our selling motion there, and that we are going to become more strategic and less transactional in that arena and why we play very well there. We had a number of customers in that space that did a lot with us, thought highly of us and gave us feedback that we had a unique value proposition. So it was kind of easy to bet on that. And we did. Now what we had to do is we had as we were changing just the density, it wasn't just that it was just, in fact, a more strategic selling motion. So we had some people that were able to do that. And we had to bring in some talent from outside, people that had experience selling high-end enterprise and a more strategic selling motion. So we've been on that journey this year. We're very happy with how that's gone. That is one, I certainly knew that there would be some challenges because it's not just about slicing going from 7 to 8 and going to 3 or 4 accounts, that's kind of easy. It was also changing the culture of that and the selling skills that were required. As we're -- over 3 quarters away through the year, we're happy with how that's going. We're seeing the progress going there. We're forming new relationships. And then remember, I think we were open about this, I'm probably repeating myself from last year, but I think it's important to remind you that a lot of people that had 7 or 8 accounts, they were really doing business with 3 or 4 of them. And those were the -- and they kept those. We kept those people, they kept those. That was a risk mitigation. They had relationships. They had active sales campaigns and pipeline. And then sometimes there are 3 or 4 accounts that they didn't have a lot going on. So when we get out to a new app, remember, they're kind of starting from scratch a little bit. They have work to do there. So sometimes they're new to Dynatrace and they had to establish relationships and start building pipeline. But we watch that very closely. I mean, we monitor this on a daily basis, and we're happy with how that's moving.

Anything additional, Laura, you want to add in terms of just role that the marketing team is playing on kind of building out some of the go-to-market changes or how all that is playing out.

So we're aligned very closely in the marketing organization with the sales organization I think a lot of you know I've been here just a year and coming in and just sitting with Dan and saying, "What are your priorities? What are the customer segments? How do we increase investment in the globals and the strategic accounts that we need to do more there?" As he changes out his go-to-market changes, making sure that I'm doing the same thing to align very closely across everything that we're doing. And so it has been a very symbiotic type of change that I've been going through as well.

I just have to add something that Laura won over the entire field sales organization, over 1,100 people. by helping them with this is that we no longer -- we won't want to start off our sales calls of who Dynatrace is. We wanted to start off our sales calls by saying, you know who Dynatrace is. Let's talk about your problems and how we solve them. That was our motion. And Laura, we've made huge progress there. But that's a huge motion. The field is, hey, that's what we want to go in and do. We want to go in, we don't want to explain to Dynatrace. We want to go in and say, "Hey, what challenges you're facing? What's keeping you up at night? What's causing you pain?" And then how can we align our technology there. So I think we're on that journey, and I think that's working very well.

Thank you. And it is a journey. So it started. It doesn't happen overnight. You can't just flip the switch and suddenly everybody knows you. but it is absolutely the right journey that we're on, and we're making it easier for our sellers to be able to talk about Dynatrace and all the advancements. Great. Awesome. So I want to be mindful of time, and I want to give everybody a chance to kind of ask questions in the audience, too, but I obviously still have a lot cards here, but I'm not going to go through all of them, but I do want to give Matthias an opportunity to talk about just what he's doing from his team's perspective in terms of just driving customer adoption and driving that retention rate for us.

Yes. So we have the pleasure actually to prove and fulfill the reality for the promise we gave upfront. So I mean that's the nature of the game, the professional services team, the success team, the support team. They are working with our large customers in making that journey overall for [indiscernible] success. So adoption has multiple facets, that's license consumption. So we sell DPS models that give free access to all the capabilities is really about going use case by use case, audience per audience and refer back the value increment into an ROI or business outcome conversation. So our customers can go back to CTO of sales and say, this is why you use Dynatrace. This is the improvement. And that's our next step in the journey. So we can accelerate that consumption out of the base. So that's pretty much what we do, and that's what our mantra mission is.

Okay. So I'm going to shift over to Jim because I'm going to ask the question that was a topic of the conversation last night as well, which is on-demand consumption before I do that. Once we're done with Jim, we're going to be circling, so you've got Hannah and Greg here who have microphones, so please flag them down if you have a question. But in the meantime, Jim, so on-demand consumption.

Never heard of it.

Topic of conversation, right?

Do you think there's going to be time for more questions after we [indiscernible].

We'll see. Well, this will be -- this is a little bit of a lighter side. One of the things that investors have been asking is, so what does that mean in terms of metrics? So how should they be thinking about the company? Is it ARR? Is it NRR? Is it now ODC or subscription revenues? so maybe you can talk about that, and then we'll move on to....

No, that's -- I was going to comment on Matthias' point earlier around driving adoption, driving consumption of the platform. I'd say it's been a cultural change, I think, for the company. And DPS is a wonderful vehicle to be able to allow for that. You're getting full access to the platform. And so it's done exactly what we wanted, which is people are consuming faster. They could consume 2x the number of capabilities of kind of our legacy oriented SKU-based customers. And so that vehicle is really working very, very well. We talked about the fact that they're growing at 2x the rate from a consumption perspective of SKU-based customers. And so that was our thesis. Our thesis was to get them on board. If they like it, they would consume more and we're seeing that play out. I do think -- we knew there would always be some level of kind of on-demand consumption when we put the model in place, but we actually thought it would be more modest than it's become. And we're realizing here that on-demand consumption is going to be a real revenue stream for company. So to your point about what are the right ways to look at kind of leading metrics. I think ultimately, subscription revenue is, I'd say, ultimately going to be a north star for us. It's a journey. So I think in the interim, the NRR still are very important. But you have to look at ARR and NRR in the context of what's happening also with on-demand consumption because what happens with on-demand consumption could affect ARR and NRR because the timing of when something turns into ARR and NRR will be different. But at the end of the day, people are getting value from the platform, growing subscription revenue, so I think that's ultimately where we're landing. I'd say it's a journey. We'll provide metrics for customers or for investors, I should say, for all of these things to help you on the journey as we go through it.

Okay. And with that, we'll open it up. So go ahead and circulate with the microphone.

I want to ask you [indiscernible] and DPS-based customers will always grow faster than non-SKU customers or both of them will converge at some point.

So I would say that initially, when we go on to DPS, there was a bit of -- I even said it to investors a bit of sampling by us for customers that were going to go into DPS and consume more. But if I'm understanding your question correctly, that I then what we're learning on this journey is that when customers are committing, they're committing with like 100% certainty that they're going to spend to their commitment. We do the same thing internally. When we make commitments, either with the hyperscalers or someone else where we're making very large commitments for. We want 100% certainly we're going to spend that. And so their commitments are sized that way. But we are finding customers are willing to budget. They're willing to budget for consumption over that specific amount. And so I think we're learning in this journey that this value chain of kind of committed contracts and consumption on the back end is really the way customers want to consume. And I think what we're also learning is that one of the things we've done a very good job of Bernd and Steve and team is building up the telemetry to be able to forecast for customers when they're consuming. We're giving them alert. So there's no surprises in the model. We are telling them how they're consuming, whether they're consuming fast or whether they're consuming slower. And so there's a lot of transparency in the model. And as we talked about, there's no penalty there's no penalty for exceeding your commitment. We're not charging like some of our competitors do for overage premiums for that. They pay the same unit price that they were previously. So it's just a really customer-friendly vehicle that some customers will manage it in different ways. But I think it's playing out that we were hoping.

And just to give you a field perspective of that, we get a lot of positive feedback from customers on the commercial model. They don't want a model that is trying to get them. They want a model that's very friendly and flexible. And I think we played the long game on this model and saying, "Hey, if you have a model that customers are giving you positive feedback for it, I get that a lot." That will serve you well for the long term.

Just one small product add to that too is I don't think you can underestimate that when people go into initiatives, sometimes they don't know exactly what's going to be next and where it's going to take the next turn. And with the platform subscription, they have access to all capabilities. I'm sure we've established that before. So not only do they find new ways to grow and accelerate, but as we add new capabilities, those are auto added to the vast majority of customers' rate cards as well. So as we come out, as we launch new capabilities, those are immediately available to those customers to pick up without a new sales cycle. Obviously, they're going to test and things like that, but it's a very easy way for a customer to consume more.

A good example being what was announced over the last 2 days. That will be available to customers.

AI observability. We had Peter from Northwestern Mutual. I'll talk about how they turned it on and under now. This is someone who is a part of their data management team. He was a part of observability. They put those -- tied those dots together. And within an hour, he's using something that is being monetized through existing rate card capabilities, growing that out, getting the broader view across that platform for something that they did not know they were going to do with that same sort of, for thought, it was a point in time ability to take advantage of that power.

All right. I think Julian has the mic over there.

Maybe 1 for -- Julian Medick from Decade Partners. Maybe 1 for Dan. Thanks for the comments on the success that you're having in IT 500. I was wondering if you could broaden the aperture a little bit and talk about further down market, which has historically been a big part of Dynatrace's success in the kind of Global 15,000, and what you're learning there, and what your priorities are heading into the next financial year?

Yes, it's a good question. I think you're getting ready. We have kind of a road map that we're sharing with the board, so I'll give you a little glimpse. So we -- as you know, with this disruption and change in segmentation. So we have to really monitor how much change do you inject at one time. You have a road map, you have a multiyear road map on go-to-market. And you say, okay, how do we stagger this so that we can continue to show growth to investors and so forth and also do our transformation. So we stage it. I think the IT 500, we saw that as something we had to do, would take a while. We had to start early because it would take a while for that to actually deliver the fruits of that. But we all look at our transactions, and as we go into '26, we'll be implementing things to -- we'll sell start hitting on another cylinder of the engine in our transactional business. So we'll be adding that to our FY '26. I think there is a opportunity is a big part of our business. It's continued to be strong as it's been for a long time, but we want to accelerate it. So we'll look at how we accelerate our transactional business in FY '26.

And I think we have Will over here, yes.

It's Will Power with Baird. Questions probably for Bernd, whoever wants to take it on the security front. You announced the cloud security posture management product I just would love to get perspective on the strategic fit. Was this something customers were asking for? I'm just trying to understand how it fits with the broader application security portfolio.

Yes. Absolutely. So yes, this has been asked for a lot, especially, and this is why the whole push is also for cloud and native teams because in sort of the other setup is very different. So typically, in classic security organizations, it's very seasonal driven. But in cloud native setups, it is development team driven. And the development teams need, therefore, an offering also for their hyperscale setups that they can automate as part of the rest of their software delivery life cycle. So therefore, they look into modern offerings for that matter, and this is exactly our opportunity here. And also the posture management and vulnerabilities. Those are the initial steps. And once you have rolled out, then you look at all the threats and exploits. And this is why these 3 pieces together give exactly both cloud and AI natives to package the need.

And then I think Matt has the mic.

Matt Hedberg. I think when I think about the path to sustained 20% growth, I think there's a lot of drivers. And obviously, a lot of performance has been on the product side. But when we think about the go-to-market side, I wanted to go back to back because it seems like there is a real opportunity there. And the question was like down market. And I guess, when you think about what are those investments, we know the GSIs can be an important part of the sales motion. So I was wondering how much of its internal investments in bringing in new sellers to target even a wider aperture or how much of it is like leaning into these partners that we all talk to. It seems like it's a natural fit for you guys.

Yes. I think, Laura would weight in this as well. I typically go with an -- and strategy. So I try not to. But I think the latter, the partner piece, it if you think about where we're activating 3 key parts GSI actually would take you more upmarket. If you look at GSI is going to play as a partner, typically, whether it's center, Deloitte and some of the others in your IT 500. I think that's where they spend more of their time I think as you go down to the transactional business, you have a regional players that are there, so our regional partners, and then what's critical and one that we are spending a lot of energy in really, I would say, is still in early days, early innings as we use is our co-sell with the hyperscalers. We have activated huge initiatives with hyperscalers. That is a huge motion for us in that transactional business. And so we -- I think it's that -- and then we'll add capacity. We will continue to add capacity. Down market is is our bread and butter. We do that as a natural evolution of our downmarket business, but I think where you get really acceleration is on your partner side of that.

And then I'll add. You mentioned performance of big product event. It is a customer event. I look at this as a customer first. We have over 50 customers here. So a lot of product innovation with the customers talking about what they're doing, and it has been amazing for those that have seen the mainstay journey of the breakouts to have them talking about the value that they get from Dynatrace. And so that's where we start. We start with the customers, just talking about it. And that is not just from Dynatrace, but it's with our partners. And I know I have a lot of conversations with the hyperscalers and GFI, my counterparts, CMOs or their marketing teams on what can we do? We've been building up the partner marketing organization, along with the partner team within Dan's organization. They are [indiscernible] hit together. On how we're going to not just utilize our partners as a sell-through. This is a marketing opportunity. This is a co-sell opportunity. This is how do we design programs together. There is so much activity happening there. that we see big opportunity for us as well going into this new, what is our fiscal year with our -- all of our partners.

And that we have the mic over here. Thanks.

Karl Keirstead at UBS. I wanted to go back to a comment you made on a couple of occasions focusing on the cloud and AI natives. Could you define what you mean by that. And if what you mean or pre-IPO smaller companies, how does that sync with the focus on the IT 500? And what's the strategy to displace Datadog given that they've communicated that they've got a pretty good footprint there?

So first on the definition, it is really about all those modern projects that set up typically in hyperscalers. They're API driven. Obviously, Kubernetes containerized or these kind of projects. But also, it's not only about the tech, it's also about the processes, how you develop and deliver software. Basically, in the cloud and the AI native approach, you also have broken up or actually eliminate some of the silos there, here is ops, and here is test, here is that basically have much more a continuum. And this is also why in the cloud and the native approach. You have the Dev SRE and the DevSecOps teams usually part of the same organization so that you have 1 continuing further rollout. And this is also where the beauty of hyperscalers come in. You don't need a decade separate global ops team in order to keep hyperscalers running. This is what the hyperscalers are doing. So -- and this gives exactly those teams more autonomy to accelerate, to iterate faster, to deploy faster, but also gives or sort of opposes the responsibility to take not only care about delivering features, but it poses that they have to take care about resilience, meaning availability, security at the same time, plus and often the care as about business metrics, like, let's say, how is their service being adopted and so forth to look at that. So this is what I see here is cloud native definition.

I think we need to be more direct in that answer to simply say that virtually all organizations at this point are moving to cloud-native, cloud-native workloads. We see 85% to 90% of our customers or more now have cloud-native workloads. They're expanding in banks, expanding e-commerce, health care everywhere. So don't correlate that to SMB approach.

Not all -- I was going to say the same thing we're usually talking about projects, not companies with that definition. Okay.

And then, Fatima?

Fatima Boolani with Citi. My question is for Matthias. Matthias, you spent a lot of time with customers. And so I wanted to get your perspective on what the behavior is in terms of customers on DPS, adopting more diverse functionalities on the platform. If you can give us some perspectives on, hey, are a lot of the DPS customers are actually becoming power consumers of existing capabilities and going to the end with more full stack observability, or has this really galvanized an opportunity for customers to experiment with Grail to experiment with optic, any quantitative wrapping you can put around that in terms of multi-SKU adoption within the DPS base?

Yes. So there's a strong pattern that customers on DPS actually use quite a strong variety of capability modules or whatever. So just this easy access to use Dynatrace in whatever way you want to not be limited to buy a certain SKU upfront, knowing how much that will be potentially or not just gives our teams much easier access to those personas and realizing value while in those capabilities start to grow. And then those customers can still find more budget in another pre-commit or solve that with ODC what Jim was mentioning. So that's a clear pattern. I mean I was here in 40 conversations over the last 2 days, and we are lining up our teams now to bring all that innovation, we are announced again back into the base because people are super excited. Now we don't need a sales cycle to get started. That's the beauty because they have it. And still, if those new functionalities, those new use cases, those new value adds drive a higher and higher level of consumption Then, of course, we're going to book another, let's say, growth deal or a multiyear expansion into that specific customer. But I think that's the motion we are seeing. And it's really about us as Dynatrace together with those customers to find different workloads, new personas, new use cases, new processes, which they were not able to do that before.

Okay. Sanjit.

I was at the afternoon session at the keynote, and there was a leader from the extra practice. And he had this line where he said, AI is just another workload, which I actually thought was quite a constructive comment because what defined to this category is that with compute cycles, the mousetrap changes, the reference architecture, the application architecture changes. When we went to model that to microservices and the Kubernetes, you guys are on top of that and benefiting from that growth. And so the question is that do you sort of agree with that statement by et cetera, saying AI, just another workload, therefore, we're really well positioned to monitor these type of applications, or is the mouse, fundamentally. Is there anything that you're seeing in terms of how customers build applications, and we think about getting to an inferencing cycle and GPU-based workloads and new architecture, is there anything bubbling up that gives you guys a in terms of how to monitor this next wave of applications that are coming online?

Yes. So I think in this sense, there's lots of truth in this statement because the instances and workloads grow and think of agenetic is more or less microservices talking to each other. But yes, the take stake is slightly different in their sort of in the detail. Maybe the biggest thing that changes with AI is that have additional types of metrics like guardrails on buyers and so forth that you would not have otherwise, but sort of on the rest, sort of, let's say, security, it's similar. You still have to take care that there is no P2 data in your prompts that you sent to Generative AI or the like. So yes, this is why, to me, I'm super excited about the opportunity.

Yes. I think if you over simplified a little bit if I'm being blunt, because while I agree with Bernd that there are things that rhyme and there are patterns. I mean the complexity is crazy. I mean if you follow how fast to see the hyperscaler services are going, if you look at the different audiences that get involved, like go back to that Northwestern Mutual example, those aren't all traditional buyers. Like you're yet, once again, creating a necessity for a shared view for collaboration, which I believe was the bias, but that plays to our favor, plays to the strengths of GRAIL to bring these different capabilities together, different insights, different data types. So yes, it is -- it's software at the end of the day. But I think the pace and kind of the hydrogenous environments and buyers is definitely creating new dynamics.

We're going to do 1 more question. We're a little bit over, but I know we started a minute late. So go ahead, Keith.

So am I the last questioner?

You are the last.

So I'll break this into 17 parts. Keith Bachman from BMO. I wanted to ask the question to the panel. How do you become more successful in security? And I will break it into a couple. So the first is you've announced cloud security is something we were talking about last night. How do you -- what gives you the right to win there? And just to give you for an example, BMO is a big customer for observability I think the chances of you winning the cloud security is very small, we use wind it's very formidable competition. The second is, do you actually need to keep expanding the portfolio security in order to win, in other words, try to get more mind share with the security operations people. And the last is just do you need changes to go to market to be successful in security.

Only 3 parts, Keith, I'm disappointed. Should I start? Okay. So clearly, the whole security area is being disrupted with those new modern workloads. This is where the classic CISO-driven security doesn't work. This is also why actually, you mentioned that is actually sort of having their successes there. But I think also what is providing agentless good ease of use and the fourth, but the whole point is that they like is they don't have a platform. They are now saying they're building an agent. They don't have the end-to-end data for context, sort of the point that I'm trying to make is from the foundation of what we provide Dynatrace and extending there to this modern cloud native security workloads, we are in a fantastic position there sort of this, you could argue has a head start and is known, but sort of foundationally, I think we have an even stronger platform than them because also they now have to start actually integrating all their acquisitions. [indiscernible] that far with our platform that we can say this is all cohesive, it's all together and we can now push and draw forward. Dan, do you want to add anything there?

I didn't touch on something, but I'll give you something actually we're very excited about. So we have -- and it's -- I'm going to try to answer your question in this is that we have formed 3 specific strike teams. And what these are, are subject matter expertise that help our field teams. They own the opportunity, but we formed 3 strike teams. And 1 we've had, at least for a while, which is our security team because they bring some subject matter and expertise. And Keith, just to help you understand, one of the things that we do is we try to draft off an overall security plan. We don't -- we're not going to try to change the security. We're going to plug into it. We have a unique -- if you think of runtime vulnerability, we have unique data, unique insights that we like to feed into their overall security strategy. So we're not trying to replace a lot of times. We're trying to give our unique data to that framework. So I think that's one. But also, we did -- from a go-to-market standpoint, we have 3. We have logs. We have digital experience DEM, and we have security, and we have strike teams, which these people are subject matter experts. So as you kind of get deep and into the more complex selling motion, you bring these people in to help augment the field teams to help drive that. So that's what we're doing. We're excited about the strike teams actually. We've hired a new logs person she presented today in front of a main stage. I don't know if you guys were able to see. She's fantastic. She's a great addition to our team. So I know we're talking about security, but I think logs is really important to us and having the right team in place is a big help.

And some of what we do from the marketing side then is also to align to the strike teams so that we can go deeper with more focused programs because we have that expertise. So again, logs done with insights and security, are all core to those.

And the only other thing I'd add to it, Keith, is that again, I started earlier about a culture of adoption the incentives of the strike teams that Dan is talking about is to drive consumption. So their metric is going to be consumption. Our model before wasn't like that. They were a front-end model helping in the security sale. They were not necessarily the person involved in the adoption of the security offering. And we think having that combined with what Bernd was talking about, we'll be able to get better penetration with an and with customers that are already familiar with us on the observability side to be able to extend into security.

Okay...

I wanted to just find a product comment to that because I had many customer conversations on the security topic, and they all distilled it down to one word context. This is what they need. And this is what we clearly have is the best of all, and this is also adding to huge differentiation to, for instance, with.

Keith, I would answer the question this way. I would just say that we enter it similarly every time. But we are going to invest in those areas of security where we have differentiable value. And what that typically means is areas in which observability data matters. We don't want to compete against Paolo. We don't want to compete against CrowdStrike or numerous other parties in the security markets, we will lose, and that is not our strategy that is not our intent. But in areas in which observability data matters, and observe in areas in which agent technology really has differentiable value. Those areas are areas in which we believe we can ultimately compete to win in security.

All right. With that, we're going to have Rick say maybe a lot of -- some parting words, and we'll let you go.

Yes. So just a couple of things to wrap up. First is I want to thank Noelle and Hannah and Greg, I don't know about you all, we interface with that all the time, but Jim and I get to do it every day. And I think they are an incredible team that punch way above their weight. And I hope you agree with that. But thank you to you all. Really amazing, amazing work. The second is, I just want to thank my team. You see some of them here. But Sue, Collin, Nicole, other members of our leadership team, they are rock stars. I would go to battle with them any day of the week or month or year, just love them and I really want to thank you all for making our short number of hours on a weekly basis all play out well. And lastly, I really want to thank all of you. It is -- it's not something that I've experienced often in my career, but I really must say that you all understand our business very well. You take the time to understand it, you take the time to engage with us. We are grateful to you for that. You make us better as a company. And I love working with and engaging with people that make us better each day, and I really do believe that you all do that for us. So thank you for being here at perform. Thank you for your support, and we look forward to our continued engagement in the future. Thank you very much. Have a great day. And you have one time [indiscernible].

The team will linger a little bit if you have some parting questions but other than that. Thanks for coming.

Thank you very much.