Good day, and thank you for standing by. Welcome to the second quarter 2024 Datadog earnings conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question-and-answer session. To ask a question during this session, you will need to press star one one on your telephone. You will then hear an automated message advising you your hand is raised. To withdraw your question, please press star one one again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead. Thank you, Michelle. Good morning, and thank you for joining us to review Datadog's second quarter 2024 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog's Co-founder and CEO, and David Obstler, Datadog's CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the third quarter and fiscal year 2024 and related notes, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities, and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended March 31, 2024. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended June 30, 2024, and other filings with the SEC. This information is also available on the investor relations section of our website, along with a replay of this call. We will also discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com. With that, I'd like to turn the call over to Olivier. Thanks, Yuka, and thank you all for joining us this morning. We had a very productive second quarter. First, we welcomed thousands of Datadog users to our DASH conference in June, where we announced a broad range of exciting new products and new features for customers to observe, secure, and act in their cloud environment. We continue to add new customers and help existing ones as they grow in the cloud. Let me start with a review of our Q2 financial performance. Revenue was $645 million, an increase of 27% year-over-year and above the high end of our guidance range. We ended the quarter with about 28,700 customers, up from about 26,100 a year ago. We had about 3,390 customers with an ARR of $100,000 or more, up from about 2,990 last year, and these customers generated about 87% of our ARR. We generated free cash flow of $144 million, with a free cash flow margin of 22%. Turning to platform adoption. Our platform strategy continues to resonate in the market. As of the end of Q2, 83% of customers were using two or more products, up from 82% a year ago. 49% of customers were using four or more products, up from 45% a year ago. 25% of our customers were using 6 or more products, up from 21% a year ago, and 11% of our customers were using 8 or more products, up from 7% a year ago. We continue to expand the capabilities of all of our products over time, enabling our customers to solve more of their critical challenges. This includes our efforts in digital experience monitoring, an area of observability, which includes Synthetics and Real User Monitoring or RUM, and both Synthetics and RUM are seeing growing adoption, and each product today represents more than $100 million in ARR, becoming our fourth and fifth products to achieve that milestone. We have also been innovating rapidly in this area, with recent capabilities including mobile app testing, feature flag testing, user journey visualization, and retention analysis. And with our recent announcement of Product Analytics at DASH, we are excited to go further and allow our customers to consolidate more of their usage and business insights into Datadog. Now, let's discuss this quarter's business drivers. Overall, the business environment for Datadog was roughly unchanged from last quarter. Our customers overall are growing their cloud usage, while some are continuing to be cost conscious. In Q2, we saw existing customer usage growth that was broadly in line with our expectations and consistent with the overall improved trend that we have experienced over the past several quarters. Our usage growth with existing customers was higher than in the year-ago quarter, and we saw continued healthy growth across our product lines, with newer products growing faster from a smaller base. Finally, churn continues to be low, and gross revenue retention was stable in the mid- to high 90s, highlighting the mission-critical nature of our platform for our customers. Moving on to R&D. We held our DASH user conference in late June, and we're excited to announce many new products and features for our users. There's too much for us to cover in detail, but let me review just some of the announcements we made in the past three months. In the next-gen AI space, we announced the general availability of LLM Observability, which allows application developers and machine learning engineers to efficiently monitor, troubleshoot, and secure LLM applications. With LLM Observability, companies can accelerate the deployment of AI applications into production environments and reliably operate and scale them. We also expanded Bits AI with new capabilities. As a reminder, Bits AI is a Datadog built-in AI copilot. In addition to being able to summarize incidents and answer questions, we previewed at DASH the ability for Bits AI to operate as an agent and perform autonomous investigations. With this capability, Bits AI proactively surfaces key information and performs complex tasks, such as investigating alerts and coordinating incident response. Taking a step back and looking at our customer base, we continue to see a lot of excitement around AI technologies. Our customers are telling us that they are leveling up on AI and ramping up experimentations, with the goal of delivering additional business value with AI, and we can see them doing this. Today, about 2,500 customers use one or more of our AI integrations to get visibility into their increasing use of AI. We also continue to grow our business with AI-native customers, which increased to over 4% of our ARR in June. We see this as a sign of the continuing expansion of this ecosystem and of the value of using Datadog to monitor their product environment. I will note that over time, we think this metric will become less relevant as AI usage in production broadens beyond this group of customers. Last but not least, we announced Toto, our first foundational model for time series forecasting, which delivered state-of-the-art performance on all relevant benchmarks. In addition to the technical innovations devised by our research team, Toto derives its record performance from the quality of our training data set and points to a unique ability to train, build, and incorporate AI models into our platform that will meaningfully improve operations for our customers. Moving on from AI, we have a lot more to show in observability. We announced the general availability of Flex Logs, which extends our logging-without-limits approach and allows our customers to scale storage and compute separately for cost efficiency. Our customers can today use our new Log Workspace for log analysis. Log Workspace is an advanced analytics feature that allows users to connect data sets, build and visualize complex queries, and create reusable, composable views and reports. It is particularly relevant to customers who previously built sophisticated analysis and workflows in legacy log management tools. We announced the general availability of Data Jobs Monitoring, which allows data engineers to detect and fix issues with their Spark and Databricks workloads, and to optimize the cost and performance of their data jobs. Moving and transforming large amounts of data has grown in importance and become a mission-critical capability for many businesses, a trend that we believe will continue with the adoption of AI. With this, our data observability set of products is expanding. Data Jobs Monitoring works alongside our Data Streams Monitoring product, which helps customers understand their queuing pipelines, involving components such as Kafka or RabbitMQ. We're increasingly providing visibility for data lakes and data warehouses, such as Snowflake, to deliver end-to-end data observability across customer data resources. Moving on from data observability, we introduced Kubernetes Autoscaling to allow customers to optimize for cost and performance by automatically right-sizing Kubernetes resources. For our customers using OpenTelemetry, the Datadog Agent will embed a fully configurable OpenTelemetry Collector, giving our customers access to Datadog products such as container, network, and Universal Service Monitoring, and offering our customers what we believe will be the best fully managed OpenTelemetry experience in the market. Shifting left, our new Live Debugger enables developers to step through code directly in production environments and find the exact root cause of production errors. As I mentioned earlier, we are building up on our success in digital experience monitoring, and we announced Product Analytics, providing in-depth product and user insights for product managers and business owners. In the cloud security space, we launched a new application security capability called Code Security, which allows our customers to detect and prioritize code-level vulnerability in their production applications. We also announced Data Security, which allows our customers to automatically pinpoint sensitive data, starting in AWS today and expanding to other environments in the future. For instances where customers can't or don't want to deploy agents, our new Agentless Scanning capability provides visibility into risks and vulnerabilities within hosts, containers, and serverless functions without requiring agents to be installed. Finally, in the cloud service management space, we're going further to allow our customers to take action directly within Datadog platform. We announced the general availability of App Builder, which lets teams rapidly create self-service, low-code applications and integrate them securely into their monitoring stacks. We introduced Datadog On-Call, a modern on-call experience with paging and Incident Management workflows fully integrated with observability. Let's move on now to sales and marketing. We again saw strong execution from our go-to-market teams this quarter, and we added some exciting new customers while expanding with many more. Let's go through a few examples. First, we landed our largest-ever new logo win, a multi-year deal with total contract value of tens of millions of dollars, with one of the largest banks in South America. This customer was using a commercial observability product as well as open-source tools, but didn't have full stack visibility. With Datadog, they will enable end-to-end observability, and they expect to transition to modern infrastructure with confidence. They also anticipate better management and predictability of their observability costs, thanks to products such as Flex Logs. Next, we signed a 7-figure annualized land deal with one of the world's largest travel management companies. This company was using a commercial log management tool, but found it expensive and complex to support. They also worried about stability as the tool would crash and cause fire drills across the organization. By moving to Datadog and replacing this tool, they expect to drive significant savings with log management and will benefit from a unified platform across infrastructure monitoring and APM. Next, we landed a seven-figure annualized land with a security software company. This customer felt they were overspending on their commercial logging tool, and lack of visibility led to issues catching incidents, with users notifying them first of outages. This customer is now adopting the Datadog unified platform across all three pillars and displacing one commercial and two open source tools in the process. This customer also expects net savings of $500,000 every year by switching to Datadog. Next, we signed a seven-figure annual expansion with a leading central bank in Europe. This institution became a Datadog customer three years ago to enable its ambitious plan to move half of its applications to the cloud over a couple of years. They have been increasing their usage of Datadog as they moved into the cloud, displacing two commercial observability tools, which they use in their on-premise environment. They have now adopted a total of 17 Datadog products. Next, we signed a seven-figure annualized expansion with a large American insurance company. This customer had been using Datadog for full stack observability at one business unit. With this expansion, they have chosen Datadog as their enterprise-wide observability provider. In comparing us to the performance of other tools, this customer measured stronger developer adoption and fewer incidents with Datadog. In displacing its legacy APM and log management, they expect to save over $1 million annually on tool costs alone. Finally, we signed a high seven-figure annualized expansion with a leading online gambling and entertainment platform. This long-time customer uses Datadog as its strategic observability partner, enabling full visibility across infrastructure, applications, logs, network, and their public front end, with users spanning from hands-on keyboard engineers all the way to their C-level executives. This renewal supports this customer's expansion into new use cases to have security embedded into the operations by using all of our cloud security products, to build a culture of cost accountability with Cloud Cost Management, and to take action by using Incident Management and workflow automation. This customer, to date, has adopted 19 products in the Datadog platform. That's it for another productive quarter from our go-to-market teams. Now, let me say a few words on our longer-term outlook. Overall, we continue to see no change to the multi-year trend towards digital transformation and cloud migration. We are seeing continued experimentation with new technologies, including next gen AI, and we believe this is just one of the many factors that will drive greater use of the cloud and next gen infrastructure. As indicated by our many announcements at our DASH conference, we are delivering rapid innovation at scale, and we are helping our customers every day to deploy and scale their modern environment with confidence across observability, digital experience, cloud security, cloud service management, software delivery, and product analytics. Finally, I'd like to welcome two new leaders to our team. Yanbing Li is joining us as our Chief Product Officer. Yanbing has more than 25 years of product, technology, and engineering experience, spanning enterprise software, cloud infrastructure, and AI at companies such as VMware, Google, and Aurora. She will lead our product team's efforts to expand the Datadog platform. And David Galloreese is joining us as our Chief People Officer. David has more than 20 years of HR experience at tech companies and large-scale, high-visibility enterprises such as Cigna, Wells Fargo, or Walmart. He will help us drive the next chapter of growth and scale at Datadog. With that, I will turn it over to our CFO. David? Thanks, Olivier, and good morning to all. Q2 revenues were $645 million, up 25% year-over-year and up 6% quarter-over-quarter. To dive into some of the drivers of the Q2 revenue growth, first, regarding usage growth from existing customers, the overall trend we saw was consistent with our expectations. In Q2, we saw usage growth from existing customers that was higher than usage growth in the year ago quarter. And as we look across the first half of 2024, our usage growth was higher than the first half of 2023. And we are seeing solid growth across our products. Our three pillar products continue to increase in customer penetration and usage, and our newer products across observability, cloud security, and cloud service management are ramping. Regarding usage growth by customer size in Q2-... We saw strong performance among our largest customers, who spend multiple $ millions with us annually, as they continued to return to growth and strike a balance between new deployment and focus on optimization. As we look at usage growth by segment, we saw the strongest growth with our enterprise customers, where year-over-year growth in usage has accelerated over the past several quarters. Over the same period, we have seen more steady year-over-year growth trends among our SMB and mid-market customers. As a reminder, we define enterprise as customers with 5,000 employees or more, mid-market as customers with 1,000 to 5,000 employees, and SMB as customers with less than 1,000 employees. Regarding our retention metrics, our net revenue retention percentage was in the mid-100s in Q2, similar to the past couple quarters. But remember, this is a trailing twelve months measure, and we've seen an increase in recent quarters as we look at the NRR quarterly trend. And finally, our trailing twelve-month gross revenue retention percentage remains stable in the mid- to high 90s. Now, moving on to our financial results. Billings were $667 million, up 28% year-over-year, and similar, similar to the trailing twelve months billing year-over-year growth. Billings duration was roughly flat versus a year ago. Remaining performance obligations, or RPO, was $1.79 billion, up 43% year-over-year. As we said before, contract duration has generally been increasing as customers choose more multi-year deals, and contract duration increased modestly in the year-over-year period relative to a year ago. Current RPO growth was in the mid-30s% year-over-year. We continue to believe revenue is a better indicator of our business trends than billings and RPO, as those can fluctuate on a quarterly basis relative to revenue based on the timing of invoicing and the duration of customer contracts. Now, let's review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. Gross profit in the quarter was $530 million, representing a gross margin of 82.1%. This compares to a gross margin of 83.3% in the last quarter and 81.3% in the year-ago quarter. Our Q2 OpEx grew 21% year-over-year and increased from 14% year-over-year growth last quarter. As we mentioned last quarter, Q2 OpEx included $11 million in expenses related to our DASH user conference. As we've discussed, we are investing in headcount in 2024, and the growth in OpEx reflects our execution on hiring in sales and marketing and R&D so far this year. Q2 operating income was $158 million, or a 24% operating margin, compared to 27% last quarter and 21% in the year-ago quarter. Now, turning to the balance sheet and cash flow statements. We ended the quarter with $3 billion in cash, cash equivalents, and marketable securities. Cash flow from operations was $164 million in the quarter, and after taking into consideration capital expenditures and capitalized software, free cash flow was $144 million, for a free cash flow margin of 22%. Now, for our outlook for the third quarter and the fiscal year 2024. First, our guidance philosophy remains unchanged. As a reminder, we base our guidance on trends observed in recent months and apply conservatism on these growth trends. For the third quarter, we expect revenues to be in the range of $660 million-$664 million, which represents 21% year-over-year growth. Non-GAAP operating income is expected to be in the range of $146 million-$150 million, which implies an operating margin of 22%-23%. And non-GAAP net income per share is expected to be $0.38-$0.40 per share, based on approximately 360 million weighted average diluted shares outstanding. For the fiscal year 2024, we expect revenue to be in the range of $2.62 billion-$2.63 billion, which represents 23%-24% year-over-year growth. Non-GAAP operating income is expected to be in the range of $620 million-$630 million, which implies an operating margin of 24%. And non-GAAP net income per share is expected to be in the range of $1.62-$1.66 per share, based on approximately 360 million weighted average diluted shares outstanding. Some additional notes to our guidance, we expect net interest and other income for the fiscal year 2024 to be approximately $125 million. Next, we expect to pay cash taxes in the range of $20 million-$25 million, and we continue to apply a 21% non-GAAP tax rate for 2024 and going forward. Finally, we continue to expect capital expenditures and capitalized software together to be in the 3%-4% of revenues range in fiscal 2024. Now, to conclude, as Oli mentioned, we are pleased with our execution in the first half of 2024, and plan to continue to help our customers observe, secure, and act in their modern cloud environments. I wanna thank Datadogs worldwide for their efforts in this. With that, we will open up the call for questions. Operator, let's begin the Q&A. Thank you. If you would like to ask a question at this time, please press star one one on your telephone and wait for your name to be announced. To withdraw your question, please press star one one again. One moment for our first question. Our first question is gonna come from the line of Sanjit Singh with Morgan Stanley. Your line is open. Please go ahead. Yeah, thank you for taking the questions, and congrats on Q2. I wanted to get your assessment of the sort of demand environment, spend environment, and your description of, like, how the usage trends played out by end market, mid-market versus enterprise was super helpful. You know, Microsoft had noted that they saw some weaker usage trends in June. Just wanna get a sense of, if you look across your geographies or even across some of your key verticals, anything that stood out, sort of positive, negative, in June going into July, in terms of the usage trends? Yeah, thanks, Sanjit, and hello. Again, I think you've noted, we said that we experienced strength in our enterprise segment and stability in our SMB segment, and that continued throughout the quarter. As far as the more recent trends, for what we're seeing towards the end of the quarter and also in July, very similar trends to what we saw in Q2 and for the first half of the year. So continuation of higher usage growth than we saw in the comparable periods in the previous year. Understood. Then, Oli, maybe for you. I know at the Investor Day, you sort of outlined the sort of thoughts and strategy on on M&A and sort of identified the criteria. It sounds like your corp dev team sees a lot of opportunities, but the bar was pretty high, was the message from that investor a couple of months ago. I wanted just to sort of double-check your latest thinking on the M&A strategy with respect to potentially being looking at more strategic, more transformational, larger-sized deals. Has anything sort of changed in the way you view M&A as part of the Datadog growth strategy? So no, there, there's no change to the way we see things. You know, because we have this, this platform strategy, where we're building a consolidator, and we're bringing together many different use cases into one shared platform, we have very broad interest and a very ambitious roadmap in many different directions. So as a result, we cast a very wide net, you know, when it comes to M&A. There are many possible potential fits, you know, for us. So, you know, historically, we've been very successful with doing a lot of small and medium-sized deals. At any point in time, we're going to look at a lot of deals that might be small or big. We expect the bigger deal to be fewer and far between, as the bar is very high for those. And today, we're also not looking into anything that would be very material to the business. Understood. Thank you, Oli. Thank you, and one moment as we move on to our next question. Our next question comes from the line of Raimo Lenschow with Barclays. Your line is open. Please go ahead. Perfect. Thank you. Has there been any impact, or what are you seeing in terms of as a reaction from customers around the CrowdStrike outage? Because that's obviously a event that impacted the whole industry. You guys, I'm sure, kind of saw some of the ramifications there. Just talk a little bit about how that impacted you in the quarter, but also what it means to customer conversations. Thank you. Yeah. So, I mean, obviously, this is something that was very much in the news, very visible. It was particularly visible because it affected devices that are, you know, airport check-in kiosks, basically, and point of sale that are in the field and, you know, in front of consumers, and was, you know, pretty much everywhere at once. So, you know, very visible incident. That being said, you know, in the grand scheme of observability, like, it's very unremarkable. So the CrowdStrike event is very visible to everyone everywhere, but every single day, there's a, you know, 100 or 1,000 companies that are having their CrowdStrike moment because they've updated software, either third-party software or software, software that they've built, and they cause large business disruptions, large business issues, and that's what we deal with, you know, pretty much all the time. So, you know, what you see in the public eye is really a reflection of the value we provide every single day to our customers, you know, when it comes to preventing those issues, and whenever those issues happen, to remit them- remediate them extremely quickly. So of course, you know, we had all of the interactions you can imagine with our customers around it, you know, in terms of how they use our product to-... come back online, debug and everything, even though the fix in that case was very, very manual. You know, there was really no good way to automate it. But again, we see that every single day. That's what we do. Okay, perfect. And then the, maybe it was just me, but it did feel like you mentioned the logs quite a bit on this quarter's earnings call. Do you see any change, like your product is getting more mature and the innovation that is coming through is obviously kind of very visible, but do you see a change in the market with kind of recent movements in terms of vendors that that kind of opens up a little bit more from your perspective? Thank you, and congrats from me as well. Yeah, we definitely think there's gonna be more opportunity in the future, you know, which is why we're investing heavily, both in terms of making logs economical to scale, you know, that's Flex Logs in particular. And also going further in terms of the sophistication of the functionality we can offer to customers, so they can build very complex processes around those. So we talked about Log Workspace also in the call. Log Workspace is particularly interesting for customers who have used other platforms and have built pipelines basically that, you know, post-process a lot of logs data. And so we would build that for them, and that's been very well received so far. So all of that is in service of going after these opportunities. Perfect. Thank you. Thank you, and one moment for our next question. Our next question is gonna come from the line of Mark Murphy with JP Morgan. Your line is open. Please go ahead. Thank you so much, and I'll add my congrats, Olivier. It's great to see the announcement of LLM Observability reaching GA. I think we're all looking at this tremendous wave of hyperscaler commitments. They're gonna be ramping in the second half of this year, and it, it's all for training of these next-gen AI models. And since you're more exposed to the, excuse me, since you're less exposed to that training and you're more driven by the inferencing, I'm wondering if you could just help us understand how the spending pattern or activity changes as the AI models go live and reach the inferencing stage. I'm basically looking for any way to assess how much spending is ultimately gonna develop into the inferencing where you have an opportunity. Yeah. I mean, look. In general, it's still early. We do see customers that are going increasingly into production, and we have a few of those. I mean, we named a couple as early customers of LLM Observability. I think the two we named were Whoop, the fitness band, and AppFolio. And you know, we see many more that are lining up and that are going to do that. But in the grand scheme of things, looking at the whole market, it's still you know, very early. I would say the best proxy you can get from the future demand there is the growth of the model providers and the AI natives because they tend to be the ones that currently are being used to provide, you know, AI functionality into other applications and largely in production environments. And so I would say they are the harbinger of what's to come. Okay. And then as a quick follow-up, maybe for David, a couple of the consumption model software companies had recently commented that, in June and July, they were seeing more cloud cost control or optimization, specifically among the digital natives. And so, your results are solid. I don't think you've mentioned that, but could you just comment on the, how the optimization activity is kind of, trending now between the digital natives and the enterprises heading into the back half? Yeah, as you know, we've said that, so when you look at the time series, the peak of the optimization was in Q2, Q3 last year, and we've had, you know, a time series of higher usage growth for our clients, month to month, since then. And that's continued through the first half of the year and into July. It's the usage growth, as we talked about, is stronger in the enterprise and in the larger users, but it has been fairly stable in the SMB. So, we're seeing, you know, some more, when you look at the chart and the line, enterprise being, you know, users growth being higher than it had been, and SMB being stable. You know, for us, I would add that the digital natives are largely SMB, mid-market. They're not enterprise. And even when you look at the digital native, there's two stories, depending on whether you talk about the AI natives or the others. The AI natives are inflecting in a way that the others are not at this point. So today, we see this higher growth from AI natives and from traditional enterprises, and stable growth, but not accelerating from the rest of the pack. Thank you very much. Thank you, and one moment for our next question. Our next question is gonna come from the line of Kash Rangan with Goldman Sachs. Your line is open. Please go ahead. Hello, thank you very much. Oli, you've mentioned, I think on the call, there's been a repeated instance of enterprise growing faster than SMB. I'm curious, why is that the case? And is this something of a change in the trend? Have you seen SMBs actually showing better usage trends in the past? And what could cause the SMBs to start to pick up consumption? What are the things that are holding back that, their consumption, and what could be the unlocks from Datadog, Datadog's side? Because the enterprises are doing well, so obviously the product portfolio is being well received. So what's stopping the SMB? Thank you so much once again. Yeah, I don't know that there's that much of a trend just yet to look at or, you know, there's too much to say at this point. You know, this is just the way the numbers came out, you know, over the past quarter or so. I would say, look, there's many reasons why the SMBs could be more careful, you know, in terms of the macro environment, you know, the fact that they are less, maybe less, there's less runway, immediate runway with consolidation, like, things like that, you know, compared to the larger enterprises, and some of them maybe are further along also in their cloud journey. So the growth there is more tied to their overall growth as opposed to the speed of transition into next gen and cloud environments. So those are all potential factors. But look, there's no at this point. I wouldn't call it like a major, super important difference. Mm-hmm. I think we'll see what this looks like in a few quarters. Got it. And one for David, if I could. How strong is the delta between enterprise consumption growth versus SMB? Are we talking orders of magnitude or meaningful percentage or a big percentage? No, no, we're just- Yeah. We're just talking about a few points but different trends. That's it. No, we're just basically commenting on the line. You know, as we said, you know, they have been around each other's, and we're really commenting more on, as Oli mentioned, enterprise things like they may have been more careful, you know, in the increase of spending. Consolidation continues to be a factor in going to a common platform. But as Oli mentioned, these are sort of comments on the way things are evolving, but we still have pretty similar metrics in all the different segments. Thank you so much. It's something that we noted because we, you know... A little bit counterintuitive in that when you look at the overall market, the enterprise is where we have the most mature competition, the most scaled competition, and we're doing better. That part is scaling faster than I would call it, the less competitive side of the market. But again, not too much to read into it just yet. We're just informing you of the trends. Mm-hmm. Wonderful. Thank you so much. Thank you. One moment as we move on to our next question. Our next question is gonna come from the line of Kirk Materne with Evercore ISI. Your line is open. Please go ahead. Yeah, thanks very much, and I'll add my congrats on the quarter. Olivier, I was wondering if you could just talk a little bit more about the LLM Observability product Mark referenced. When people are thinking about bringing on LLMs into their organization, do they want the observability product in place already, or are they testing out LLMs and then bringing you on after the fact? I'm just wondering, you know, it's sort of a chicken and egg question. I'm wondering if you're someone they wanna talk to before they start moving things into production, or it's after they get something going, they bring you in after the fact. Yeah, I think so. So the first thing I'd say is we expect this market to change a lot over time because it is far from being mature, and so a lot of things that might happen today, in a certain way might happen, you know, in two years in a very, very different form. So that being said, the way it works typically is customers build applications using developer tools, and there's a whole industry that has emerged around developer tools for, and playgrounds and things like that for LLMs. And so they use not one, but, you know, 100 different things to do that, which is, you know, fairly similar to what you might find on the IDE side or code editor side, you know, for the more traditional development. There's lots of different, very fragmented environments on that side. When they start connecting the LLM to the rest of the application, then they start to to need like visibility that includes the other components, you know, because the LLM doesn't work in a vacuum. It's plugged into a front end. It works with authentication and security. It works with connects to other systems, databases, and other services to get the data. And at that point, they need it to be integrated with the rest of the observability. For the customers that use our LLM Observability product, they use us for the rest, all the rest of their stack, and it would make absolutely no sense for them to operate their LLMs in isolation, completely separately and not have the visibility across the whole application. So we'd say, at that point, it's a no-brainer that they need everything to be integrated in production. That's helpful. And then, David, that we can kind of infer your, your sort of implied answer for Q. I was just wondering, you know, some of the elections in Europe have come up on a couple other calls in terms of any things that have been distractions. I was just wondering if you had any thoughts on how you think the U.S. election might impact usage, if at all, or if you have any thoughts on that. I realize you guys were a lot smaller last time we had a presidential election. Yeah, I mean, no, we are not forecasters like that. As you know, usage growth has many factors. The effect of the election on the operation of modern cloud applications is not something that has been, you know, a very significant change in usage patterns, for instance, in the European elections, and we wouldn't anticipate any here as well. No, no, no impact. The only, the only impact on us of the US election is we're trying not to schedule our earnings calls on the same day. Yeah. We'd appreciate that. Thank you. Thanks, guys. Thank you. Thank you. One moment as we move on to our next question. Our next question comes from the line of Fatima Boolani with Citi. Your line is open. Please go ahead. Good morning. Thank you for taking my questions. Oli, I wanted to start with you. You and David both talked about improving usage trends, but I wanted to take a step back and ask you—Have you seen the quality of the usage improve by virtue or of, or by extension of your introduction of the Cloud Cost Management SKUs? You talked about the Kubernetes with the autoscaling, and then the original sort of Cloud Cost Management SKU. So I'm wondering if it's maybe a serious correlation that now that customers have that much more visibility into the mechanics of what they're spending with you, they're actually more inclined to drive usage because it's higher fidelity. Just any commentary on that would be helpful. And then I have a follow-up for David, please. Yeah, I mean, look, in general, customers have invested a lot in understanding their spend, whether that's on us or on their cloud providers. And as a result, you know, you can say that there's less, you know, call it overhang of, you know, things customers are spending and they don't understand, you know, which is always, you know, bad in the long term, you know. So I think customers understand much better the value of what they're getting in the cloud in general this year than they did two years ago before this whole, you know, optimization movement started. And they want more, you know, in terms of visibility into what they spend, what actually creates value for them, and you know, where they can optimize in the future. So that's definitely a virtuous cycle that we are embarked on with our customers in terms of building the right products for that. I appreciate that. And David, as you all kind of roll out more what I would call resource-intensive or compute-intensive SKUs, like logs and Flex Logs, Log Workspaces, I'm wondering if you can shed a little bit of light on how some of the gross margin characteristics differ by product pillar. I'm just looking at kind of some of the sequential compression gross margins, so just kind of wanted to get a better understanding of what are some of the more you know resource-intensive products that you're anticipating scaling that could keep a lid on gross margins in the next couple of quarters. Thank you. Yeah, we have. I'll just go in the numbers first, and then Oli on the engineering side of it. But essentially, what we said, oh, and consistently, is that gross margins have operated in a range. They've operated towards the top of the range, but there will be variability quarter to quarter as we launch functionality, often having to do with growing out functionality and then optimizing it. And so the movements, slight movements that we've seen quarter to quarter, have been the result of that, and then turn it over to Oli for more on the sort of engineering. Yeah, there's definitely nothing to read into the, the small movements in the gross margins from a product mix perspective. A lot of what happens is, you know, we build new features. Maybe some of those new features will have, you know, more compute impact or more storage impact, something else. Maybe also, they won't be fantastically optimized on day one, you know, from a code efficiency perspective. Or maybe sometimes we'll focus more on building more things as opposed to optimizing them because it has the same people, same resources on our end that work on both. And so what you should expect to see is some ebbs and flows on that number as we keep shipping new features and then we keep optimizing. In general, we feel good about the gross margins. We're not constrained, you know, in terms of what we can build, by the margin profile we have, and also, should we need them, we have many levers to improve these margins as well. So we, you know, I wouldn't read too much into the small changes. I would expect some more of those small changes in the future. And on the line, we feel good about that. Thank you so much. Thank you, and one moment for our next question. Our next question is gonna come from the line of Matt Hedberg with RBC. Your line is open. Please go ahead. Great. Thanks, guys. Oli, in your prepared remarks, you talked a lot about security and noted data security as a new sort of growth engine from a product perspective. I'm curious, can you talk about how customers might leverage that offering versus maybe other traditional data security offerings in maybe like DLP, for instance? Yeah. So, you know, it's interesting because. So in many ways, we've been doing Data Security for a while now, you know. So we, on top of our logging product, we started building sensitive data scanning, which was, which is very successful with customers. We extended that to cover data that flows inside APM tracing, that flows between the front end and the back end, you know, in really the monitoring. And we basically heard our customers, you know, ask for more. Basically, they wanted to not just see data in transit, but also see where data was exposed at rest, and so that's how we expanded to the rest of Data Security. So you can see customers coming to that from two different sides on our end. One is customers adopting our security suite, and, data security is little by little becoming part of, you know, CNAPP and, you know, cloud infrastructure, you know, security in general. But we also see customers coming to it from the log and APM side, basically, where they start from the applications, and they want to track where the data is. So it serves both sides, basically, and it plays to the strategy we have of integrating both observability and security into one platform. Got it. Super helpful. And then, you know, as we get into Q3 and kind of the U.S. Fed spending quarter, what are your thoughts on, you know, how federal spending just in general might play out in Q3 relative to kind of your assumptions? Well, we're building up the capacity for it, you know, so we have build up to do on several sides. I mean, we have the go-to-market capacity to build. We also are still pursuing more government certifications and government-specific deployments, you know, to open up some more of the market there. But that's definitely an area of investment for us. ... Got it. Thanks a lot, guys. Well done. Thank you. One moment for our next question. Our next question comes from the line of Jake Roberge with William Blair. Your line is open. Please go ahead. Thanks for taking the questions. I just want to follow up on the enterprise strength that you saw in the quarter. Are you starting to see enterprises reengage with their cloud migration efforts, which is helping you drive that growth? Or is the strength more related to just general platform usage and expansion? They never stopped their enterprise migration. I think maybe, you know, some of the usage was not growing as quickly for some time. So maybe some short-term optimization efforts were ongoing. But, you know, the direction was always the same, like, they... And, you know, also, they never stopped growing with us in the cloud, you know, so we definitely saw that throughout the past couple of years. Some of the strength we see today, you know, has to do with the fact that the embrace of AI has reaffirmed for them the need to go to the cloud, you know, sooner rather than later, so they can build the right kind of applications. They have the right kind of data available to build the applications. But also, you know, we have more to offer, like we have—we, we can do more, and consolidate more of what they were using, before, and that gives us more avenues to, to grow these customers in the short term. Yeah, I think we said, you know, over the quarters that one enterprise is very early in their journey, and there's a lot of white space, too, that we said a couple quarters ago, that enterprises have started to resume more normal activity of deploying of modern cloud applications. And as Oli mentioned, there's opportunities also for consolidation in the platform, cloud platform that we've talked about many times. I'll point you to the numbers we shared, I think two quarters ago in terms of our enterprise penetration and the average size of our contracts with enterprises, which are still fairly small. Like, there's a lot of runway there, and the growth of those accounts is not predicated on the growth of the enterprises themselves. They're still early in their transformation. Okay, very helpful. And then you've talked a decent amount about the demand you're seeing from AI-native customers, but how are you thinking about driving growth with your own AI solutions, like Bits AI and LLM Observability? And when do you think those start to layer more meaningfully into the model? Thanks. Yeah, I mean, right now, the first era of direct application of Bits AI is in Incident Management and incident resolution. So that is tied more to the SKUs we're selling there, you know, in terms of Incident Management. But Bits AI is not the only ingredient of that product. You know, so part of it is what we had already in terms of the mechanics of Incident Management. Part of it is also the new On-Call product we announced, and part of it's going to be the smarts in this, and we're integrating all that to have a fantastic end-to-end experience for our customers that almost makes them want to have incidents. No, actually, they still won't want to have incidents, but, you know, the point here is it should really help them. Thank you, and we'll move on to our next question. Our next question comes from the line of Koji Ikeda with B of A. Your line is open. Please go ahead. Yeah. Hey, great. Thanks, guys. Thanks for taking the questions. Just one from me. I wanted to ask on the usage growth trends. You know, in the prepared remarks, you said a lot about trends, exiting or this quarter versus Q2 of last quarter, and the first half of this year being better than the first half of last year. But the question here is: How did Q2 this year compare to Q1 this year? Thank you. Yeah, we have. So we have normal seasonality related to the number of days in the quarter and customer behavior in as they launch new applications. So we really look at it because of the seasonality over quarters. So the usage growth exhibited the same patterns of improvement over last year's similar period, looking at the days as it did in the first quarter. Got it, David. Actually, one quick follow-up, if I may here, then. You know, the follow-up would be, I know in the Q, you give a net new revenue growth split between existing and new. Mm-hmm. I was wondering if we could get that mix now, or, or maybe at least some color in that mix. Last quarter was 70% coming from net new from existing. Was it higher or lower this quarter from that 70%? It's gonna be 75, 25. 25 from new, 75, which would be what we said all along, is that, you know, as net retention recovers and usage growth is higher than the previous comparable period, as if you go back through our history, you will see that the amount from existing customers relative to new logos has generally increased. Great. Thank you very much. Mm-hmm. Thank you, and one moment for our next question. Our next question is gonna come from the line of Yi Fu Lee with Cantor Fitzgerald. Your line is open. Please go ahead. Thank you for taking my question, and congrats on the quarter. In terms of, like, the new products that were launched at DASH, you know, a lot of stuff going on, LLM, AI Ops, et cetera, like, Olivier and David, like, which one are you most bullish near term and then longer term? Well, you know, it's always hard to have a favorite child, you know, in all of the amazing things that we're shipping. Look, I think the short term is the ones that are going to have the most impact are the ones that relate to the products that already have scale, you know. So anything we do that facilitates the deployment of APM at scale has a large impact. Everything we do that changes the economics of logs opens up new markets within the existing legacy incumbent user base has a huge impact. What we're doing with OpenTelemetry has a large impact, you know, because it's a big trend in the industry, and we're making bold moves there. You know, so, longer term, look, we think there's a very large opportunity for us to do a lot of automation on behalf of our customers. And, you see that, whether that's on the observability side or on the security side, with all of the various ways in which we are taking action into the product, we are fixing things for customers, we're driving them to take the next step. We are organizing the tracking of the workflows they're running, you know, from end to end. So this is a longer view, but I think in the long run, it makes a very, very large difference in terms of the value we can provide to our customers. Thanks for that, Olivier. And just a quick follow-up with, for David is, like, NRR is like at the mid-110 level. What needs to happen in order for, Datadog to go back to the above 120 level? I mean, it sounds like the trends are very, very healthy, month-to-month, quarter-over-quarter. So just some commentary around there, and that's it for me. Thank you. Yeah, I mean, we don't give that, you know, that forecast. I mean, the components are the use of existing products and the cross-sell. And so, you know, as you mentioned, both of those have, you know, been stronger in the first half of this year than they were, you know, last year. And, you know, it, you know, we'll see what happens, but we don't give, you know, guidance or forecast on net retention. Thanks. Thank you very much. Thank you, and one moment for our next question. Our next question comes from the line of Patrick Colville with Scotiabank. Your line is open. Please go ahead. All right, terrific. Thank you so much for having me on. Olivier and David, I mean, one of the themes you talked about in the past is kind of competitive dynamics in observability. I mean, there have been a lot of corporate transactions in the space over the past year. So I guess, how are you seeing competition versus your, you know, open source peers, kind of platform peers, peers that are now, you know, private, versus, you know, a couple of quarters ago? So in general, the commission is very, very much unchanged. You know, there's nothing super specific to say about that. I think the... We have some of the scale players that are disappearing to a certain extent, as, you know, as a result of the transactions you've mentioned. Though we expect that to play out more in the midterm than in the very short term, in the marketplace. We do have scaled competition still in terms of, you know, public companies that are competing with us, you know, on observability. And, you know, there's no change in the posture there, and we like the way we're performing. You know, a number of the large deals we've mentioned, where, you know, displacements or wins against these folks, we feel very good about that. And then on the low end, there's been a pretty much a rotating cast of, you know, sub-scale companies that, you know, are going after that market, and that's also unchanged. That's been the same throughout the life of the company, pretty much. So nothing to report there. I think largely when we build products, we build it with customers. We don't build it with competition in mind. The few exceptions being when we see large vertical opportunities in the market because of the big changes and big transactions, like you mentioned earlier. Okay. Very helpful. And I guess, David, I mean, looking at the 3Q revenue guidance, it looks like the kind of buoyant trends you saw this quarter will continue. And can you just put a fine point, if possible, on the trends we saw through July and thus far in August? Yeah, no, so I think what we've seen since the quarter, as we mentioned, is a continuation of better usage trends relative to the comparable period last year. So, you know, more, more of the same. And in our guidance philosophy, it hasn't changed. We take those trends as much information as we have and apply discount and conservativism, given that, you know, we don't control the consumption of our clients, we, you know, observe it. So it's a very similar methodology to what we've used in previous quarters and a continuation of the trends we've seen in the first half of the year. Terrific. Thank you so much. Thank you, and one moment for our next question. Our next question comes from the line of Imtiaz Koujalgi with Wedbush Securities. Your line is open. Please go ahead. Hey, guys. Thanks for taking my question. I have a question for David on your sequential revenue growth this quarter. So I'm trying to reconcile the comments you made about the usage growth in this quarter being better than last year. But if you look at the revenue growth sequentially, that's slowed down. I think it's the lowest Q2 sequential growth in the longest time. And one more question was, if you look at the sequential growth for the last three, four quarters, it's been accelerating since the optimization trends ended, but that trend kind of I guess it buckled this quarter because the Q2 growth in Q2 was lower than what you had last year. Just like to reconcile the commentary about usage growth being strong, but then the, revenue growth sequentially looks a little bit lighter than last year. Yeah, a lot of that has to do with what we saw—we said, which is that in the second half of December, clients are not at their desk and new deployments have been frozen. So we generally find that the usage or revenue run rate growth then, you know, goes down or is the same. And then we find a recovery as people get back to their desks in Q1, and then we find in Q2 a similar linearity pattern that we see in all Q2s, which is, you know, how it sort of people work. And so we didn't see anything out of the ordinary in terms of the time series of Q4 to Q1 to Q2. Got it. And then just one follow-up. And David, you, you mentioned that revenue is the best metric for your business. You shouldn't be looking at billings and RPO or bookings. But I'm just wondering, any color you can provide on the first half of bookings growth this year? It's been flat year-over-year, with duration increasing, and that's, I think, the lowest bookings growth again in any first half of your year. Any more commentary beyond what you already provided? Is the renewal base lighter in the first half? Should we expect an acceleration in the second half? Any more color on the bookings momentum? No. If you look at the latest 12 months of all these trends, they all eventually converge around revenues. It has to do with, as we mentioned, you know, on every earnings call, when bills go out, whether the deals are multi-year or single year, et cetera. So no, all of that is essentially balances out back to the metrics that we direct you to, which is revenue and then ARR. So no, nothing in it. Thank you. Thank you, and I would now like to hand the conference back over to Olivier Pomel for any further remarks. Thank you. And just to close the call, I want to thank again everybody who was involved in DASH this year. So that means obviously the product and engineering teams who shipped these amazing products, and there were lots of them. That means the go-to-market teams that have relayed the message to our customers. That means the marketing and community teams that did such a fantastic job putting up a show. And of course, that means the customers who showed up in large numbers with enthusiasm and who have been the life of the conference. So thank you, everyone, and we'll see you next quarter. This concludes today's conference call. Thank you for participating. You may now disconnect. Everyone, have a great day.