Citi's Tech Conference. I'm Tyler Radke, Co-Head of U.S. Software. Thanks for bearing with us with the elevators and stairs. I know I got my exercise going up and down the stairs, so we're happy to have Elastic to kick things off here in the afternoon. We have the CFO and COO, Janesh Moorjani, in the house with us. You know, before we get into the recent results, which I know are very topical, there's a lot of investors in here, they may have different familiarity with Elastic as a company. Can you just quickly give a synopsis of who Elastic is, and how does that vision look with all the excitement around AI?
Yeah, I'm happy to, Tyler, and thanks for having us here today. It's great to be here again in a new venue and everything. So, thank you for that. You know, Elastic, at its core, is a search AI company, and was founded back in 2012 on this premise that the power of search technology can be applied to many, many different use cases. And so anytime you have very large pools of particularly messy, unstructured data, the bigger those pools of data are, the better we shine in some senses. And anytime you're looking for meaningful results or meaningful information within those large pools of data, that's a great use case for Elastic.
So you can think of us at, at our core as a search engine, and we get applied to many different use cases. Search in its most traditional form, the way you think about it, whether that's a search bar on a website or a shopping cart experience or any other way you, you typically think of search. As well as for use cases like security, and particularly within security, the SIEM Use Case, which is fundamentally a data problem, or in observability for logging, or log analytics, which is, again, fundamentally a, a data problem, where you're trying to analyze these large pools of messy, unstructured data.
Over the last few years, as GenAI has become more popular, that's actually been a fairly good catalyst for us in terms of thinking about the way people think about search and the ability to use search- to- solve all kinds of business problems.
Got it. Great. So let's dive into it. You're fresh off Q1 results last week, which y ou know, I think in terms of how the quarter played out from a revenue consumption perspective, you know, I think things looked relatively straightforward, but you had an unforeseen go-to-market impact that, you know, led you to have a shortfall on commitments, and ultimately, you cut the full year guide by a couple points. Take us through, you know, what happened. What was kind of the biggest surprise that you saw during the quarter?
Yeah, I think, you know, as you mentioned, Tyler, looking back at sort of the history for the quarter, all of the metrics like the reported revenue for the quarter, our cloud revenue growth, our customer statistics, the count of GenAI customers, including in the larger pool of more than 100K of ACV, the customer count in that category, I think all of those things played out really nicely for us, including the net expansion rate, which ticked up slightly to 112%. So all of those metrics played out really nicely for us. I think where we had the biggest issue, and the reason it was a dissatisfying quarter from our perspective, was we came up short in terms of new sales, essentially customer commitments or what the sales team sells to customers.
The main reason for that was certain segmentation changes that we made at the start of the year entering the new year. I think most people are familiar that every year, most software companies in the industry will make changes to coverage models and territories and segmentation. We were no stranger to that. In the past, we would make certain changes as well. Over the last several years, as we've continued to increase our focus on selling within the enterprise and continuing to move further up the stack, if you will, we've continued to make changes and modified our go-to-market approach slightly over the years. There was no fundamental shift in terms of our overall strategy from a go-to-market standpoint. We continued to think of...
Within the United States, we continued to think of our accounts as segmented as strategic accounts, enterprise accounts, and then within commercial, you've got mid-market and general business, but broadly thinking of that as commercial. This was also unrelated to the SMB change that we made a couple of years ago, but what we did was three big changes as we entered this fiscal year. One was in the strategic account segment. We added some additional accounts there, but and also added more reps, but the net result of that, we actually have fewer accounts per rep, so a rep's territory on average was smaller, and that was by design, and we moved to much more industry-standard metrics in all of the changes that I'll just describe here.
And we're designed to help our sales teams go deeper into those accounts, penetrate them further, grab greater share of wallet, and it's the right enterprise-selling motion, and we moved to a more industry-standard norm there. Similarly, in terms of our broader enterprise sales coverage, again, similar concept, where, while we added some more enterprise sales coverage, we actually reduced the number of accounts that sales reps carry, quite significantly, which meant that, you know, people can't go to the lowest-hanging fruit. They actually have to go deep into those accounts, build those relationships, and that will allow us to represent the portfolio more fully, to those customers and drive higher adoption across use cases.
And then the third thing we did was we created new greenfield territories as well, and these were accounts where we may not have had a lot of business historically, and they represent net opportunity for us. If you think about the total addressable spend and how much those customers actually spend on various different solutions in these to solve these kinds of problems, it represents opportunity for us, and that opportunity would take some time to cultivate. So those were the big changes that we made. I'll point out that these were mainly in the Americas.
Outside of, and particularly the United States, we did not segment public sector because that has its own, or I should say we did not re-segment public sector because that has its own selling motions within federal and, and also state and local education. And outside of the United States, there tend to be just natural geographic ways in which markets are segmented. A salesperson in France usually won't call on accounts in Germany, for example. So within Europe, you have these natural segmentation limits that occur anyway.
Most of the changes for us were here in the United States, and what happened for us was the changes were bigger than what we had had historically done, and as we implemented those changes, I think where we came up short was in the way those changes were implemented over the course of the quarter, and how one sales rep manages handoffs to the other sales rep, the incentive structures you put along those, just things that you do to try and make that more effective, and I think that's where we came up short.
So the impact of that was really felt in the month of July and particularly the last few weeks of the quarter, because as you think about the enterprise software landscape, like many other enterprise software companies, our quarters tend to be heavily back-end loaded, and when we made the changes in the month of May, we started to really see the effects, or the impact of that, only towards the end of the quarter.
And by then, it was too late to actually change anything within Q1 itself, but we obviously started to put significant actions in place to address that. I think those. We are seeing really encouraging signs of those actions taking hold here in Q2. Many of the deals that had moved out of the quarter have already closed. We've not seen any meaningful shifts in our win rate, so we don't believe it's a competitive issue. The other deals that remain in the pipeline are slated to close in due course, some in this quarter, some in future quarters. I think that was the biggest impact associated with the segmentation.
The other thing we saw, and this was to a much lesser degree, was towards the end of the quarter, we saw some deals push out in EMEA in particular, and I think that was more because of specific budget issues in those customer settings. I don't know that it's broad enough that I would call it a deeper macro issue. We don't have enough scale to be economic bellwethers ourselves, at least not just yet. Someday we may, but I think we saw a little bit of that, which impacted the quarter as well. So we're on our way to addressing the issues and hope to have them addressed in the next couple of quarters.
Yeah. So, I guess going back to the change, and, you know, I think as you described also on the earnings call, this was a pretty broad-based change that impacted, you know, almost every rep in the U.S. and not only the resegmentation, but the introduction of these new greenfields. So I guess when you initially set guidance, did you just think that this was gonna be a pretty smooth transition, or what was sort of the underlying assumption for this transition? And I guess beyond the booking shortfall at the end of the quarter, what were like the signals that you saw that this transition was gonna be a bit bumpier than you had planned?
Yeah, clearly, we anticipated some effect associated with it. And in terms of our approach to guidance, it's been very consistent over the quarters, where we try and incorporate everything that we know into the guide and then try and protect ourselves to a degree for things that we don't know that may come our way. We took a similar approach, and we tried to protect in the guidance to some extent for this issue. The problem is that it turned out to be a much bigger issue than we could have anticipated, and it showed up much later in the quarter.
That's part of the reason why there was a more immediate impact from a guidance perspective looking out towards, the rest of the year. In terms of, you know, the other part of your question around signals, I think the best signals to look at are deal progression through the pipeline. Because so much of it was slated to close naturally in July, we didn't see some signs of that, earlier.
But as we've continued to examine exactly where those deals are, and Mark is deeply involved in this, Ash is personally engaged in this, even during a break over here, I've been dealing with a couple of deals and making sure that they progress nicely, here through Q2. Like we're all down at the individual transaction level for the transactions that are more meaningful, are working on making sure that we're making adequate progress on those, and that's the best indication.
As I mentioned, some of those deals have already closed and that's a really positive indication. In other settings, the feedback from customers is that we weren't there driving the transaction forward with them. It's not like those deals have gone away, or it's not like they've been lost to competitors. So we're still working those and are working to try and bring those to closure.
Okay. I mean, in some ways, it sounds like the customers should be even more involved with it. Or, sorry, the sales reps should be even more involved with customers if they have fewer-
That's the intent.
... accounts to focus on. So I guess in terms of the specific steps that you're taking to remediate this issue, and there's only, you know, one of you and one of Ash, which I'm sure that's helpful getting involved, but what are you doing to like, what were the solutions that you sort of identified to remediate this issue?
Yeah, there's a few things, right? One is just naturally continuing to engage with customers, engage, engage with the accounts. I, I think the second one, that just happens quite naturally, to be honest, is that, it's less of an action, but more just making sure that it's actually happening, is that as sales reps settle into those territories, they're naturally uncovering new opportunities. We are seeing that on the enterprise side as well as, as people engage with the, with the new accounts. You're seeing greater opportunity discovery. You're seeing greater customer engagement in terms of meetings in terms of customer participation at events, where we get called in as executives to engage with those customers as well. And the third is simply just the passage of time as people become familiar with their territories.
If you had somebody that inherited a set of new accounts, then it's gonna take them a while to build those relationships. We are starting to see encouraging signs of that happen as well. I think in addition to all of those things, there were a couple of things that we were planning anyway, launching, and it was not necessarily directly a result of the impact of the segmentation, but those are things that were in the works anyway, and we have done, and we are seeing really encouraging signs of that. The two things I'll call out specifically on that front was we launched an what we call the Elastic Express Migration Program. We launched that at Black Hat.
We've talked about platform consolidation as a theme for a while now, where customers are looking to move off legacy vendors, especially for SIEM and logging, and move on to Elastic. And what we did was, if you think about it from a customer's perspective, they're in that migration trying to minimize costs and minimize risks, and we've helped them minimize risks from a technical perspective through the product in a number of different ways. ES|QL was a great example of a feature that we launched more recently. We launched automatic import for SIEM, which makes the migration a little bit easier.
But commercially, what we did was took a bundle of services which would in order to help the customers through the migration, as well as provided them with some relief from dual vendor costs during the migration period, to construct offers that help them eliminate that friction in the near term, but that are still commercially sensible for us as a company. And we packaged that up and launched that as the Express Migration Program. And that's been very well received, not only by our field, but more importantly by customers who see that as lowering the barriers to adoption. Another example of that was, in addition to all the other segmentation changes we made, at the start of the year, incubated a very small team of technical search specialists.
We had had some success with that in security in the past. We did that with Search now as well. These are individuals who work with customers who are working through their GenAI architectures, thinking about their applications, and they're helping those customers along that journey in terms of how best to use Elastic and our capabilities on that front, and there's so many demands on that team's time, it's really been encouraging to see, so there are some natural things we are doing anyway to help eliminate the friction and drive execution as well.
Okay. Okay, got it. So, so obviously, with the, you know, anytime you have these unforeseen shortfalls, they can be pretty painful. But I think what, you know, investors want to get comfortable around is, how do we not get surprised again? So maybe as you think about, you know, the, the guidance update, which did have a, a decent cut to the guide, even despite a bit of a beat in, in the quarter, can you talk about the assumptions that, that you embedded? Are you assuming that this, you know, suppressed bookings environment continues throughout the full year? Is it- does it resolve itself by Q2? And then I'd also be curious on the EMEA point that you made, which, which does, by the way, line up with, you know, even how Microsoft talked about Azure softness.
Is that something you're seeing continuing here into Q2 as well, and have you sort of downgraded EMEA expectations for the rest of the year?
Yeah, if I think about the broad assumptions, maybe starting with the macro and then talking about deal closure rates and so forth, in general, we've assumed that the macro environment stays where it is, and that includes EMEA as well. We are obviously mindful that some deals took a little bit longer to close, and as I said, I don't know that is necessarily a broad macro issue from our perspective just yet. But we have been cautious in terms of how we think about that part of the business as we've looked at the guide. In terms of the other assumptions that go into the guidance, you know, we have assumed relatively prudent close rates on the pipeline and in terms of just our ongoing sales execution.
The issues that we experienced and the fixes that we've put in place, although we are seeing encouraging signs of progress here in Q2, we have assumed that they'll take a couple of quarters to come back to our normal pace of execution. In the guidance, continuing that philosophy of guiding based on what we know, we've taken everything we know about what happened in Q1, including the current state of affairs in the sales organization, the work that we are doing to address that, and that's all been factored into the guide. As I said, we've assumed relatively prudent close rates, and then beyond that, again, we've continued to protect ourselves against known unknowns to a degree.
Right. Right. Okay. Okay, that makes sense. One of the other topics that I think maybe got overlooked at the earnings, given all the moving pieces on the guide, was the announcement of the return to open source AGPL licensing for kind of the core Elasticsearch product.
I'm super excited about that.
Yeah.
Yeah.
Yeah, so I'd love to talk about that. I mean, I guess what sort of prompted the move at this point? Like, why now? And you know, I'd imagine you'd love to make that announcement under better circumstances with go-to-market issue. But yeah, well, walk us through it.
Yeah, it was clearly unrelated to anything related to one quarter. For those of you that may be familiar with Elastic or have followed the story for a long time, like you have, Tyler, you know that we have a lengthy history. We were founded. Our roots are in open source when we were founded. We used to offer a lot of our software under an open-source license. Over time, what happened was we saw that Amazon was offering a competing cloud service. They used to call that, back in the day. They used to call that the Elasticsearch Service. A big part of our license changes at that time were motivated when we, a few years ago, we said we're not gonna publish our free software under an open-source license anymore.
We still made it available for free, as open code, so you could still inspect the code and play with it. But instead of the source code being licensed under open source, it was licensed under a proprietary license or under the SSPL license, which is again a relatively permissive license that is not technically open source, but looks and feels very much like it, and the intent of the change at that point, a few years ago, was to make sure that we are continuing to protect our IP and that Amazon eventually went a different direction. We knew they would fork the code of the old open source version.
We also settled the trademark dispute with them, and that became the birth of OpenSearch from Amazon. So we felt really good that Amazon has now, for the last three years or so, gone down this path of OpenSearch. And over those three years, we've also built a very healthy and vibrant partnership with Amazon, and you see that in a number of different ways. You've seen us win awards. You've seen a lot of traction for us on the AWS Marketplace. You've seen a lot of technical integrations being built with Amazon. So the partnership is in a really good spot right now.
I think the other thing is all of the hyperscalers have done really well in terms of thinking about a first-party service and a third-party service, both running on their underlying infrastructure, and they're used to managing that as a concept. And so we felt really good about where we are from that standpoint, and so in some senses, returning to open source has felt a little bit like a return to our actual roots. And more specifically, what we did on that front was we took the free and open version, the version that was open code, and put that under not only our Elastic license and SSPL, but we made the source code now available under AGPL as well, which is an OSI-endorsed open-source license.
The important distinction to just keep in mind here is that nothing that was free has gone into... Excuse me, nothing that was paid has gone into free as a result of this change. The only thing that changed is that what was already free continues to be free, except that, instead of being available only under the Elastic License or SSPL, it's now also available under AGPL.
And that unlocks significant opportunity for us on the vector database side, going back to the timing of why now that, you know, a couple of reasons were, one is we felt that we had enough distance, that the competitive issue had been addressed, but importantly, it's about the opportunity in the vector database side. And because AGPL is an OSI-endorsed open-source license, as you think about vector databases and open-source vector databases, it suddenly unlocks a whole set of opportunity for us on that front.
Got it. So you sort of feel like the maybe bottoms-up, grassroots developer adoption of, of the vector database was, I don't know if, maybe it wasn't right where you want it to be, if that's the right way to think about it, but this sort of is an accelerant to that.
It is an accelerant. And I think the adoption that we had was very strong, and you see that in a number of the statistics that we've been printing in every earnings call in terms of customer adoption of our vector databases. You can see that at our user conferences, where we conduct these as tour stops around the world, where you see a very strong degree of engagement. But being open source just unlocks even greater opportunity for us.
Got it. Got it. Okay. Shifting to the products and the GenAI stuff, 'cause I think a lot of that is sort of was, you know, we were distracted by the go-to-market issue, issue last quarter. But just for folks in the room, can you sort of just articulate what Elastic offers in terms of GenAI? You know, ESRE is often used, I think, as kind of an umbrella term to describe a suite of products, but what is your approach between vector databases, different types of search?
Yeah, it's a great question, and you're right, ESRE is sort of an umbrella term. The key word there is really about relevance, which is the R in the ESRE. And if I think about all the features, so ESRE is not a product. Just for those that might not be familiar with our product portfolio and how we go to market, what a customer buys is the Elastic Stack, and depending on which tier they buy, a subscription tier, they'll get different levels of features across all of the different solutions. And if you think about ESRE, it's not a standalone product that is sold separately, but it's a collection. It's the umbrella term for a collection of features that relate to GenAI, and vector search is one of those.
We have our sparse encoder model, we have an inference API service. There's a number of different features that customers use, either simply for vector search or in order to build GenAI applications that all come within that ESRE umbrella. So that's what we have there, and we help customers across all of these. If I think about the rate of customer adoption that we've seen, we've seen every quarter for the past several quarters now, we've seen hundreds of additional customers adopting us for vector search solely in the cloud, right? When we talk about more than thirteen hundred customers now, those are all cloud customers. There's a larger number of customers that are using us in self-managed mode for vector search.
Similarly, if I think about the pool of customers, that's the customers that are more than $100,000 in ACV in the aggregate, which is our proxy for some of our larger customers. Within that universe, there's more than 200 customers using us now for vector search. We've talked a little bit this quarter about a slight shift towards search bookings that we saw, so we're really starting to see these things come together quite nicely.
Got it. And as you think about the competitive environment within vector search and GenAI , right, you have a number of private companies in this space, be it Pinecone or Weaviate. You also have vector database offerings from companies like MongoDB or, you know, even Postgres. How do you sort of see yourself? Like, what type of use case? Is it anything around search, or are you trying to kinda go after the broader vector database market, too, for, you know, GenAI applications?
Yeah, I'm glad you mentioned Postgres, 'cause we actually think they've implemented it the right way and by doing this directly in the query engine.
Yeah.
But stepping back a little bit more broadly, I mean, fundamentally, we view ourselves as a search engine. From our standpoint, there's a number of other players out there. You can always have standalone tools, where you've got some amount of data that is sitting in the tool itself, and you can have some search functionality that is resting on top of that, which will be inherently limited to the data that is in the tool, because it doesn't have visibility to data more broadly within the enterprise. You know, I think those will continue to exist. We fundamentally don't see them as being competitive to the way we approach the market, and from our perspective, search is much more ubiquitous.
With respect to some of the standalone players like you know Pinecone or Weaviate and so forth that you mentioned, our view for a long time has been that ultimately vector search becomes a feature. It's not a product category by itself, and that's a big part of the reason why when we implemented vector search, we implemented it within Lucene, and we implemented it natively into the Elastic Stack. And the...
You know, back then, we used to have some FUD thrown at us around performance, but that has long been addressed, and if I think about what now differentiates us and how we see ourselves winning, you know, to start with, if you think of vector search as a feature, you have to have high performance on that feature, and we compare very well with any of the others out there. In terms of popularity, we tend to be much more popular, simply given the size of our installed base, because we implemented this within the stack itself. And now, with our vector database being open sourced, effectively under AGPL, for people that wanna use that, it becomes an even greater accelerant, like we were talking about.
The other important piece is that in order to succeed from a technical standpoint, we've maintained for some time that customers will need a lot more than just vector search itself. They'll need all the other features that enterprises have become used to when you think about implementing search. That includes a ton of features around things like security aspects or just features that enterprises would come to naturally expect over time, and we have a long history of delivering on those features. Even from the standpoint of economics, we talked in the past about examples like hybrid search and reciprocal rank fusion, which was the technology to enable hybrid search, which allows customers to get the best results across traditional lexical search and vector search without rerunning the search and to re-rank the results.
And you can't do that unless you have access to all of the feature sets that we have. At least can't do it as effectively as we can. So we feel very good from the standpoint of our competitive positioning. I think over time, you will continue to see more innovation. You always do in the technology landscape, and we feel really good about how well we are positioned with our offerings for customers, and you see that in the numbers of customers that are adopting us.
Yeah, and your comment earlier, where you sorta saw more of a mix shift towards search, at least in terms of the bookings, and I think you talked about on the call that search was actually re-accelerating in terms of revenue growth, perhaps outgrowing the total company business. Is that all being driven by AI? And I guess, how close are we to the, you know, ESRE family of products really starting to, you know, move the needle in terms of driving revenue?
Yeah, I think it's largely being driven by GenAI.
Okay.
But in terms of when we start to see that from a revenue perspective, one of the things that we talked about when we entered the year was that we had w hile we had seen some revenue contribution from GenAI in our FY 2024 , we were not expecting to see meaningful inflection in FY 2025 because we do think this is a longer-term play. Like most major technology transitions, we think this takes longer to happen, but ultimately ends up being bigger than what many people anticipate, and so we think of this from a longer-term perspective, and that view hasn't fundamentally changed. On the one hand, we're really encouraged with what we saw in Q1 with the additional commitments that we secured and the customer interest translating into this higher search mix.
but over time, I think that's when we really see a more meaningful revenue impact. Mix shifts are also really based on relative growth rates and can bounce around, so we're not trying to engineer a particular mix shift in the business. So far, really encouraged by what we've seen on GenAI, but we just think it's longer term from the standpoint of how this plays out on the revenue side.
Okay. I know we've spent a lot of time talking about search and ESRE and everything, but I did wanna talk a little bit about the other businesses, too, which are just as important. On the logging and SIEM security analytics side, what have you seen thus far, just with Cisco now, I think, owning Splunk for two quarters now, if I'm not mistaken? How are you sort of positioning your team to go after that opportunity, and have you seen any potential benefits or any, you know, positive signals that you're seeing in terms of being able to go out and capture that?
Yeah, I think, when the acquisition first happened, our view was that the reason a customer is concerned and wants to move away from legacy vendors is usually because of costs, or because of lack of innovation.
Yeah.
And those were the main reasons why people were thinking about adopting Elastic and coming to Elastic compared to some of these legacy folks out there. And that fundamentally hasn't changed, even post-acquisition in relation to Splunk. So we've not seen any big shifts or dynamics play out in front of customers as we are engaging with them on particular opportunities, and we've continued to feel really well positioned on that front. I think customers continue to give us the same feedback that they've always given us about the reasons that they're adopting Elastic relative to some of the legacy players. And our goal over the coming time frame is to continue to try and accelerate that movement.
And that's part of the reason why we launched the Elastic Express Migration program. Features like automatic import, which was a relatively recent feature, will continue to help. So we feel really good about how well we're positioned and the future potential on that.
Okay. Okay, great. And then on security, I'd be remiss if I didn't ask you just, you know, post the CrowdStrike outage and all the fallout on that. I mean, I guess a couple perspectives. Number one, did you see any material share gain opportunity in terms of Elastic's own endpoint products? And then, you know, did that sort of trigger more logging use cases or security analytics use cases that you saw during the quarter?
Yeah, there was no direct impact, and, you know, the CrowdStrike issue, I have a lot of respect for them as a company. They've obviously built a great company over the years, but, we're not directly competing with them on endpoints.
Our focus on security is primarily on SIEM, and the endpoint issues that they saw really didn't have any direct bearing on what that means for us from a SIEM standpoint. I think customers are very aware of our offerings and what we bring and how we show up, and I think that plays nicely to our advantage overall.
Okay. Okay, got it. One of the product announcements that I, you know, didn't get as much airtime this call, but it's sort of coming down the pike, and I know there's a lot of excitement around it, is with serverless.
So I was wondering if you could sort of just talk about where we're at with that, you know, what the benefits are for customers, and then how investors should think about the potential pricing changes, and you know, how to think about the rollout of that across your customers.
Yeah, so it's a great area, and one that has been a high-priority focus area for our engineering team for some time now. You know, fundamentally, one way to think about serverless is what it lets you do is it lets you decouple the compute from the storage, and what that does is a few different things. One is it unlocks a whole new set of use cases. If you've got use cases that have particularly bursty needs in one dimension of those, it allows you to scale those somewhat independently.
But importantly, with serverless, it actually changes a lot of the actual user experience, and it's a lot simpler and easier in terms of thinking about what that customer experience looks like because the experiences are more, you know, bespoke to the particular solution areas. You, if you're a security operator, if you're a DevOps person, and you're looking at log analytics, if you're just thinking about search, historically, those were all, you know, the experiences that we had in our traditional hosted product were somewhat catered to those.
But this is a true SaaS-like experience in terms of thinking about not having to deal with a lot of the orchestration work that you otherwise would have had to handle, not having to deal with a lot of the management work, things like managing, sharding, and the size of your indices, and so forth. So it actually simplifies the management quite significantly, and, it makes it a much, much, more, much better user experience. And the third thing is from a pricing standpoint, it actually, allows us to have, pricing that is more specific to the, to the solutions or to the use cases.
And that actually helps us in the longer term from the standpoint of thinking about our gross margin, where we can price based on a particular use case, and the pricing is connected to, indirectly connected to, but not directly, informed by immediate changes in the pricing of infrastructure. So it gives us more flexibility from that standpoint as well and gives the customer more flexibility as well from the standpoint of the way they think about it. So it's been incredibly positive on all of those fronts. Serverless is currently in Beta, and it will go GA by the end of this calendar year. For us, that means we need enough presence in the different hyperscalers in the geographies. But so far, the reaction to the service has been incredibly strong.
What's important to know is that serverless is not going to replace the existing Elasticsearch offering, so we're not gonna do any kind of forced migrations or anything of that sort. It will be offered alongside the existing hosted offering, and so we think a lot of new customers and new workloads will go to the serverless offering. There might be some people that are more comfortable with the existing offering, particularly if they've already got all of their processes set up, their dashboard set up. If they're comfortable with the pricing model, they may stay there, so I think over time, we will naturally see a shift to serverless.
But we are not trying to engineer a particular, mix shift there.
Right. And just thinking about the financial impacts of that, obviously tough to predict 'cause it's in Beta, but just with the separation of compute and storage, is there any risk of, you know, revenue loss if there's more efficient storage? Or conversely, maybe the serverless pricing is gonna be at a premium, and so if there is conversions, that turns to a price tailwind.
Yeah, I don't think there's any sort of immediate risk of big revenue hit associated with it, because, as I said, it'll also take time for it to ramp quite naturally anyway. Net-net, I think this will actually be positive for us both in terms of aggregate revenue dollars, as well as in terms of gross margin percentage.
Okay. Okay. Yeah, very clear. You know, I guess on margins, we didn't talk too much about that, but you know, despite the top line shortfall, you actually did take up margins. If you could sort of speak to the actions that you did, and then philosophically, how do you sort of think about long-term growth and profitability at Elastic? Or do you aspire to be a you know, Rule of 40 company? How do you sort of think about that?
Yeah, we, we've not formally adopted a particular framework, but conceptually, that's exactly how we think about it, that you have to balance revenue growth with profitability, and the right to keep investing in the business is earned based on the results that you deliver on the top line. And, you know, these models tend to have enormous leverage on the way up and down, and so the way we've tended to think about it is, when we see continued growth in the business, we'll invest some towards that growth while continuing to expand operating margins at the same time, because there is leverage that is inherent in the business model. And if, if growth slows for whatever reason, then we step back and assess why did that happen. And if it's something that is short term, we take actions in the short term.
If we think there is some structural shift in the market, then we will take appropriate actions based on that. But fundamentally, it is about making sure that we're driving for both revenue and profitability and achieving that balance, and that's what you saw us do this time as well. If I think about FY 2025 and the revenue guidance, we brought it down by two percentage points in terms of year-over-year growth. As you think about that change in the revenue guidance at the midpoint, that was about $34 million of total revenue at the midpoint that we brought down, and we brought down our expenses by a little bit more than that, and still protected and slightly increased the operating income in the guidance.
And the way we did that was by cutting back on certain areas of investments that were planned that don't necessarily have a direct impact on long-term growth. And that includes being a little bit more targeted in the sales function in terms of investing in selling capacity only in those places where we see the stability of execution. From a long-term perspective, staying the course on GenAI investments on the R&D side, we are slowing down some of our investments in non-selling roles in the sales organization, slowing down some of our investments from a marketing perspective, particularly on the brand side, and close to my heart, continuing to drive efficiencies on the G&A side of the organization.
So there are things that we've done to take steps that I would call proportionate and measured based on what we saw as a short-term execution issue.
Great. I think we are out of time, Janesh. Thank you very much. That was a lot of detail. Appreciate the explanation, and have a good rest of the day, everyone. Thank you.
Thank you. Thanks again for having us.