Good day, and thank you for standing by. Welcome to the Fourth Quarter 2023 Datadog Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers' presentation, there will be a question-and-answer session. Please be advised that today's conference is being recorded. I would now like to hand the conference over to the Vice President of Investor Relations, Yuka Broderick.

Thank you, Carmen. Good morning, and thank you for joining us to review Datadog's fourth quarter 2023 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 the fiscal year 2024 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, 2023. Additional information will be made available in our upcoming Form 10-K for the fiscal year ended December 31, 2023, 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 on 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 good Q4 to end what has been a very productive year for 2023. Throughout the year, we kept innovating at a fast pace, going broader and deeper into the problems we solve for our customers. We also continue to add new customers and expand with existing ones, driving both usage growth and adoption of new products. But most of all, I'm very pleased that we mobilized as a company to help our customers get through a tougher economic environment. We helped our customers make more efficient use of their cloud and observability, leaving them in a better position at the end of the year, from which they can focus again on growing their businesses and migrating to the cloud. Now, let me start with a review of our Q4 financial performance. Revenue was $590 million, an increase of 26% year-over-year and above the high end of our guidance range. We ended with about 27,300 customers, up from about 23,200 last year. We ended the quarter with about 3,190 customers with an ARR of $100,000 or more, up from about 2,780 last year. These customers generated about 86% of our ARR. We had 396 customers with an ARR of $1 million or more, compared to the 317 we had at the end of last year. And we generated free cash flow of $201 million, with a free cash flow margin of 34%. Turning to platform adoption, our platform strategy continues to resonate in the market. As of the end of Q4, 83% of customers were using two or more products, up from 81% a year ago. 47% of customers were using four or more products, up from 42% a year ago. 22% of our customers were using six or more products, up from 18% a year ago. And as a sign of continued penetration of our platform, 9% of our customers were using eight or more products, up from 6% a year ago. And our success with cross-product adoption isn't limited to core observability, as our newer products continue to gain traction. Note, for example, that the ARR for products outside of infrastructure monitoring, APM suite, and log management grew by more than 75% year-over-year. As a reminder, within the APM suite, we include core APM, Synthetics, RUM, and Continuous Profiler. During 2023, we continued to land and expand with larger customers. As of December 2023, 42% of the Fortune 500 are Datadog customers, up from 37% last year. We think many of the largest enterprises are still very early in their journey to the cloud. The median Datadog ARR for Fortune 500 customers is still less than $0.5 million, which leaves a very large opportunity for us to grow with these customers. Now, let's discuss this quarter's business drivers. In Q4, we saw usage growth from existing customers that was similar to Q3. Our usage growth during the quarter played out roughly as expected, including a strong start in October and the slowdown we typically see at the end of December. We also note that the greater intensity of optimization we've seen over the past six quarters appears to have dissipated. For the last couple of quarters, we have discussed with you a cohort of customers who are optimizing. In Q4, this cohort's usage grew at a faster pace than the broader customer base. We take this as a positive sign. To be clear, we see optimization activity with our customers every quarter. We expect them to continuously ensure they are using their cloud efficiently, and we'll keep helping them do that. And we do still see attention to cost in certain parts of our customer base, but overall, we see less headwinds than we did a few quarters ago. Meanwhile, we had a strong bookings quarter in Q4. Our go-to-market teams delivered our largest annualized bookings since Q1 of '22. And our enterprise team in particular executed on a record amount of annualized bookings in Q4. We are also seeing more customers enter into multiyear deals with us, which speaks to our deepening relationships with them, as well as customers planning for growth and for the longer term after a period of optimization and uncertainty. 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 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, we released over 400 new features and capabilities during 2023. Of course, that's too much for us to cover today, but let me speak to a few. In observability, we now have more than 700 integrations, allowing our customers to benefit from the latest AWS, Azure, and GCP capabilities, as well as from the newly emerging AI stack. We continue to see increasing engagement there with the use of our NextGen AI integrations growing 75% sequentially in Q4. In the Generative AI and LLM space, we continue to add capabilities to Bits AI, our natural language incident management copilot, and we are advancing LLM observability to help customers investigate how they can safely deploy and manage their models in production. Today, about 3% of our ARR comes from NextGen AI native customers, but we believe the opportunity is far larger in the future as customers of every industry and every size start deploying AI functionality in production. In the APM space, we launched Data Streams Monitoring to monitor queuing, streaming, and event-driven pipelines, which is a technically challenging type of workloads APM products have historically struggled to cover. We also rolled out single-step APM onboarding, allowing a single engineer to enable APM across complex applications in minutes. And with dynamic instrumentation, engineers can add logs, metrics, and traces to their applications on the fly without code changes or redeployment. In the digital experience area, we've added heat maps and scroll maps to our real user monitoring product to show developer and product owners what their users are actually seeing. And our customers can now create synthetic tests directly from Session Replay, for which we have received very positive feedback. And in log management, we continue to expand our capabilities. Starting with Flex logs, customers can have a very cost-effective way to retain their logs at a large scale. With error tracking for logs, customers can quickly cut down millions of error lines into a handful of actionable summaries. And our log pipeline scanner allows customers to inspect log events in near real-time, building greater visibility into data quality and data governance. In Cloud Service Management, we made workflow automation generally available, enabling customers to easily automate and orchestrate processes across operations and security. And today, we are announcing the general availability of case management to provide engineers with a single view for investigations, ticketing, to-do items, tasks, and follow-ups across the Datadog platform. Moving on to Cloud Security, we kept executing against an ambitious roadmap and are pleased to know count over 6,000 customers using one or more Datadog Security products. This month, we launched software composition analysis to enable our customers to proactively detect and remediate vulnerabilities before the code gets to production. We announced Cloud Infrastructure Entitlement Management to help customers prevent identity and access management security issues. We shipped cloud SIEM investigator, so customers can conduct deep security investigations using logs over long periods of time. We simplified security operations with our security inbox to allow our customers to correlate security issues into one single list to investigate and remediate. And we also expanded our data security capabilities. Sensitive Data Scanner is now able to find secrets and sensitive data in traces and run events, in addition to logs. In Software Delivery, we launched Intelligent Test Runner, which dramatically accelerates the testing process in CI/CD. And we shipped code quality and security gates to enforce best practices, catch security vulnerabilities, and prevent flaky tests. And last but not least, we delivered on a number of platform-wide initiatives. We launched our latest data center in Japan to help customers comply with local data privacy laws. We opened up CoScreen throughout our platform for collaboration, incident response, pair programming, and debugging. We extended Cloud Cost Management, which is now GA for AWS and Azure and will soon be for GCP, to offer a comprehensive view of costs across our customers' cloud footprint. And we announced our intent to achieve FedRAMP High and Impact Level 5 authorizations. So I'd like to thank our product and engineering teams for a very productive 2023, and I'm very excited with what we have planned for 2024. Let's move on to sales and marketing. First of all, I'd like to welcome Sara Varni to the team as our new Chief Marketing Officer. Sara brings more than 15 years of marketing experience centered around developers and enterprise software, and we really look forward to her leadership in this pivotal role. As I said earlier, we had a very strong close to 2023, with record levels of bookings and some very exciting new logos and expansions. So let's discuss some of our wins. First, we signed a three-year expansion and our first-ever nine-figure TCV deal with a major global fintech company. This expansion brings us into a major new business unit that we were not deployed in before. This time, the customer focused on bringing end-to-end observability to their mobile applications, aiming in particular to be in front of any user-impacting issues through the use of our Real User Monitoring product. With this renewal, this customer expects to use 15 Datadog products and will consolidate what used to be 10 separate tools, including the replacement of three commercial products across infrastructure monitoring, APM, and RUM. Next, we signed a seven-figure expansion with one of the world's largest restaurant chains. This customer is using AWS, Azure, GCP, and Oracle Cloud and believes Datadog is the only platform that can deliver a consistent experience across all four clouds. With this expansion, the customer plans to deploy Datadog for Cloud Service Management use cases and will expand to a total of 10 Datadog products. Next, we signed an eight-figure multiyear expansion with a leading European financial services company. This customer is undergoing a large-scale migration to Azure and will expand its use of Datadog across on-prem, private, and public cloud. Today, Datadog is used by 3,000 users every month in over 400 teams to monitor 13,000 hosts. With the migration, Datadog's platform usage will expand to more than 1,000 teams and 50,000 hosts. This customer plans to use 14 Datadog products and consolidate more than 10 legacy open source and cloud monitoring tools. Next, we signed a seven-figure land with one of the world's largest food and consumer goods companies. This customer wants to be more proactive with risk mitigation and system resilience as they migrate to Azure. They also want to reduce the thousands of hours of engineering time they spend every year in incident triage. This customer brought in Datadog to be the observability foundation of their AIOps strategy, using Watchdog and our incident management capabilities. This new land includes 17 Datadog products, and the customer expects to consolidate at least six commercial observability tools. Finally, we signed a six-figure land deal with one of the largest US utilities. This customer is re-architecting its customer-facing website and re-platforming its customer support experience. They identified Datadog as the only platform that could still easily integrate end-to-end with their existing sales, customer experience, and data workflows. This customer expects to start with six Datadog products and they will displace two commercial observability tools in the process. And that's it for this quarter's highlight. Congrats again to our go-to-market teams for their great work in 2023, an excellent close of the year, and ambitious plans for 2024. Before I turn it over to David for a financial review, a few words on our longer-term outlook. During 2023, we continued to execute on our product innovation plans and we solved more problems and delivered more value to customers. As we enter 2024, it appears that the worst of cloud optimization may be behind us. We continue to believe digital transformation and cloud migration are long-term secular growth drivers of our business and critical motions for every company to deliver value and competitive advantage. We see AI adoption as an additional driver of investment and an accelerator of technical innovation and cloud migration. And more than ever, we feel ideally positioned to achieve our goals and help customers of every size in every industry to transform, innovate, and drive value through technology adoption. With that, I will turn it over to David.

Thanks, Olivier. Q4 revenue was $590 million, up 26% year-over-year and up 8% quarter-over-quarter. To dive into some of the drivers of this Q4 performance, first regarding usage growth. Overall, we saw usage growth from existing customers in Q4 that was similar to what we saw in Q3. Last quarter, we mentioned that the larger and more intense optimizers had begun to show signs of stabilization. In Q4, we saw those trends continue and the large optimizers begin to grow again. While we may still be in a cost-conscious environment overall, we believe that the higher intensity of optimization has dissipated, and clients are continuing to invest in new digital applications. For the first time in six quarters, our sequential ARR adds in Q4 were higher than in the year-ago quarter. As we look at early data for Q1, January usage growth was solid. The rebound we're seeing from the slower end of December is better than what we experienced last January. We note as always that it's too early to know how the quarter will play out, and we would caution investors from extrapolating too much, but we're encouraged by the near-term trend. Regarding usage growth by customer size, we experienced our highest growth in our largest and smaller spending customers in this quarter. This includes a record increase in sequential ARR added from customers who spend $1 million or more annually with us, and an expansion of 1 million plus customers from 317 to 396 over 2023. In terms of new logos, our customer additions on a gross and net basis, as well as on a new dollar — a new logo dollar basis were similar to that of Q3. As before, our net adds included slightly elevated churn in our very long tail of small customers, many of whom are self-service. Geographically, we experienced stronger year-over-year revenue growth in international markets in North America. Our international markets represented 31% of our revenue in Q4 2023, up from 28% in Q4 of last year. Finally, for our retention metrics, our trailing twelve-month net revenue retention was in the mid-110s in Q4. Our trailing 12-month gross revenue retention continues to be stable in the mid-to-high 90s. And our dollar churn is low and declined sequentially. Now, moving on to our financial results. Billings were $723 million, up 35% year-over-year. Billings duration increased year-over-year. Remaining performance obligations, or RPO, was $1.84 billion, up 74% year-over-year. Current RPO growth was in the mid-40s percent year-over-year. We are continuing to see increasing interest with our larger customers in multiyear commitments, which results in longer RPO duration in both total and current RPO. We welcome the opportunity to have these longer-term strategic partnerships with our clients. And we see that once customers are farther along in their optimizations, they feel comfortable committing over longer periods of time in the future. As we said before, we continue to believe revenue is a better indicator of our business trends than billings or 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 our 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 $492 million, representing a gross margin of 83.4%. This compares to a gross margin of 82.3% last quarter and 80.6% in the year-ago quarter. We continue to experience efficiencies in cloud costs reflected in our cost of goods sold as our engineering teams pursue cost savings and efficiency projects. Our Q4 OpEx grew 10% year-over-year, a decline from 17% year-over-year growth last quarter. As we discussed last quarter, while making meaningful investments in 2023, we were more cautious than in previous years given the macro condition and focused more on efficiency and optimization. We believe this will put us in a good position to accelerate investment in 2024 while maintaining margin discipline. Q4 operating income was $167 million, or a 28% operating margin, up from 24% last quarter and 18% in the year-ago quarter. As with last quarter, our margins ended up being higher than we expected in Q4 as we executed well on our internal optimization and cost management efforts. Turning to the balance sheet and cash flow statements. We ended the quarter with $2.6 billion of cash, cash equivalents, and marketable securities. Cash flow from operations was $220 million in the quarter. And after taking into consideration capital expenditures and capitalized software, free cash flow was $201 million with a free cash flow margin of 34%. Now for our outlook for the first quarter and the fiscal year 2024. 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 first quarter, we expect revenue to be in the range of $587 million to $591 million, which represents a 22% to 23% year-over-year growth. Non-GAAP operating income is expected to be in the range of $128 million to $132 million, which implies an operating margin of 22%. And non-GAAP net income per share is expected to be $0.33 to $0.35 per share based on approximately 357 million average diluted shares outstanding. For fiscal 2024, we expect revenues to be in the range of $2.555 billion to $2.575 billion, which represents 20% to 21% year-over-year growth. Non-GAAP operating income is expected to be in the range of $535 million to $555 million, which implies an operating margin of 21% to 22% and non-GAAP net income per share is expected to be in the range of $1.38 to $1.44 per share based on 361 million average shares diluted outstanding. Some additional notes on guidance. As it relates to our growth in OpEx and hiring, as I mentioned earlier, we took a more cautious attitude towards hiring during 2023. Our headcount ended fiscal 2023 at about 5,200 people, growing in the high single digits year-over-year. We remain excited about our numerous long-term growth opportunities. As a result, our operating profit guidance reflects our intent to invest for future growth in 2024. We intend to accelerate hiring in R&D to execute on our long-term growth opportunities and in sales and marketing to reach customers worldwide. Because of that, our operating profit guidance implies operating expense growth in the mid-20s range year-over-year, with operating expense year-over-year growth ramping throughout 2024 as we execute on our hiring plans. Meanwhile, we will continue to balance our investments in long-term growth with financial discipline as we have executed in the past. Now turning to other areas of the P&L. First, we expect net interest and other income for fiscal year 2024 to be approximately $100 million. Regarding taxes, while we expect to continue to be a modest cash payer in 2024, estimated to be $20 million to $25 million, we are establishing a non-GAAP tax rate of 21% in fiscal year 2024 and going forward. This is reflected in our non-GAAP net income per share guidance. We have recast our fiscal 2022 and '23 non-GAAP net income to reflect this non-GAAP tax rate, which is available in the tables in our earnings release as well as the financial supplemental. Finally, we expect capital expenditures and capitalized software together to be in the 3% to 4% of revenue range in fiscal year 2024. Now to summarize, we are pleased with our execution in 2023. We are well positioned to help our existing and prospective customers with their cloud migration and digital transformation journeys. We plan to innovate further and expand the set of problems we solve for our customers in 2024 and beyond. I want to thank Datadog's worldwide team for their efforts in 2023, and I'm excited about our plans for 2024. Finally, I'd like to invite you to join us for our Investor Day this Thursday in New York City. Please go to the Datadog IR website for the live stream or contact the IR team at [email protected] to attend in person. And with that, we'll open the call for questions. Operator, let's begin the Q&A.

Our first question is from Sanjit Singh with Morgan Stanley. Please proceed.

Thank you for taking the questions and congrats on the great bookings result to end the year. Oli, as we sort of come out of this sort of down cycle, reflecting the optimization cycle that we've seen for the last several quarters, I was wondering how you think about where the sources of growth are going to come from in terms of your various customer reports? I'm thinking about the digital natives, which drove a lot of growth in 2019, 2020, and '21 versus your enterprise opportunity and your mid-market customers. As we go into sort of the next cycle, where does that dollar growth do you think comes from for Datadog?

Well, it's a good question. I would say, pretty much all of the above. I think it's always a little bit hard to time the cycles for specific subsets of the customer base as various macro conditions ripple through the economy. We suddenly saw a big slowdown from the digital native over the past year. On the other hand, they might be the first ones to fully leverage AI and deploy it in production. So you might see some reacceleration earlier from some of them at least. If you zoom out a little bit, our focus over the past few years has been on really going to market aggressively in the enterprise, the mid-market, the more traditional side of the world that still has to largely transition to the cloud. We've planted a lot of seeds there with a number of large companies that still have relatively small deployments in the cloud. Our focus over the next couple of years is going to be to grow them and obviously land the ones we still don't have. We mentioned on the call that 42% of the Fortune 500 are Datadog customers, and they're still largely small, with a few hundred thousand dollars a year spent on us. So that's where we direct our efforts.

And I appreciate that thought. And one quick follow-up. When you get customers adopting almost 10% of the base, eight or more products and the number of customers you highlighted in your script had over 10-plus products, how are those deals being structured? Meaning that are they buying sort of individual SKUs at a time and adding them on over time? Or are they being folded into a rate card agreement or an enterprise licensing? Just how does that pricing and packaging work for customers that get up to that level of adoption?

In general, what we do is when we execute these larger multiproduct or consolidation deals, we have a specific rate card, and customers can have total fund commitments, allowing them to allocate the funds in real time to the products they need when they want them. This approach gives them a lot of flexibility that they don't have when they manage five different vendors for different parts of their coverage. There are some exceptions. There are some customers that have such a specific and large volume requirement for one product in particular, typically things like logs or maybe metrics and other areas where they get specific commitments in place around certain products. But in general, most customers have considerable flexibility when they take these commitments with us. We will show some examples at the Investor Day. The mix of spend can change over time with customers while we expand and cover more of their environment.

Thank you. One moment for our next question please. And it comes from the line of Mark Murphy with JPMorgan. Please proceed.

Thank you so much. David, the billings growth accelerated 5 points. It was also seasonally stronger than a year ago. And just eyeballing the CRPO figure, it's a pretty massive number. Is that strong bookings performance more tied to a small number of mega deals coming from your cloud data? Or did you feel that it was kind of a broader phenomenon across the multiple verticals? And then I have a quick follow-up.

There's a couple of aspects. First of all, given the sort of renewal cycle, Q4 tends to have more recommitments. So I think if you look back, you'll see that we tend to have nice billings growth. But in terms of where, it really was correlated with larger customers who, as Oli mentioned, are buying a more complete suite of Datadog products. It wasn't cloud-native or not cloud-native. It was our customers who have standardized on Datadog, who have a good sense of their volumes and have committed longer, resulting in a longer average billing and contract duration in Q4 than we have had previously.

We should emphasize that this is really a change of stance of the customer base compared to last year. Last year, customers were in optimization mode. They didn't know what their consumption should look like. They didn't know economically what they were shooting for as businesses. After a year of optimization, a year of examining everything, we see customers recommitting for much longer periods than they did before as they focus on growing and investing. Therefore, we like the setup a lot more than we did last year.

That's very encouraging. Thank you, Olivier. And just as a follow-up, if you think about the very long term, would you think attach rates of observability will end up being higher or lower for these AI workloads versus traditional workloads? Because on the surface, with AI, it's bringing the risk of hallucinations and bias, your products help to control that. It's also more computationally intensive and there's more value to unlock if the LLM runs reliably and creates that kind of great user experience. So I'm just wondering how you might think about that attach rate three to five years down the road?

We see the attach rate going up. The reason for that is our framework for that is actually in terms of complexity. AI just adds more complexity. You create more things faster without understanding what they do, meaning you need to shift a lot of the value from building to running, managing, understanding, and securing all the other things that need to keep happening after that. The shape of some of the products might change a little bit because the software that runs it has changed a little bit, which is not different from what happened over the past 10 or 15 years. But we think it's going to drive more need for observability and more need for security products around that.

Thank you. One moment for our next question please. And it comes from the line of Raimo Lenschow with Barclays. Raimo, please go ahead.

Hey, thank you and congrats from me as well. I have two quick questions, first for Olivier and then one for David. Olivier, if I think about some of your customers have some very, very large contracts. But then you talked earlier about if you look at the average kind of large customer is still relatively small in terms of their spending with you. Can you speak a little bit about the difference between one and the other? And then what you can do to kind of change that for those that are not spending as much with you? And then also maybe as part of that, like, is the competitive landscape changing with all the consolidation in the space of some of your larger competitors actually kind of being in a new home now? And then for David, any little more yardstick in terms of like how the timing of the investments plays out this year? I know you mentioned a comment that like, is there more sales and marketing earlier in the year to get the sales guide ramped in the latter part of the year. But how should we think about that modeling? Thank you.

So I'll start with the large companies that are still small customers. That's completely due to them being small in the cloud today. They might have one or two business units in the cloud with some fraction of the applications there. The goal is to have them consolidate on us as they move more into the cloud. We aim to go end-to-end in a specific business unit and then expand to the whole enterprise at the end. The difference between a customer that, like the ones we mentioned today who signed a nine-figure deal with us, and a customer that’s still at the low hundreds of thousands of dollars, is that the one that has that large deal has us pretty much wall-to-wall in a significant part of their business and has consolidated a large part of their observability. The good news is that all of that business is coming to us as these customers move into the cloud. The unfortunate part is that we don't drive the move to the cloud. So in periods where it goes a little bit slower than we've seen over the past year, that growth can be a little bit slower. But we are very confident in the fact that this is going to happen. AI is going to accelerate the transition, which will make it even more relevant. That trend is going to stay with us for the next few years. On the competition side, there's no real change; the situation is pretty much the same as it was last quarter and the quarter before.

On your second question, much of this growth is related to hiring, which takes time to do. We are trying to invest both in quota capacity, in terms of sales, as well as in R&D capacity. Our intent is to open up the heads earlier in the year to try to get returns in the near term. But I think you can assume that that investment will ramp throughout the year because it takes time to onboard the headcount in. We gave guidance for Q1 indicating what we think is going to happen during that quarter.

Thank you. One moment for our next question and it comes from the line of Ray McDonough with Guggenheim. Please proceed.

Great. Thanks for taking the questions. Maybe first for Oli or maybe for David. As you think about the investments you're making to the sales force and your hiring capacities, are there any changes you're making to your go-to-market motion? Are you adding incremental overlay sales forces for security or anything else we should be thinking about in terms of changes to the go-to-market motion?

There's no change at scale that we’ve made worth noting on this call. We've made a lot of adjustments in the way we sell all the time. We make adjustments in how we package our products. For example, we package some of our security products directly into our infrastructure and APM products. We have a new tier called DevSecOps for both APM and infrastructure, and these are great ways for us to actually bring those products into the conversation, make them easier for customers to discover, and also make them easier for the sales force to bring up and to sell. We're actually starting to see great success with that. It’s still early, obviously, because it was rolled out last quarter, but we like what we see with those SKUs. More broadly, we're investing in the sales force. We're increasing capacities. We've increased capacity last year even though it was a slowdown year in the economy, and we have plans to increase the capacity again this year. We think there's plenty more markets for us to be had, both in terms of the segments in which we're already very present, as well as in new categories and geographies that we don't cover very well yet.

Thanks. Maybe just as a follow-up, can you talk a little bit more about your pipeline construction? Specifically, how are larger opportunities weighted in your pipeline at this point? You talked a lot about more multiyear deals. You discussed the construction of billings and CRPO. But alongside that, can you talk about how long it typically takes to close an opportunity like the nine-figure deal you mentioned? Obviously, your go-to-market motion is more of a land and expand motion, but I'm just wondering if as you see larger opportunities in your pipeline, deals may be taking a little longer to close than typical.

Yes, due to our business approach, we aim to secure small deals quickly and then expand over time. We haven't observed any lengthening of sales cycles, even in what was a challenging year for many sales organizations. Sales cycles have remained stable, and our sales pipelines have been strong. As CEO, I can rely on the pipeline at the start of each quarter, and the forecast usually comes to fruition by the end. Generally, it grows during the quarter without large fluctuations, which reflects the effectiveness of our sales team's efforts and the strategy we've implemented. When discussing significant customers, those making substantial payments, these are usually expansion deals. We secure these by ensuring customer success over time and engaging with their teams when we launch new products, ensuring they have access to them. By the time we initiate a sales discussion, typically, the customers have utilized the product, understood its features, and communicated with our product teams. At that point, it becomes about how we commercially package and present the offering to customers, including what other products they might phase out. For new customers, the closing duration heavily relies on the initial deal size. Most of our initial contracts are small and can close quickly; however, for large enterprises, it might take a quarter or two, which is considered brief for enterprise deals but could extend for larger agreements.

Thank you. One moment for our next question please. And it comes from the line of Ittai Kidron with Oppenheimer. Please go ahead.

Thanks. And Oli, I wanted to dig into your comments on security. I think you mentioned that you have 6,000 customers that are now using one or more security products. Can you give us a little bit more color? First of all, who is the buyer usually? Do you see for these solutions initially? And then, second, maybe you can kind of parse out a little bit more color on ranking order kind of the more popular versus least popular security products right now? Would love to get more color on that.

The buyers depend on the product. For infrastructure security and application security, this tends to be the DevOps teams that start buying, with some involvement from the security teams on their end. For our cloud SIEM product, the buyer tends to be the security team. So we have a little bit of both, and it turns out we're successful in both ends. Both types of products are growing in a similar way. The focus has been over the past year on developing the products, getting them to maturity, getting them into the hands of as many customers as possible, and also ensuring maximum usage of those products. So the metrics we look at internally for our security products are even more than revenue, which can vary with usage and other factors. We look at the activity. How many of those customers are actually using the product, how many issues are being tracked, and how those issues are being resolved for the products. These are the North Stars we use as we develop those products.

Got it. And then as a follow-up, maybe just to dig into this a little more. When customers buy these, I mean, how often is it a vacuum there? There's no solution versus a displacement? Or how often do you kind of sit side by side with other solutions that do the same thing, like the companies had multiple monitoring solutions? Will they just have the same security solutions from other vendors, or is this a complete replacement or greenfield? Would love to get more color on that.

In most situations, we start side by side with other things, because customers typically have a patchwork of a lot of different security solutions. This is not very different from when we started selling our infrastructure and APM products. We have a number of customers spending more than $1 million a year on security, and a large number exceed $100,000 annually. Those customers tend to use less other products and consolidate more into what we have. The playbook here is the same for us as it has been for observability. The security products' ranking, in order of introduction, shows the cloud team has the most usage, followed by the other products still below that.

Thank you. One moment for our next question please. And it comes from the line of Mike Cikos with Needham. Please proceed.

Hey, guys. Thanks for taking the questions here. I guess first a question for David. Again, just coming back to the guidance here, wanted to get some more color, if we could, on December into January. So it's great to hear that January this year seems to be trending better than the seasonal drop that we saw in January of last year. Just wanted to get a better sense. The holidays seemed to play out the way that you guys expected, but can you provide some more color or parameters on that December holiday slowdown and how that is playing out in January versus where we stand today in mid-February?

Yes. As you said, we've seen, and we've tried to flag that in the second half of December, we have a slowdown of usage, particularly in our sort of more use-oriented products like logs. It played out very similarly to what we expected. I would caution everybody that it's too narrow of a data point. But the bounce back from that and the growth in January was stronger than the bounce back last year, and we'll have to see how the rest of the quarter plays out.

In general, throughout the rest of the company, we’ve seen a slowdown in December for good reasons. All sorts of environments get turned off and some companies close shop altogether for one week at the end of the year. It has become more pronounced starting last year as companies wanted to see some cost control, and maybe they automate some processes to downscale or shut things down at the end of the year. This year was consistent with last year. It’s hard to compare year-to-year exactly because some factors depend on which day of the week the holidays fall on and how much they impact usage. But overall, what we saw was very consistent with last year.

Great. Understood. And thanks for that, Oli. I do appreciate the additional color. And just for a quick follow-up here, I know that you guys are citing the expanded penetration of the Fortune 500, and it's great to hear the five percentage points increase when you think about the 42% of Fortune 500 customers using it today. Wanted to get a better sense. I know you guys are stating that those customers on average are still spending less than $500,000 with you. So I know it's a bit of a point in time here, but a two-part question. First, can you help us think about if you had 37% of the Fortune 500 last year and now 42% this year, how has that average spend per customer within the Fortune 500 increased over the last year? And then the second part of that question is, if the 42% of Fortune 500 customers with you are on average under $500,000 at this point, where does Datadog ultimately see that opportunity going, just given we're talking about the 400 new features and capabilities launched in the last year? Where does that spend increase to over time?

We’re not providing guidance on the expansion of that group. If you look at our larger customers and just observe the trend over time, you can see that in the land and expand model, we have had an increase in average customer size in the group over $100,000. We have customers in the tens of millions within that statistic, both inside and outside the Fortune 500. We see buying patterns in the tens of millions. Many of the larger, more traditional enterprises are just getting started, and there's a lot of upside is what we're trying to communicate.

Definitely, for customers in the Fortune 500, those in the hundreds of thousands should be in the millions to tens of millions with us in the end. There's no question about that.

Thank you. One moment for our next question please. And it comes from the line of Frederick Havemeyer with Macquarie Capital. Please proceed.

Hi, thank you very much. I wanted to ask a bit more of a forward-looking technological question here, perhaps to Oli. There has been quite a lot of, at this point, let's say, testing development, but a lot of interesting development with autonomous agents for DevOps-related tasks. So I'm curious, as you're considering the opportunity and potentially some of the risks also around Generative AI and perhaps like agentic usage of large language models, how are you thinking Datadog is positioned strategically, both from a and perhaps pricing perspective around this technology trend?

We think we're ideally positioned for that. It's one of the things we'll share some of our thinking on during our Investor Day. We've been actively building on our Bits AI assistant. We've been interacting with customers based on that. There are a number of ways for us to build on that and do more to automate work for our customers, and that's something we're working on. We also see a lot of demand and expectations on the customer side for incorporating Generative AI into the product. From a positioning perspective, we feel great about that. We don't have much more to share today, but it's definitely top of mind.

Sorry, I don't mean to ask about the Investor Day, it's too early here. So I look forward to that this week. Just quickly then also, I understand the perspective on complexity driving more usage of observability and DevOps tooling. But I think last quarter, we got an update on where GenAI-related operations were contributing to the business. Would you have any data or points to share about how much Generative AI in these use cases are contributing in Q4?

Yes, we said that 3% of our ARR comes from AI-native companies. It's hard for us to grasp exactly what is GenAI and what is not among our customer base and their workloads. The way we chose to do it is we looked at a smaller number of companies that we know are substantially all based on AI, like the model providers. We see the benefits on our end too. If I look at our Azure business in particular, there is substantially more than 6% that is attributable to AI-native as part of our Azure business. This trend is very true for us as well. It's harder to tell with the other cloud providers because they don’t break those numbers up.

Thank you for taking my question. It's great to be on the call. I would like to focus on the annual recurring revenue from AI-native companies. Are the product SKUs that these GenAI companies are using similar or different from those of other customer groups? When considering GenAI, it’s clear that these workloads are typically quite computationally intensive. How do these companies influence the financial model compared to traditional customer groups? Are there any differences worth mentioning?

Yes, there aren't many differences today. This is largely the same SKU as everybody else. These are infrastructure, APM logs, profiling, release, or monitoring tools that these customers are using. It's worth noting that they're in a separate world because they're largely the builders of the models, so all the tooling required to understand the models is less applicable to them. That's more applicable to their own customers, who also represent the rest of our customer base. We see the bulk of the market opportunity in the longer term, not in the handful of model providers that anyone is going to use. Regarding the economics, there are two parts to AI workloads today: training and inference. The majority of players are in training. Only a few scale with inference. The ones scaling with inference are the ones driving our ARR because we're present on the inference side, but not on the training side. This aligns with what you might see from some of the cloud providers, where a lot of players scaling the most are on Azure today in the inference area, while many other players remain largely focused on training. Thank you, everyone, for your time and attention today. We're excited about what's ahead and appreciate your continued support.