Thank you, Daniel. Good morning, and thank you for joining us to review Datadog's fourth 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 first quarter and fiscal year 2025 and related notes and assumptions, 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 September 30, 2024. Additional information will be made available in our upcoming Form 10-K for the fiscal year ended December 31, 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 strong Q4 to end a very productive year. During 2024, we kept building and innovating as we scaled up our teams and went broader and deeper into the problems we solve for our customers from the cloud to AI. We continue to add new customers and expand with existing ones and delivered more value as customers adopted more products in the Datadog platform. Let me start with a review of our Q4 financial performance. Revenue was $738 million, an increase of 25% year-over-year and above the high end of our guidance range. We ended with about 30,000 customers, up from about 27,300 a year ago. We ended Q4 with about 3,610 customers with an ARR of $100,000 or more, up from about 3,190 a year ago. These customers generated about 88% of our ARR. We had 462 customers with ARR of $1 million or more compared to $396 a year ago. And we generated free cash flow of $241 million with a free cash flow margin of 33%. Turning to customer adoption, our platform strategy continues to resonate in the market. As of the end of Q4, 83% of customers were using 2 or more products, which is about the same as last year, 50% of customers were using 4 or more products, up from 47% a year ago, 26% of our customers were using 6 or more products, up from 22% a year ago, and 12% of our customers were using 8 or more products, up from 9% a year ago. During 2024, we continued to land and expand with larger customers. As of December 2024, 45% of the Fortune 500 are Datadog customers, up from 42% in 2023. We think many of the largest enterprises are still very early in their journey to the cloud. The median Datadog ARR for our Fortune 500 customers is still less than $0.5 million, which gives a very large opportunity for us to grow with these customers. So we're serving more customers with more products, and we are also very pleased to celebrate several milestones for the business. First, our total ARR now exceeds $3 billion, a big achievement for all of us at Datadog even though we're still only just getting started. And we have achieved this milestone largely by growing our first product infrastructure monitoring and expanding into the other pillars of observability: APM and log management. Today, infrastructure monitoring contributes over $1.25 billion in ARR. But we didn't stop there. Log management is now over $750 million in ARR and so is our third pillar as our end-to-end APM products together also exceed $750 million in ARR. Note that even in the three pillars of observability, we are still just getting started as more than half of our customers do not buy all three pillars from us or at least not yet. Meanwhile, we're making progress with our other products, and we are pleased to see them increasing in customer usage and growth. Products outside these three pillars now contribute over $200 million in ARR and we are excited about our growth opportunities in the many new products in this group. Now let's discuss this quarter's business drivers. In Q4, we saw usage growth from existing customers that was roughly similar to the year-ago quarter. Our usage growth during the quarter generally played out as expected, including a stronger October and November and the slowdown we typically see at the end of December. We continue to experience a stable business environment and our customers overall are growing their cloud usage, while some are continuing to be cost-conscious. We also hit a new record in bookings this quarter as our go-to-market teams executed on our first ever quarter with over $1 billion in bookings. As a reminder, our bookings don't translate immediately into revenue growth, but it is an indicator that we continue to serve our new and existing customers as well, and they are growing with us over time. Finally, churn has remained low, with gross revenue retention stable in the mid- to high 90s highlighting the mission-critical nature of our platform for our customers. Moving on to R&D and what we built in 2024. We released over 400 new features and capabilities this year. Not as too much for us to go back today, but let's go over some of our innovations. First, we continue to improve the Datadog platform. We now have more than 850 integrations, making it easy for our customers to bring in every type of data they need to benefit from all the new AWS, Azure, GCP and OCI capabilities and engage with the latest technologies like the newly emerging AI stack. We announced Kubernetes autoscaling to help customers right-size the Kubernetes environments without impacting stability and performance. We launched Datadog Monitoring for Oracle Cloud Infrastructure so customers can now monitor their OCI stack and unify their monitoring across all clouds and on-prem environments. And we took several big steps to expand on Datadog as the best observability platform for OpenTelemetry users including making our infrastructure monitoring and APM instrumentation fully interoperable with OpenTelemetry components and improving the experience for OpenTelemetry customers by embedding the OpenTelemetry collector directly within the Datadog agent. In the next-gen AI and LLM space, we continue to add capabilities to Bits AI, launching Bits AI for incident management and previewing Bits AI for autonomous investigations. We launched LLM observability in general availability to help customers evaluate, safely deploy and manage their models in production, and we continue to see increased interest in next-gen AI. At the end of Q4, about 3,500 customers used one or more Datadog AI integrations to send their data about their machine learning, AI and LLM usage. In the end-to-end APM space, our Error Tracking product now allows customers to view and manage errors across user stations, applications and logs, all in one place. We kept building our data observability, including the launch of data job monitoring to help data engineers detect problematic Spark and Databricks jobs anywhere in their pipelines. And we expanded the technologies we can provide deep insights into such as Amazon SQS, in data stream monitoring, and MongoDB in database monitoring. In Digital Experience, our customers can now use our mobile app testing to test iOS and Android applications on real mobile phones. We allow faster investigation of mobile app issues with mobile session replay. And while product analytics remain in early stages, we are encouraged by customer interest in using Datadog to analyze user behavior for better business outcomes. In log management, Flex Logs launched into general availability, and customers can now cost-effectively retain and analyze massive volumes of data over long periods of time. We expanded log workspaces for advanced analytics and querying. And we simplified the deployment of observability pipelines with new out-of-the-box templates and granular configuration options. In cloud security, we now have more than 7,000 customers using one or more security products. We launched agentless scanning to detect risks and vulnerabilities within hosts, containers and servers across a whole cloud account in a few clicks. We shipped Datadog infrastructure as code security, so our customers can identify and fix misconfigurations in their Terraform and Plat4mation code. Our customers can now use Kubernetes security posture management to benchmark their environments against industry-based practices. We launched code security to detect vulnerability in first-party code running in production environments. We continue to expand on our software composition analysis capabilities. And we built many more integrations, content packs and investigative workflows into our cloud SIEM product. In software delivery, developers can now use Datadog code security with quality gates to ensure production code meets quality, security and performance standards. And we announced the ability for customers to observe DORA metrics to improve the speed and efficiency of the engineering teams. In Cloud Service Management, we launched our modern scheduling solution, Datadog OnCall for general availability last month. We are already seeing significant customer interest in it and are excited to solve this problem for our users. We launched Event Management for general availability using AIOps to intelligently aggregate, consolidate and simplify alerts from any sources. We built out our case management functionality so users can triage, assign and close production-related tickets faster. And finally, our app builder product lets users build apps to implement their own custom processes and workflows and take action directly within Datadog. So I'd like to thank our product and engineering teams for a very productive 2024, and I'm super excited about what we have planned for 2025. Let's move on to sales and marketing. We had a strong close to 2024 with record bookings and some very exciting new logos and expansions. Let's go through a few. First, we landed a 7-figure annualized deal with a major U.S. financial institution. This company was struggling with high costs and expansive logging tools. By using Datadog Flex Logs and observability pipelines, this customer expects to save money on log management and we'll redeploy those savings to invest in observability transformation. This customer is starting with 4 Datadog products and is replacing 4 commercial and open-source tools. Next, we landed a 7-figure annualized deal with a large Brazilian retail company. This company had built a homegrown open-source-based observability tool but had poor visibility into customer journeys for their shopping application. With Datadog, they quickly improved application performance, which drove higher app store ratings, better digital reputation, and improved user confidence. This customer is starting with 5 Datadog products. Next, we landed a 6-figure annualized deal with the leading American entertainment company. This company had limited visibility into their customers' experience on in-store kiosks and on their mobile app. By using Datadog's unified platform, this company will correlate monitoring across the front and back end and enable multiple teams to collaborate for improved customer experience. This landed deal featured our brand-new product analytics capabilities and will displace 2 commercial observability and analytics tools. Next, we landed a high 6-figure annualized deal with a U.S. federal health insurance company. This company's Medicare Services business requires a SIEM, but its SIEM tool was expensive and poorly adopted by the teams. They will now rely on both Flex Logs and our cloud team within GovCloud for significant cost savings, all that while improving security and compliance. And we have the opportunity to provide additional value and expand to three pillar end-to-end observability over time. Next, we signed a 7-figure annualized expansion with a Fortune 100 oil and gas company. This customer is moving thousands of hosts from on-prem to the cloud and will replace 2 legacy infrastructure and network monitoring tools. The estimated cost and productivity savings from operating these legacy tools exceed $1 million annually. And we work with them to evaluate the productivity gains when thousands of users saw less disruption by incidents for expected savings of over $10 million per year. This customer is expanding to use 14 Datadog products. Last for today, we signed a 7-figure annualized expansion with a leading security software company. This customer built a homegrown log management tool using open-source software, but it was time-consuming to maintain, extremely costly and performed poorly with unacceptable delays. By moving to Flex Logs, this customer is already saving on total cost, reducing mean time to resolution and increasing user productivity with estimated savings over $1 million a year. And this customer is expanding to use 8 Datadog products. And that's it for this quarter's highlights. Congrats again to our go-to-market team for their great work in 2024, our best ever close to the year and the exciting plans we've laid out for 2025. Before I turn it over to David for a financial review, a few words on our longer-term outlook. We continue to believe digital transformation and cloud migration are long-term secular growth drivers of our business as well as critical for every company to deliver value and gain competitive advantage. And we think moving to modern cloud-based technologies is more important than ever as more companies step up to adopt AI capabilities. We continue to focus on delivering innovation and value to our customers against their mission-critical needs. And more than ever, we feel ideally positioned to help customers of every size in every industry to transform, innovate and drive value through technology adoption. And with that, I will turn it over to our CFO. David?

Thanks, Olivier. To start, Q4 revenue was $738 million, up 25% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of the Q4 revenue growth, overall, we saw trends for usage growth from existing customers that were consistent with our expectations. We continue to see conditions that were similar to recent quarters and roughly stable throughout 2024 with continued movement to cloud and modern DevOps technologies, and with customers remaining cost-conscious and seeking efficiency and value from their spend. In Q4, we saw usage growth from existing customers that was roughly similar to the usage growth in the year-ago quarter. Next, we continue to see robust contribution from AI native customers who represented about 6% of Q4 ARR, roughly the same as last quarter and up from about 3% of ARR in the year-ago quarter. AI native customers contributed about 5 percentage points of year-over-year revenue growth in Q4 versus 4 points in the last quarter and about 3 points in the year-ago quarter. So we saw strong growth from AI native customers in Q4. We believe that adoption of AI will continue to benefit Datadog in the long term. Meanwhile, we did see some optimization and volume discounts related to contract renewals in Q4. We remain mindful that we may see volatility in our revenue growth on the backdrop of long-term volume growth from this cohort as customers renew with us on different terms, and as they may choose to optimize cloud and observability usage. Next, as we look at usage growth by segment, similar to recent quarters, we are seeing the strongest year-over-year usage growth from our enterprise customers. Meanwhile, our SMB customers' usage growth remained solid with slight year-over-year acceleration versus last quarter. 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 trailing 12-month net revenue retention percentage was in the high 110s in Q4 compared to the mid-110s last quarter. And finally, our trailing 12-month gross revenue retention percentage remained stable in the mid- to high 90s. Regarding our customer growth, we added 800 net customers in Q4 for a total of around 30,000 customers. This includes the highest number of gross new logos and dollar new logo annualized bookings since early 2023. Now moving to our financial results, billings were $908 million, up 26% year-over-year. Remaining performance obligations, or RPO, was $2.27 billion, up 24% year-over-year. Current RPO growth was in the mid-20s percentage year-over-year. RPO duration was down year-over-year. Normalizing for duration, RPO growth was in the mid-30s year-over-year. We continue to believe revenue is a better indication of our business trends than billings and RPO, as those can fluctuate 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. First, gross profit in the quarter was $603 million for a gross margin of 81.7%. This compares to a gross margin of 81.1% last quarter and 83.4% in the year-ago quarter. Our Q4 OpEx grew 30% year-over-year accelerating from 21% last quarter as we continue to execute on our hiring plans. This includes our successful investment in sales and marketing, which grew 31% year-over-year in Q4 2024 to 23% of revenues, up from 5% year-over-year growth in Q4 of 2023 at 22% of revenues. We ended 2024 with sales and marketing headcount of about 3,000, up from about 2,400 at the end of 2023. This also includes our successful investment in R&D, which grew 29% year-over-year in Q4 2024 to 29% of revenues, up from 15% year-over-year growth in Q4 last year at 28% of revenues. We ended 2024 with R&D headcount of about 3,100, up from 2,400 at the end of 2023. Q4 operating income was $179 million or a 24% operating margin compared to 25% last quarter and 28% in the year-ago quarter. Now turning to the balance sheet and cash flow statements. We ended the quarter with $4.2 billion in cash, cash equivalents and marketable securities. In December, we issued a 5-year $1 billion convertible note. We used $122 million of the proceeds for transaction costs and cap calls associated with these notes. And simultaneous with the issuance of these notes, we've repurchased approximately 15% of our outstanding 2025 convertible notes and terminated the associated cap calls for a net cost of $142 million. After taking into account this issuance and repurchasing activity, our cash balance increased by $736 million net. $636 million principal amount of the 2025 convertible notes and associated cap calls remains outstanding, and we expect to retire the outstanding amount of the 2025 notes on or before their maturity date of June 15, 2025. Cash flow from operations was $265 million in the quarter. After taking into account capital expenditures and capitalized software, free cash flow was $241 million for a free cash flow margin of 33%. And now for our outlook for the first quarter and fiscal year 2025. First, our guidance philosophy remains unchanged. As a reminder, we based our guidance on trends observed in recent months, and apply conservatism on these growth trends. So for the first quarter, we expect revenues to be in the range of $737 million to $741 million, which represents 21% year-over-year growth. Non-GAAP operating income is expected to be in the range of $162 million to $166 million, which implies an operating margin of 22%. And non-GAAP net income per share is expected to be $0.41 to $0.43 per share based on approximately 366 million weighted average diluted shares outstanding. And for the full fiscal year 2025, we expect revenues to be in the range of $3.175 billion to $3.195 billion, which represents 18% to 19% year-over-year growth. Non-GAAP operating income is expected to be in the range of $655 million to $675 million, which implies an operating margin of 21%. And non-GAAP net income per share is expected to be in the range of $1.65 to $1.70 per share based on approximately 369 million weighted average diluted shares outstanding. Now for some additional notes on this guidance as it relates to our growth in OpEx and hiring. First, we successfully executed on our hiring plans in 2024, ending the year with about 6,500 employees, growing 27% year-over-year. And we remain excited by our numerous long-term growth opportunities. Our operating profit guidance reflects our intent to continue to invest for future growth in 2025. Because of that, our operating profit guidance implies operating expense growth in the high 20s percent range year-over-year. As we did in 2024, we expect to grow our investments in both sales and marketing and R&D this year. As I discussed earlier, in Q4, sales and marketing expenses grew 31% year-over-year and R&D expense grew 29% year-over-year. We continue to expand our capabilities in sales and marketing, including expanding in our less mature geographies, adding more channel and alliance capabilities and extending our efforts around larger enterprises, among many other initiatives. And in R&D, we are focused on delivering more value to our customers, both in expanding the number of products for our customers and the capabilities we add as part of the Datadog platform. Meanwhile, we continue to balance our investments in long-term growth with financial discipline, as we have executed in the past. Now turning to the other areas of the P&L. First, we expect net interest and other income for fiscal 2025 to be approximately $120 million. Regarding taxes, our non-GAAP tax rate is 21% in fiscal year 2025, and this is reflected in our non-GAAP net income per share guidance. Next, we expect our cash taxes in 2025 to be about 1% of 2025 revenues or about $30 million to $35 million. While we have utilized the majority of our U.S.-based NOLs, we have R&D tax credits and deductions related to stock-based compensation that reduced our cash tax payments. Finally, we expect capital expenditures and capitalized software together to be in the 4% to 5% of revenues range in 2025. Now to summarize, we are pleased with our execution in 2024. We are well positioned to help our existing and prospective customers with their cloud migration and digital transformation journeys. And we continue to invest in our growth opportunities in 2025. I want to thank all Datadogs worldwide for their efforts last year, and I'm very excited about our plans for this year. And with that, we will open the call for questions.

Our first question comes from Mark Murphy with JPMorgan.

Great to see the record bookings in Q4. I'm curious how you're feeling overall about the book of business for AI native customers. We recall you anticipated several months ago that some of them were growing so rapidly that they would increase their commitments with better terms. And I'm curious if the developments that you mentioned on the call aligned with that, or whether any of that might become so large that they would try to handle observability in-house. So in other words, I'm trying to understand if the AI usage and commitments are kind of on the same trajectory that they were on or whether you feel that there are some oscillations there.

Thanks for the question. Overall, what occurred during the quarter aligned closely with our expectations from the previous earnings call. In the AI cohort, we observed renewals with increased commitments, improved terms, and optimized usage, which is typical for larger end customers during renewals as they aim to maximize their value. This often leads to better pricing and increased commitments, followed by a flat or declining month or quarter, while still maintaining strong growth compared to the previous year and future growth potential. The cohort as a whole, despite significant renewal optimization and improved unit economics, showed stability in revenue quarter-to-quarter, with considerable growth from the prior quarter. Additionally, with some very large customers experiencing exceptionally fast growth—perhaps the fastest in the tech industry—there are still those who prefer to manage their observability or monitoring in-house. This choice is generally cultural, as it’s not economically sensible unless they have immense scale, exceptional talent, and aren’t limited by engineering bandwidth for innovation. These conditions rarely occur simultaneously. Among the top companies in the world by infrastructure size, some build everything in-house without using third-party software, while others do incorporate third-party solutions, including our services for parts of their operations. However, these top companies have never been the target market for software or SaaS. Instead, the broader market is our core focus. In discussing the AI cohort, we find it noteworthy not just because of the relatively small number of native companies but as an indication of future AI adoption trends and how the broader world will start utilizing our workload and grow accordingly.

Okay. Understood. And then just as a very quick follow-up, Olivier, either for Olivier or David. All three major hyperscalers did miss their Q4 revenue forecasts. And they were talking about capacity constraints on the AI side. But the non-AI side for some of them seemed to slow just regular typical cloud migrations. And I'm just wondering if you felt the timing of the holidays, excuse me, had any impact on December or whether their AI capacity constraints might be flowing through to Datadog as well?

It's challenging to determine precisely what is happening regarding the AI capacity constraints. When comparing our growth to that of cloud providers, we're experiencing slightly faster growth despite the significant boost those providers receive from GPU sales, which we don't monetize effectively. This is partly because those GPUs are mainly linked to trading workloads that we don't heavily engage in, and partly due to these new infrastructures having varying needs as they get adopted by more companies. If you exclude the AI-related growth from the top providers, they are indeed showing a slowdown, while we are significantly outpacing them in that part of the business. Broadly speaking, our growth aligns with the ongoing trends in digital and cloud transformation, which continue to progress and will support our growth now and into the future.

Our next question comes from Sanjit Singh with Morgan Stanley.

Congrats on the record bookings quarter in Q4. Olivier, I want to talk on the sales and marketing side, how you're thinking about this year in terms of the magnitude of change versus the prior year, whether it's relating to the investments in underserved geos or the channel partners or continuing to serve the enterprise opportunity? What do you have in store for the sales organization going into 2025?

We have a lot planned. We're focusing on certain areas of the business where we believe we're about to see significant growth. For instance, we discussed several customer wins today, including successes with Flex Logs. We believe that both logs and Flex Logs have the potential for much wider market adoption. Additionally, there seems to be an advantageous opportunity in the competition as some major players have recently exited the market. We are concentrating our efforts in these areas. Another product we’re excited about is OnCall, which has just launched and is already seeing strong demand. We're ensuring that we have the appropriate go-to-market strategies in place for these products. If we look beyond specific products or partners, the key focus is on increasing our sales capacity. We made progress last year, though we had a slower start in the first half than we hoped. However, we picked up speed in the second half and are continuing to grow our sales capacity, expecting positive results from this. Generally, when you invest in sales and marketing, the impact usually becomes evident within 1 to 2 years. For engineering and R&D investments, the effects are typically seen in 2 to 3 years. That's the direction we're heading towards.

That makes total sense. And just as a follow-up, actually, I was going to ask about logs and Flex Logs, it sort of dominated a lot of your customer highlights this quarter. In terms of logs becoming sort of renewed focus across the observability stack. You obviously have some incumbents. But is there anything sort of changing technologically? You guys have obviously, I think, rearchitected your log platform. But what seems to be driving the renewed interest in logs and cloud SIEM that gets you excited about the opportunity?

There is a combination of new technologies and economics related to these technologies that appeal to customers. Now, you can store much more data for a longer period at a lower cost. This is one key aspect. Another important factor is that modernizing the technology stack is focused on being cloud-first and cloud-based, which was not true for the platforms we previously used. Additionally, there are opportunities to unify some of the operational and security aspects. We see significant demand for Cloud SIEM alongside Flex Logs, and we find the competition in this space quite interesting. Together, these elements are driving the renewed interest in this segment of our business, which is why we are emphasizing it.

Our next question comes from Raimo Lenschow with Barclays.

There's a lot of focus on the major AI players right now, but that's just the beginning of the AI opportunity. What are your observations regarding inference workloads and the need for observability? I believe that will be a significant opportunity in the long run. What do you think? I also have a follow-up question for David.

Yes. On the inference side, most customers are using a third-party model, either through an API or a third-party inference platform. They are primarily focused on assessing whether that model is functioning correctly. Currently, we provide this through our LLM observability, which has seen significant adoption, largely not from AI-native companies. Right now, there are relatively few customers fully operating the inference stack, but we believe that will change in the future. We are excited about the developments in this area. There are many viable options emerging for running AI inference, including a robust set of commercial API-gated services and open-source models that are competing in quality with the best closed API models. We see the ecosystem evolving into a rich diversification, offering customers various modalities for utilizing AI, which is very promising.

Okay. Yes, that's really exciting. And then, David, like if you think about the increased investments that we're seeing across sales and marketing and R&D, obviously, we could have kind of taken kind of an accelerated approach or an approach there like this time last year, the year before, et cetera. What drives your confidence or what drives the decision to kind of think this year? Like what are the signals that you're seeing out there to kind of get you excited about that?

Yes. It's really bottoms up. We look at the geographies in one case where we see the white space and the evidence of success and attainment and the accounts that, as we talked about internationally, we don't fully cover. Next, as you know, we've been developing our channel and our partnerships. We think there's a big opportunity there. So we've been increasing our investment and see return on that, the percentage of our sales that are affected by channel partners has been increasing. So there's evidence there. And then in terms of across the different types of customers, we see very large enterprise customers that need to be treated in a certain way and have been increasing the way we go to market. Of course, we go bottoms up, but we also have an increasing effort in some key accounts. So all of those things are based on the evidence of the demand cycles we see in our results to date.

One thing to keep in mind when we consider growing our sales capacity and its relationship to business growth and guidance for this year is that revenue is based on usage, which is only loosely related to the bookings we receive from the sales team. Therefore, when we think about the guidance we are providing and our outlook for the year, it is all grounded in recent usage trends that we project into the future, and it doesn’t heavily factor in many of the long-term benefits we gain from scaling our go-to-market strategy.

Yes. Just to add. I think we've said that in some quarters, the bookings and RPO numbers might diverge from the ARR and revenue growth. I think in this quarter, you see there's pretty good convergence, right? They all point to the same range, etc. We certainly have the motion, as you mentioned, of assigning commits and then working with clients to use those commits and then go above that. That hasn't changed. So the amount of spread between usage and commits is similar to what it's been. I think you're correct. A lot of what we do operationally in our customer success, our technical account management, our product management, our marketing is about trying to get our customers to use more of the platform. And in the metrics we show, both in terms of revenues of the different product areas and in the cross-sell metrics that continue to be strong. I echo what Oli said was when we provide the guidance, we really haven't changed our methodology. We take what we know from those trends and we've essentially put conservatism going forward. So I think you can't necessarily go one-to-one there, and we've not changed our approach in doing that and providing guidance.

Our next question comes from Matt Hedberg with RBC.

David, it was encouraging to see the net revenue retention improve somewhat. I understand it's based on trailing twelve months, and this year has shown considerable stability. I'm curious about your retention perspective for 2025. Also, regarding the digital and AI aspects mentioned earlier, does your guidance anticipate a consistent contribution throughout the year?

Yes, regarding the first question, it has shown an upward trend. There are essentially two main factors that influence our revenue guidance. The most significant one is net retention, followed by contributions from new customers. As you might have guessed, we take net retention into account and apply a discount to it. When considering the contribution from AI, we incorporate that into our discount level. We are cautious and do not anticipate a non-pro rata acceleration of AI. While there is certainly a substantial opportunity, we do not assume it will occur. We apply a conservative approach to our net retention or expansion rate across our entire customer base, without trying to predict exactly where the growth potential may lie.

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

I appreciate all the disclosure on ARR coming from the three core pillars here on infrastructure monitoring, APM and logs. And so as we move into 2025 and beyond, how do you think about the potential for infrastructure monitoring specifically the growth there to accelerate from current levels? And what would be the trigger for that?

That's a good question. There are several new use cases related to infrastructure that we might want to explore. These use cases are genuinely emerging, and we still need to understand the actual needs from a large group of customers. Specifically, I am talking about infrastructure concerns around GPU management and optimization, which present a significant opportunity for us. However, to pursue this, we need to observe broad usage of raw GPUs by a large number of customers rather than just a small group of native customers, which is mostly what we are seeing today. There are also interesting segments of the market that we are not currently tapping into, such as large IoT fleets or on-premises setups. These are components of our customers' operations that we weren't initially designed to handle, but they are now becoming relevant as these customers find a balance between what they host in the cloud and what they keep on-premises. Therefore, we recognize opportunities in that area as well. Additionally, we have been enhancing our network monitoring capabilities, which is another area with potential. Overall, we see significant opportunities ahead. The largest opportunity remains in faster monitoring, where we are clearly the market leader; however, we still capture only a small share of the growing cloud market. Our efforts are focused on ensuring we can attract the right customers. Currently, we still serve just under half of the Fortune 500, and for those customers, we aim to integrate with all their workloads and environments and continue expanding our reach.

Got it. And just a follow-up here on FX and the impacts to revenue and guidance. And so I know the vast majority of contracts are in USD, about 30% of revenue being international. Are you considering some changes in pricing and packaging, making pricing more localized for international customers? And then also trying to understand any benefits to operating margin from FX in 2024 and how that may be accounted for in the 2025 guide?

Yes. As you know, we primarily operate as a U.S. dollar-based company, so our exposure is relatively low. We do sometimes consider local billing, but it's not a significant factor. This is all included in our offerings to clients. Additionally, unlike other companies, foreign exchange fluctuations do not have a major impact on our financial results.

Our next question comes from Eric Heath with KeyBanc.

Oli, you talked about Flex Logs having a lot of success, some M&A in the marketplace that's opened up some opportunity. But just curious from displacement activity that you're seeing with some of the recent M&A takeouts on the SIEM and log management vendors and curious also about your ability to win both the logs and security use cases because in our feedback, talking to customers and channel, it sounds like it's oftentimes one or the other, but not both loads. So, I'm curious about your ability to win both of those workloads.

Yes. First of all, we see a lot of success with some of the migrations, particularly to Flex Logs. The majority of the use cases are centered around DevOps rather than SIEM initially. However, we do see several opportunities that start solely from SIEM. You're correct that these areas typically don't align because they are generally acquired by different parts of the organization, and they may emerge at different times or be driven by different motivations for change. What we're observing is that with the increasing number of migrations to Flex Logs, we usually begin with a few workloads in Flex Logs and operations. Following that, we notice more workloads in operations opening up along with some discussions on the SIEM side. Historically, converting the SIEM side has been more challenging due to its deep integration with numerous specific queries and workflows that rely on legacy products. However, we have developed a significant amount of functionality not only to match the capabilities that have been utilized for those custom components but also to assist customers in the migration process. This is part of our initiatives this year aimed at accelerating our go-to-market efforts with those products.

Awesome. And Oli, I'd love to just get some of your thoughts on Agentic AI and AI generally. Just curious, when we think about agents, which parts of the core observability platform do you think are most relevant or going to be most beneficial to your business as you start to monitor those?

Yes, it's a bit challenging to predict because this is a very new field. My assumption is that a year from now, things will likely look different than they do today, just as this year is quite different from last year. However, we have noticed that when we began developing our LLM Observability product, most customer use cases were centered around chatbots or RAG, where the aim was to access and return information. Now, we see an increasing number of customers building agents that send data from those agents. This represents a clear trend of adoption, and the LLM Observability product serves as a useful abstraction layer for the current versions of these agents. That’s the current situation. Internally, we extensively utilize our products for development, identifying various opportunities to automate workflows with agents on our platform. Additionally, we observe the emergence of new and diverse modalities for developing these agents, and the market is evolving rapidly.

And our final question comes from Patrick Walravens with Citizens JMP.

Great. So Oli, I think you started touching on this, but you guys help your customers to digitally transform. But when you look inside of Datadog, what are some of the processes and the areas where you see the possibility to really drive some improvements?

Inside Datadog, what’s intriguing about the current evolution of AI is that it impacts various aspects of our business. The primary area that is undergoing transformation is the way software is developed. This includes the tools engineers use, how they write and debug software, and the operation of systems. This transformation involves not only the external tools we utilize for software development but also the internal use of our new products designed for incident resolution. Additionally, there are several other areas where we anticipate significant productivity enhancements, especially in customer support, onboarding, and troubleshooting. Ultimately, we expect to see improvements across all functions, from front office to back office.

And then the follow-up on that is, do you see your efficiency as an organization overall increasing where you can just grow with the same number of people? Do you feel like in the future, you're going to need to add the same amount of headcount to drive growth as you do today?

In general, we have a very efficient customer organization with strong sales efficiency metrics. We have been highly innovative, growing rapidly, and demonstrating our ability to deliver excellent margins. I view us as a highly efficient organization. Currently, any productivity gains in our R&D efforts are redirected towards enhancing our offerings and driving more growth. In the short to mid-term, I expect that productivity improvements in other areas of the business will also be reinvested into R&D to create more differentiation and accelerate scale in our go-to-market strategy. For the short to mid-term, this will be our expectation. Long-term, I anticipate that we will remain a highly efficient and profitable company, and I believe these advancements will further underscore that. All right. Thank you. And again, I want to thank the team for a super, super productive year. We have a lot planned, whether that's on the go-to-market side and scaling the company or on the product development side for 2025. So I'm really impatient to see how this unfolds and to share with everyone and our customers, in particular, everything we've been working on. So thank you all.

This concludes today's conference call. Thank you for participating. You may now disconnect.