Datadog, Inc. Q1 FY2025 Earnings Call

Good day, and thank you for standing by. Welcome to the Q1 2025 Datadog Earnings Conference Call. At this time, all participants are in 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 your first speaker today, Yuka Broderick from SVP of Investor Relations. Please go ahead.

Thank you, Antoine. Good morning, and thank you for joining us to review Datadog's first quarter 2025 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 second quarter and the 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 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 the Form 10-K for the quarter ended December 31, 2024. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended March 31, 2025, 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 to go through our Q1 results and what was a solid start to the year. Let me begin with a review of our Q1 financial performance. Revenue was $762 million, an increase of 25% year-over-year and above the high end of our guidance range. We ended with about 30,500 customers, up from about 28,000 a year ago. We ended Q1 with about 3,770 customers with an ARR of $100,000 or more, up from about 3,340 a year ago. This customer generated about 88% of our ARR. And we generated free cash flow of $244 million, with a free cash flow margin of 32%. Turning to platform adoption. Our platform strategy continues to resonate in the market. At the end of Q1, 83% of customers were using two or more products, up from 82% a year ago; 51% of customers were using four or more products, up from 47% a year ago; 28% of our customers were using six or more products, up from 23% a year ago; and 13% of our customers were using eight or more products, up from 10% a year ago. We are pleased to see that customers are adopting more products, and I'd like to highlight two of our newer products with you. First, Flex Logs is off to a fast start and now exceeds $50 million in ARR. Flex Logs has achieved this milestone in six quarters, which is the fastest ramp we've seen to that level, which echoes its value to customers as well as the size of the log management market opportunity. I'll also note that by adopting Flex Logs, our customers are adding new use cases at the right economics. And these Flex Logs adopters ultimately spend more on data log management as well as more on our overall platform. Second, our Database Monitoring product is approaching the $50 million ARR level as well and is growing 60% year-over-year. Database Monitoring has now been adopted by over 5,000 customers. We are very excited about the early traction we're seeing there and are doubling down on our investment into broader data observability as we see strong demand signals in that area, and we'll come back to that in a few minutes. Now let's discuss this quarter's business drivers. Overall, we saw trends for usage growth from existing customers in Q1 that were in line with our expectations. We are seeing high growth in our AI cohort as well as consistent and stable growth in the rest of the business. We also had a strong bookings quarter, with particularly strong execution in new logos and larger bookings. Dollar bookings for new logos were up over 70% year-over-year and much stronger than our typical seasonal softness in Q1. And on the large deal side, in Q1, we signed a total of 11 deals with a TCV of $10 million or more, up from just one in the year-ago quarter, as we continue to expand our business with larger customers. 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. Now moving on to R&D. We continue to see rising customer interest for next-gen AI observability and analysis. At the end of Q1, more than 4,000 customers used one or more Datadog AI integrations, and this number has doubled year-over-year. With LLM observability, we are seeing continued growth in customers and usage as they seek to manage end-to-end model performance, security and quality. I'll call out the fact that the number of companies using LLM observability has more than doubled in the past six months and we are adding to Bits AI with capabilities for customers to take action with workload automation and app builder using next-gen AI to help our customers remediate issues more quickly and move towards auto remediation in the future. Zooming up, we're making progress on all of our AI initiatives and you should expect more announcements in this area at DASH, our user conference taking place in June. Moving on to security. Our teams have been very busy building out products and features for our customers' DevSecOps needs. To give you a quick overview of our capabilities, first, we have a comprehensive set of products to identify and manage vulnerabilities across software and infrastructure. In infrastructure, our cloud security product identifies vulnerabilities in hosts, containers, Kubernetes clusters and infrastructure as code. Our security customers can use agentless scanning to cover their entire infrastructure stack in minutes and existing Datadog customers using our lightweight agent immediately gained deep granular and timely security visibility. On the application vulnerability side, our Code Security product identifies vulnerabilities in code from development to production and for first-party code as well as third-party open-source libraries. This product area has launched very recently and already has over 1,000 customers paying for the product. Because we bring visibility to production workload, we are uniquely positioned to identify which vulnerabilities are most critical in production and break down silos between developers, DevOps and security teams. Second, in security, as vulnerabilities face threats and attacks, our threat management product helps our customer identify and remediate them. They can use our Cloud SIEM to identify threats in logs and they can further protect from threats in infrastructure with workload protection and in software with app and API protection. Finally, our customers use our Sensitive Data Scanner product to discover, classify and redact sensitive data at scale across their logs, traces, events, user sessions, data stores code and all the way to LLM prompts. While we have much more to do, today, we are serving over 7,500 customers with our security products or about a quarter of our total customer base. And over half of our Fortune 500 customers use our security products, a good sign of our opportunities with the largest enterprises. Now moving on from security. Last month, we announced our plans to launch our latest data center in Australia. We see a large opportunity to serve our Australian customers and help them meet local data residency, privacy and security requirements. Finally, we recently announced a couple of acquisitions. First, we acquired Eppo, a next-generation feature management and experimentation platform. The Eppo platform helps increase the velocity of releases, while also lowering risk by helping customers to release and validate features in a controlled manner. Eppo augments our efforts in Product Analytics, helping customers improve user experience and tight feature performance to business outcomes. More broadly, we see automated experimentation as a key part of modern application development with the rapid adoption of AI generative code, as well as more and more of the application logic itself being implemented with non-deterministic AI models. Second, we also acquired Metaplane, a data observability platform built for modern data teams. Metaplane helps prevent, detect and resolve data availability and quality issues across the company's data warehouses and data pipelines. We've seen for several years now that better freshness and quality were critical for applications and business analytics, and we believe that they are now becoming key enablers of the creation of new enterprise AI workloads, which is why we intend to integrate the Metaplane capabilities into our end-to-end data observability offerings. We are very excited to welcome both the Metaplane and the Eppo teams to Datadog as we have a lot to build together, and that’s it for our products and engineering. Our teams are very hard at work this quarter and we're looking forward to sharing many new products and feature announcements at our DASH user conference on June 10 and 11 in New York City. Now let's move on to sales and marketing. As I mentioned earlier, we had a number of great new logo wins and customer expansions this quarter. So let's go through a few of those. First, we landed a seven-figure annualized deal with one of the largest U.S. car manufacturers. This customer has a complex hybrid environment, including on-prem, multiple clouds, in-car IoT, and mobile apps. They expect to unify observability across teams and across all their tech stacks while accelerating good cost analysis. They are starting with 13 Datadog products, consolidating a dozen tools and rolling out to dozens of business units. Next, we landed a seven-figure annualized deal with a major Latin American bank. They expect to use our unified observability to reduce operational costs and enable autonomy for departments that previously had to depend on specialized teams for visibility. This customer is starting with six Datadog products and is replacing three existing tools. Next, we landed a seven-figure annualized deal with a major American tech supplies company. These customers struggle with tool sprawl and limited user adoption. With Datadog, they expect to save over $1 million every year, both in engineering time and avoidance of lost revenue. This customer is starting with 11 Datadog products, including Cloud SIEM, and is replacing seven commercial tools. Next, we welcome back an insurance tech customer with a six-figure annualized deal. This customer found that their previous observability tool involved manual workflows and customization, high operational overhead and user frustration and adult fatigue. By returning to Datadog, they expect to benefit from Datadog's ease of use and out of the box capabilities while using our built-in usage controls to manage observability and cloud costs. This customer now expects to use Flex Logs, Cloud Cost Management and OnCall among the 10 products they plan to adopt. Next, we signed a seven-figure annualized expansion with one of the largest U.S. health insurers. This customer is using Datadog across dozens of business units to support millions of customers. More recently, they have been using Datadog to significantly improve customer experience and reduce time-consuming and expensive outages. As an example, one team estimated reductions in meantime to resolution from 3 to 4 hours down to 3 to 4 minutes by using Datadog. With this expansion, this customer is using 17 products in the Datadog platform, including the full Datadog security suite. Finally, we signed a seven-figure expansion as an annualized contract with a leading next-gen AI company. This customer needs to reduce tool fragmentation to keep on top of its hyper growth in usage and employee headcount. With this expansion, the customer will use five Datadog products and will replace a commercial tool for APM and log management. And that's it for another productive quarter from our go-to-market teams. Before I turn it over to David for a financial review, let's have a few words on our longer-term outlook. We recognize that there are many cross currents impacting the global economy right now, but our view of our long-term market opportunities remains unchanged. We continue to believe that 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 continue to focus on delivering innovation and value to our customers against their mission-critical needs, including their AI efforts. Now, more than ever, we feel ideally positioned to help customers of every size and enable the industry to transform, innovate, and drive value through technology adoption. And with that, I will turn it over to our CFO, David?

Thanks, Olivier. Q1 revenue was $762 million, up 25% year-over-year and up 3% quarter-over-quarter. To dive into some of the drivers of Q1 revenue growth, first, overall, we saw trends for usage growth from existing customers in line with our expectations and similar to the second half of 2024. We saw a continued rise in contribution from AI native customers who represented about 8.5% of Q1 ARR, up from about 6% of ARR last quarter and up from about 3.5% of ARR in the year-ago quarter. AI native customers contributed about 6 points of year-over-year revenue growth in Q1 versus about 5 points last quarter and about 2 points in the year-ago quarter. We continue to believe that adoption of AI will benefit Datadog in the long-term, but 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 as they may choose to optimize cloud and observability usage. Next, regarding usage growth by customer segment. Year-over-year usage growth with our enterprise customers remain healthy if a bit lower than last quarter, which we see as a product of the volatility that can occur among customers from quarter-to-quarter. Meanwhile, we saw strong booking activity from our enterprise customers in Q1. And as Olivier noted, this included some large TCV deals. From our SMB and mid-market customers, excluding the AI cohort, year-over-year usage growth was roughly similar compared to 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 as SMB as customers with less than 1,000 employees. Looking ahead to April, our usage growth was consistent with year-to-date trends. As usual, we have contemplated near-term trends in our guidance. Regarding retention metrics, our trailing 12-month net revenue retention percentage was in the high 110’s in Q1, similar to last quarter. Finally, our trailing 12-month gross retention revenue percentage remained stable in the mid to high-90s. On new logos, gross new logo additions were roughly the same as in Q1 last year, but dollar new logos increased 70% year-over-year, indicating a higher average land in the SMB, mid-market, and enterprise sectors. And our pipeline for Q2 is strong and growing healthily year-over-year. As a reminder, our sales pipeline doesn't convert into revenue immediately. Now moving on to our financial results. Billings were $748 million, up 21% year-over-year. Remaining performance obligations or RPO was $2.31 billion, up 33% year-over-year, and current RPO growth was about 30% year-over-year. RPO duration was roughly flat year-over-year. We continue to believe revenue is a better indication 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 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 $612 million and gross margin was 80.3%. This compares to a gross margin of 81.7% in the last quarter and 83.3% in the year-ago quarter. While gross margin remained in the range that we have expected long-term, our cloud hosting costs rose more quickly than we expected in Q1, as we supported large growth spikes from some of our largest customers. We also continue to innovate with new products and capabilities for our customers, which tend to put downward pressure on gross margins in the short term. While we expect some of the cost to support customers to persist, we are also focused on executing projects to improve our cloud cost efficiency and expect to realize savings throughout the rest of the year. Our Q1 OpEx grew 29% year-over-year, similar to the 30% last quarter and roughly as expected, as we continue to execute on our hiring plans. As we have spoken about in previous quarters, it has been our plan to grow our investments to pursue our long-term growth opportunities. And we've been successful in increasing sales rep headcount with over 25% year-over-year growth in total reps, including over 30% growth year-over-year in enterprise reps. This investment has been weighted a little bit towards international expansion, where sales rep headcount growth was in the mid-30%’s year-over-year. We believe that there is white space to support this growth and that we will keep seeing results as this capacity ramps as we have in the past. In addition, we grew our R&D headcount by over 30% year-over-year with R&D expense as a percent of sales at 30% in Q1, so we can deliver on the rapid pace of innovation for our customers. As always, we continue to prioritize our investments to balance near-term adjustments with our long-term plans and continue to look for opportunities to optimize our operating costs. Q1 operating income was $167 million for a 22% operating margin compared to 24% last quarter and 27% in the year-ago quarter. Now turning to the balance sheet and cash flow statements, we ended the quarter with $4.4 billion in cash, cash equivalents and marketable securities. Cash flow from operations was $272 million in the quarter. And after taking into consideration CapEx capitalized software, free cash flow was $244 million for a free cash flow margin of 32%. And now for our outlook for the second quarter and the full fiscal year 2025. First, our guidance philosophy overall remains unchanged. As a reminder, we base our guidance on trends observed in recent months and apply conservativism on these growth trends. So for the second quarter, we expect revenue to be in the range of $787 million to $791 million, which represents 22% to 23% year-over-year growth. Non-GAAP operating income is expected to be in the range of $148 million to $152 million, which implies an operating margin of 19%. As a reminder, in Q2, we will be hosting our DASH user conference, which we estimate to cost about $13 million and which we have reflected in our operating income guidance. Non-GAAP net income per share is expected to be $0.40 to $0.42 per share based on approximately 361 million weighted average diluted shares outstanding. To note, our weighted average diluted share count is expected to decline sequentially as the shares related to the 2025 convertible note will be removed upon redemption. For fiscal year 2025, in total, we expect revenue to be in the range of $3.215 billion to $3.235 billion, which represents a growth rate of 20% to 21%. Now we have raised our 2025 revenue guidance range by $40 million related to the previous guidance, which incorporates higher revenues in the first half of 2025 based on our Q1 results and our visibility as of today into Q2. Our implied guidance in the second half of 2025 is roughly unchanged. Non-GAAP operating income is expected to be in the range of $625 million to $645 million, which implies an operating margin of 19% to 20%. Relative to our previous operating income guidance range of $655 million to $675 million, the difference is mainly due to lower gross profit as a result of the previously discussed lower gross profit margins, offset by higher revenues. As we said before, we're focused on executing cost efficiencies in our cloud costs and believe our gross margins will remain in our historical range. Overall, plans for OpEx investment are roughly unchanged, with continued investment in hiring across R&D and sales and marketing. There are some changes with distribution within that. We expect $15 million of higher international costs due to currency rate changes and $10 million in net expected additional costs from our recently announced acquisition, offset by other OpEx savings. Non-GAAP net income per share is expected to be in the range of $1.67 to $1.71 per share based on approximately 362 million weighted average diluted shares outstanding. And finally, some additional notes on the guidance. The remaining approximately $635 million principal of our 2025 convertible notes will mature in June, and we expect to redeem this mainly in cash. We estimate that the GAAP purchase price from our Q2 acquisition activity will be about $180 million, of which we estimate about $110 million to be paid in cash during Q2. We expect net interest and other income for the fiscal year 2025 to be approximately $140 million. And we expect cash taxes to be about 1% of revenue or about $30 million to $35 million. We continue to apply a 21% non-GAAP tax rate for 2025 and going forward. And finally, we continue to expect capital expenditures and capitalized software together to be in the 4% to 5% of revenue range in the year. Finally, to summarize, we are pleased with our execution in Q1. We are well positioned to help our existing and prospective clients with their cloud migration and digital transformation journeys. And I want to thank Datadog’s worldwide for their efforts. Now with that, we'll open the call for questions. Operator, let's begin the Q&A. Thanks.

Thank you. At this time, we will conduct a question-and-answer session. Our first question comes from Mark Murphy from J.P. Morgan. Please go ahead.

Thank you so much, and congratulations on a great performance. Olivier, we noticed the CEO of Anthropic recently said that within 12 to 18 months that AI is going to be writing 100% of all code. I'm sure there's a bit of hyperbole there, but directionally, it's intriguing. Can you comment on the opportunity that might open up for Datadog if that sheer volume of applications being put into production starts to rise, because AI writes so much code so rapidly? And just does that AI-generated code require more or less monitoring than human-written code? And then I have a quick follow-up for David.

Yeah. That's a great question. And there's definitely a big transition that is happening right now. We see the rise of AI-written code. We see it across our customers. We also see it inside of Datadog where we've had very rapid adoption of this technology as well. While I don't think this is going to replace all our software engineering, and I'm pretty sure that Anthropic is still hiring software engineers too, I do expect big changes to come to the way software is being shipped and being run this way. The way we see it is that this means that there's a lot less value in writing the code itself, like everybody can do it pretty quickly, can do a lot of it. You can have the machine to do a lot of it and you complement it with a little bit of your own work. But the real difficulty is in validating that code, making sure that it's safe, making sure it runs well, that it's performing and that it does what it's supposed to do for the business. Also making sure that when 15 different people are changing the code at the same time, all of these different changes come together and work the right way and you understand the way these different pieces interact. So the way we see it is, this moves a lot of the value from writing the code to observing it and understanding it in production environments, which is what we do. So a lot of the investments we're making right now, including some of the acquisitions we've announced, are built towards that and making sure that we're in the right spot, so we can tell you exactly what every piece of code you've written, make sure that it works well, you understand it well, and it does what it's supposed to do for the business.

Okay. Very interesting. David, the booking statistics are impressive, with 11 deals over $10 million compared to only one a year ago. The combination of those large AI numbers is incredible. What do you attribute this level of booking strength to, especially in a quarter where concerns about a trade war seemed to affect business confidence? Can you comment on the strength of the bookings?

We entered the quarter with a strong pipeline, which aligns with our increased investments in go-to-market strategies, particularly in the enterprise sector. We have been effective in demonstrating value to our clients across the platform, enabling us to secure larger deals, consolidate, and enhance our value proposition. Much of this success can be attributed to our product strength and the growth in quota capacity.

We are closely monitoring our customer base for any signs of trouble, but so far, we haven't encountered any issues in our deal-making. Our sales cycles remain unaffected, and our pipelines are growing steadily. One of the new customers we mentioned is significantly impacted by tariffs and is adjusting its future plans. This situation highlights that cloud migration and observability are cost-saving tools for these companies, enabling them to save money and operate more efficiently, which positions us favorably in relation to their challenges.

To reiterate what Oli mentioned in our prepared remarks, we are observing that in Q2 we have maintained a pipeline quality that is higher than last year. This situation persists.

Thank you for the question, and congratulations on the quarter. I wanted to follow up on Mark’s comments. As we discuss the main drivers, particularly digital transformation and cloud migrations, what are the current trends in cloud migration? Based on your earlier remarks, Oli, it seems that cloud migration may actually increase even in a lower economic climate. In light of what we have observed in the early parts of the year, what are the trends regarding core cloud migration?

So it's very consistent. It's consistent with what we've seen before. It's also consistent with what you've heard from the hyperscalers over the past couple of weeks. So I would say it's steady, unremarkable. It's not really trending up, not trending down right now, but we see the same desire from customers to move more into the cloud and to lay the groundwork so they can also adopt AI because digital transformation and cloud migrations are prerequisites for that.

I want to discuss some additional opportunities for expansion into data observability. This has been a trending topic for the last couple of years, but it hasn't quite taken off yet. I would like to know more about the vision for moving into data observability and how significant an opportunity it could be for Datadog.

We have been monitoring this space for some time. Initially, we were concerned that the impact might be too limited, as we were only addressing the availability of reports for executives. Although this is certainly valuable, we worried it could represent a smaller market opportunity. However, we now realize that this field is evolving into a significant enabler for building AI workloads, or conversely, a hindrance if not approached correctly. It’s essential to ensure that data is extracted from the right sources, transformed appropriately, and integrated into the correct AI models. Our recent acquisition of Metaplane is a step towards enhancing this capability. Furthermore, we have already established some foundational tools for data observability, including a Data Streams Monitoring product for real-time data coming from sources like Kafka, a Data Jobs Monitoring product for monitoring Spark jobs and large data transformations, and a Database Monitoring product for optimizing queries and database performance. By incorporating data quality and data pipelines with Metaplane, we now offer a comprehensive suite that enables our customers to manage the flow of data from their core data stores into various products, AI workloads, and necessary reports. We believe this represents a significant opportunity for us.

Thank you, and congratulations from me as well. I have two quick questions, mainly for David. David, regarding the guidance, I know your team has always been conservative. You raised it more than the Q1 beat, which indicates you're seeing positive trends in Q2. What was your thinking behind presenting the potential upside for Q2 instead of being more cautious given the uncertain environment? My first question. The second question is about the change in gross margin guidance for the full year. Since this is three months after your initial guidance, could you remind us of what influenced that change and what actions you're taking in response? Thank you.

We haven't altered our strategy regarding guidance. When we evaluate recent trends, it's key to recognize that we exceeded expectations in Q1. We assessed the run rate and took into account the current growth rates, leading to a cautious outlook for Q2. This reflects our business pace while also considering ongoing trends. Additionally, due to market uncertainty, we have kept our second-half projections unchanged. Our approach remains consistent, but as we look further ahead, our visibility decreases. Therefore, our philosophy remains steady; it's simply a continuation of our current run rate. Regarding gross margin, we've consistently indicated that it would vary within a specified range. For a significant period, we've operated within the upper 70s to low 80s margin range. We designed the business to manage fluctuations by investing at times and optimizing at others. In Q1, we focused more on investment and experienced some irregularities from our customers, which we're learning to manage as we grow. From these insights, we believe we can improve our provisioning. As we've noted before, we operate across a spectrum. We encountered higher cloud costs than anticipated due to these two factors, and while some of this will continue, we will also work on optimization. This pattern of growth followed by optimization is consistent with our historical approach.

Yes, to reiterate, our engineers are focused on delivering functionality and improving performance. There is a certain margin that we are comfortable with. Last year, we felt very secure about our position, but we are now feeling slightly less secure based on recent trends. Therefore, we are reallocating some resources towards optimization to address this. As David mentioned, we are also introducing new features that may not be fully optimized initially in terms of system usage, and we have seen some rapid growth from our largest customers, which may continue, particularly as they take on new workloads. Our goal is to optimize, and we are confident that we can maintain our previous gross margin range or even improve it in the future. We have no doubts about that.

Hi. Thank you very much for taking my question. Oli, one for you and one for you, David. Oli, when you look at the AI market, certainly, it looks like we're about to move from training into inference. Where does it leave Datadog from a product perspective where you can add more consistent value without being optimized? And one for you, David. As you look at the stepped-up research development sales marketing investments, how from a financial perspective are we to see the incremental benefit of those incremental investments? Thank you so much.

On the workloads, we are shifting towards different areas and there is certainly more product development needed. We have created an LLM observability product that is seeing increasing adoption from customers as they transition to production. We believe there is additional development required both in terms of the underlying technology and the agents developed on top of these models. Expect to hear more from us at our upcoming conference regarding these topics, as there are significant emerging needs from customers moving towards inference.

Regarding our investments, we are committed to reporting regularly on our disclosures, particularly when they exceed or approach $50 million in areas like our database and Flex systems. This reflects our ability to generate revenue from our R&D investments, and we will continue to provide evidence of this in various product offerings. Our experience has shown that it typically takes two to three years to see the return on R&D investments due to the development of products. We are currently reporting on the outcomes of investments made in the past. In sales and marketing, we are focusing on identifying new end markets or customers that we previously did not serve, which allows us to expand our capacity, albeit with a ramp-up period. We anticipate that the increased capacity we are implementing will yield returns within a year as we onboard new representatives and begin to see results, and we will keep you updated on our progress.

We discussed Database Monitoring, a product that has gained significant traction. This product highlights the capabilities of our platform, generating nearly $50 million in annual recurring revenue with a considerable customer base. Remarkably, it was developed by just 10 to 15 individuals. This demonstrates how a small team can leverage our platform and existing services that gather customer data, resulting in substantial revenue growth within a short timeframe.

Great. Thanks for squeezing me in. The net-new adds 100K plus of 160 were the strongest since 4Q '22. Maybe just talk about the drivers of expansion there across new use cases, new products, share gains? And it sounds like some boomerang customers coming back to you as well. Thanks.

Yes, all of that is what we have. I'm pleased that the number is high, but the reality is it remains consistent, sometimes slightly lower or higher. All of our customers are progressing with us as they integrate more of their activities into our platform and increase their workloads with us as they grow. We are also very pleased to see some customers returning. One customer we mentioned has chosen to build their own solution using some commercial open-source options, but they decided to come back. This is a trend we observe. We are glad to see that, in the end, some customers who have tried everything, including us and our competitors, have recognized us as the best long-term choice. Perhaps we can end on that note.

Thank you. The question-and-answer session is now closed. I will now turn it over to Olivier Pomel for closing remarks.

All right. Thank you very much. So again, I want to thank all of our employees and customers for working with us and for us during the quarter. And I remind everyone that we are hard at work preparing for our conference DASH on June 10 and 11 in New York. We have a lot of exciting stuff to show there. So we expect to see as many of you there as possible.

Thank you for your participation in today's conference. This does conclude the program. You may now disconnect.