Datadog, Inc. (NASDAQ:DDOG) Q2 2024 Earnings Call Transcript

Datadog, Inc. (NASDAQ:DDOG) Q2 2024 Earnings Call Transcript August 8, 2024

Datadog, Inc. beats earnings expectations. Reported EPS is $0.43, expectations were $0.3726.

Operator: Good day and thank you for standing by. Welcome to the second quarter 2024 Datadog earnings conference call. At this time, all participants are in a listen-only mode. After the speakers’ presentation, there will be a question and answer session. To ask a question during this session, you will need to press star-one-one on your telephone. You will then hear an automated message advising you your hand is raised. To withdraw your question, please press star-one-one again. Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead.

Yuka Broderick: Thank you Michelle. Good morning and thank you for joining us to review Datadog’s second quarter 2024 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog’s co-Founder and CEO, and David Obstler, Datadog’s CFO. During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the third quarter and fiscal year 2024 and related notes, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations.

These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended March 31, 2024. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended June 30, 2024 and other filings with the SEC. This information is also available on the Investor Relations section of our website, along with a replay of this call. We will also discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com.

With that, I’d like to turn the call over to Olivier.

Olivier Pomel: Thanks Yuka, and thank you all for joining us this morning. We had a very productive second quarter. First, we welcomed thousands of Datadog users to our DASH conference in June, where we announced a broad range of exciting new products and new features for customers to observe, secure and act in their cloud environment, and we continued to add new customers and help existing ones as they grow in the cloud. Let me start with a review of our Q2 financial performance. Revenue was $645 million, an increase of 27% year-over-year and above the high end of our guidance range. We ended the quarter with about 28,700 customers, up from about 26,100 a year ago. We had about 3,390 customers with an ARR of $100,000 or more, up from about 2,990 last year, and these customers generated about 87% of our ARR, and we generated free cash flow of $144 million with a free cash flow margin of 22%.

Turning to platform adoption, our platform strategy continues to resonate in the market. As of the end of Q2, 83% of customers were using two or more products, up from 82% a year ago. Forty-nine percent of customers were using four or more products, up from 45% a year ago. Twenty-five percent of our customers were using six or more products, up from 21% a year ago, and 11% of our customers were using eight or more products, up from 7% a year ago. We continue to expand the capabilities of all of our products over time, enabling our customers to solve more of their critical challenges. These include our efforts in digital experience monitoring, an area of observability which includes synthetics and real user monitoring, or ROM, and both synthetics and ROM are seeing growing adoption and each product today represents more than $100 million in ARR, becoming our fourth and fifth products to achieve that milestone.

We have also been innovating rapidly in this area with recent capabilities including mobile app testing, feature flag testing, user journey visualization, and retention analysis, and with our recent announcement of [indiscernible] at DASH, we are excited to go further and allow our customers to consolidate of their usage and business insights into Datadog. Now let’s discuss this quarter’s business drivers. Overall, the business environment for Datadog was roughly unchanged from last quarter. More customers overall are growing their cloud usage, while some are continuing to be cost conscious. In Q2, we saw existing customer usage growth that was broadly in line with our expectations and consistent with the overall improved trend that we had experienced over the past several quarters.

Our usage growth with existing customers was higher than in the year ago quarter, and we saw continued healthy growth across our product line with newer products growing faster from a smaller base. Finally, churn continues to be low and gross revenue retention was stable in the mid to high 90s, highlighting the mission critical nature of our platform for our customers. Moving onto R&D, we held our DASH user conference in late June and were excited to announce many new products and features for our users. There’s too much for us to cover in detail, but let me review just some of the announcements we made in the past three months. In the next-gen AI space, we announced the general availability of LLM Observability, which allows application developers and machine learning engineers to efficiently monitor, troubleshoot and secure LLM applications.

With LLM Observability, companies can accelerate the development of AI applications into production environments and reliably operate and scale them. We also expanded Bits AI with new capabilities. As a reminder, Bits AI is a Datadog built-in AI copilot. In addition to being able to summarize incidents and answer questions, we previewed at DASH the ability for Bits AI to operate as an agent and perform autonomous investigations. With this capability, Bits AI proactively surfaces key information and performs complex tasks such as investigating alerts and coordinating incident response. Taking a step back and looking at our customer base, we continue to see a lot of excitement around AI technology. More customers are telling us that they are levering up on AI and ramping up experimentation with the goal of delivering additional business value with AI, and we can see them doing this.

Today about 2,500 customers use one or more of our AI integrations to get visibility into their increasing use of AI. We also continue to grow our business with AI-native customers, which increased to over 4% of our ARR in June. We see this as a sign of the continuing expansion of this ecosystem and of the value of using Datadog to monitor the production environment. I will note that over time, we think these metrics will become less relevant as AI usage and production broadens beyond this group of customers. Last but not least, we announced Toto, our first foundation model for time series forecasting, which delivers state-of-the-art performance on all relevant benchmarks. In addition to the technical innovations devised by our resource team, Toto derives its record performance from the quality of our training datasets and points to our unique ability to train, build and incorporate AI models into a platform that will meaningfully improve operations for our customers.

Moving on from AI, we had a lot more to show in Observability. We announced the general availability of Flex Logs, which expands our Logging without Limits approach and allows our customers to scale storage and compute separately for cost efficiency. Our customers can today use our new Log Workspace for log analysis. Log Workspace is an advanced analytic feature that allows users to connect datasets, build and visualize complex queries, and create readable, [indiscernible] views and reports. It is particularly relevant to customers who previously built sophisticated analysis and workflows in legacy log management tools. We announced the general availability of Data Jobs Monitoring, which allows data engineers to detect and fix issues with their Spark and Databricks workloads and to optimize the cost and performance of their data jobs.

Moving and transforming large amounts of data has grown importance and become a mission critical capability for many businesses, a trend that we believe will continue with the adoption of AI. With this, our data observability set of products is expanding. Data jobs monitoring works alongside our data streams monitoring product, which helps customers understand their queueing pipeline in moving components such as Kafka or RabbitMQ, and we’re increasingly providing visibility for data lakes and data warehouses such as Snowflake to deliver end-to-end data observability across customer data resources. Moving on from data observability, we introduced Kubernetes Autoscaling to all our customers to optimize forecast and performance while automatically right-sizing Kubernetes resources.

For our customers using OpenTelemetry, the Datadog agent will embed a fully configurable OpenTelemetry collector, giving [indiscernible] customers access to Datadog products such as container, network and universal service monitoring, and offering our customers what we believe will be the best fully managed OpenTelemetry experience in the market. In shifting left, our new live debugger enables developers to step through code directly in production environments and find the exact root cause of production errors. As I mentioned earlier, we are building up on our success in digital experience monitoring and [indiscernible] providing in-depth product and user insights for product managers and business owners. In the cloud security space, we launched a new application security capability called Code Security, which allows our customers to detect and prioritize code-level vulnerability in their products and applications.

We also announced Data Security, which allows our customers to automatically pinpoint sensitive data, starting in [indiscernible] today and expanding to other environments in the future. For instances where customers can’t or don’t want to deploy agents, our new agent-less scanning capability provides visibility into risks and vulnerabilities within hosts’ containers and [indiscernible] functions without requiring agents to be installed. Finally in the cloud service management space, we’re going further to allow our customers to take actions directly within Datadog’s platform. We announced the general availability of App Builder, which lets teams rapidly create self-service local applications and integrate them securely into their monitoring stacks, and we introduced Datadog On Call, a modern on-call experience with paging and internet management workflows fully integrated with observability.

Let’s move on now to sales and marketing. We again saw strong execution from our go-to-market teams this quarter and we added some exciting new customers while expanding with many more, so let’s go through a few examples. First, we landed our largest ever new logo win, a multi-year deal with total contract value in the tens of millions of dollars, with one of the largest banks in South America. This customer was using a commercial observability product as well as open source tools but didn’t have full stack visibility. With Datadog, they will enable end-to-end observability and they expect to transition to modern infrastructure with confidence. They also anticipate better management and predictability of their observability costs thanks to products such as Flex Log.

Next, we signed a seven-figure annualized land deal with one of the world’s largest travel management companies. This company was using a commercial log management tool but found it expensive and complex to support. They also worried about stability as the tool would crash and cause fire drills across the organization. By moving to Datadog and replacing this tool, they expect to drive significant savings with log management and will benefit from a unified platform across infrastructure monitoring and APM. Next, we landed a seven-figure annualized land with a security software company. This customer felt they were overspending on their commercial logging tool and lack of visibility led to issues catching incidents, with users notifying them first of outages.

This customer is now adopting the Datadog unified platform across all three pillars and displacing one commercial and two open source tools in the process. This customer also expects net savings of half a million dollars every year by switching to Datadog. Next, we signed a seven-figure annual expansion with a leading central bank in Europe. This institution became a Datadog customer three years ago to enable its ambitious plan to move half of its applications to the cloud over a couple of years, and they have been increasing their usage of Datadog as they moved into the cloud, displacing two commercial observability tools which they used in their on-premise environment. They have now adopted a total of 17 Datadog products. Next, we signed a seven-figure annualized expansion with a large American insurance company.

This company had been using Datadog for full stack observability at one business unit. With this expansion, they have chosen Datadog as their enterprise-wide observability provider. In comparing us to the performance of other tools, this customer measured strong [indiscernible] adoption and fewer incidents with Datadog, and in displacing its legacy ATM and log management, they expect to save over $1 million annually on tool costs alone. Finally, we signed a high seven-figure annualized expansion with a leading online gambling and entertainment platform. This long-time customer uses Datadog as its strategic observability partner, enabling full visibility across infrastructure applications, logs, network, and their public [indiscernible] with users spanning from hands on keyboard engineers all the way to their [indiscernible].

This renewal supports this customer’s expansion into new use cases through our security embedded into their operations by using all of our cloud security products, to build a culture of cost accountability with cloud cost management, and to take action using incident management and workflow automation. This customer to date has adopted 19 products in the Datadog platform. That’s it for another productive quarter for our go-to-market teams. Now let me say a few words on our longer term outlook. Overall, we continue to see no change to the multi-year trend towards digital transformation and cloud migration. We are seeing continued experimentation with new technologies, including next-gen AI, and we believe this is just one of the many factors that will drive greater use of the cloud and next-gen infrastructure.

As indicated by our many announcements at our DASH user conference, we are delivering rapid innovation at scale and we are helping our customers every day to deploy and scale the modern environment with confidence across observability, digital experience, cloud security, cloud service management, software delivery, and product analytics. Finally, I’d like to welcome two new leaders to our team. Yanbing Li is joining us as our Chief Product Officer. Yanbing has more than 25 years of product, technology and engineering experience spanning enterprise software, cloud infrastructure and AI at companies such as VMware, Google and Aurora. She will lead our product team’s efforts to expand the Datadog platform. David Galloreese is joining us as our Chief People Officer.

David has more than 20 years of HR experience at tech companies and large scale high visibility enterprises such as Figma, Wells Fargo, and Wal-Mart. He will help us drive the next chapter of growth and scale at Datadog. With that, I will turn it over to our CFO. David?

David Obstler: Thanks Olivier, and good morning to all. Q2 revenues were $645 million, up 25% year-over-year and up 6% quarter-over-quarter. To dive into some of the drivers of the Q2 revenue growth, first regarding usage growth from existing customers, the overall trend we saw was consistent with our expectations. In Q2, we saw usage growth from existing customers that was higher than usage growth in the year-ago quarter, and as we look across the first half of 2024, our usage growth was higher than the first half of 2023. We are seeing solid growth across our products. Our three pillar products continue to increase in customer penetration and usage, and our newer products across observability, cloud security and cloud service management are ramping.

Regarding usage growth by customer size in Q2, we saw strong performance amongst our largest customers, who spend multiple millions of dollars with us annually as they continue to return to growth and strike a balance between new deployment and focus on optimization. As we look at usage growth by segment, we saw the strongest growth with our enterprise customers, where year-over-year growth in usage has accelerated over the past several quarters. Over the same period, we have seen more steady year-over-year growth trends amongst our SMB and midmarket customers. As a reminder, we define enterprise as customers with 5,000 employees or more, midmarket as customers with 1,000 to 5,000 employees, and SMB as customers with less than 1,000 employees.

Regarding our retention metrics, our net revenue retention percentage was in the mid 110s in Q2, similar to the past couple quarters; but remember, this is a trailing 12-month measure and we’ve seen an increase in recent quarters as we look at the NRR quarterly trend. Finally, our trailing 12-month gross revenue retention percentage remained stable in the mid to high 90s. Now moving onto our financial results, billings were $667 million, up 28% year-over-year and similar to the trailing 12 months billing year-over-year growth. Billings duration was roughly flat versus a year ago. Remaining performance obligations, or RPO was $1.79 billion, up 43% year-over-year. As we’ve said before, contract duration has generally been increasing as customers choose more multi-year deals, and contract duration increased modestly in the year-over-year period relative to a year ago.

Current RPO growth was in the mid-30% year-over-year. We continue to believe revenue is a better indicator of our business trends than billings and RPO, as those can fluctuate on a quarterly basis relative to revenue based on the timing of invoicing and the duration of customer contracts. Now let’s review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. Gross profit in the quarter was $530 million, representing a gross margin of 82.1%. This compares to a gross margin of 83.3% in the last quarter and 81.3% in the year-ago quarter. Our Q2 opex grew 21% year-over-year and increased from 14% year-over-year growth last quarter.

As we mentioned last quarter, Q2 opex included $11 million in expenses related to our DASH user conference, and as we’ve discussed, we are investing in headcount in 2024 and the growth in opex reflects our execution on hiring in sales and marketing and R&D so far this year. Q2 operating income was $158 million, or 24% operating margin compared to 27% last quarter and 21% in the year-ago quarter. Now turning to the balance sheet and cash flow statements, we ended the quarter with $3 billion in cash, cash equivalents and marketable securities. Cash flow from operations was $164 million in the quarter, and after taking into consideration capital expenditures and capitalized software, free cash flow was $144 million for free cash flow margin of 22%.

Now for our outlook for the third quarter and the fiscal year 2024, first our guidance philosophy remains unchanged. As a reminder, we base our guidance on trends observed in recent months and apply conservatism on these growth trends. For the third quarter, we expect revenues to be in the range of $660 million to $664 million, which represents 21% year-over-year growth. Non-GAAP operating income is expected to be in the range of $146 million to $150 million, which implies an operating margin of 22% to 23%. Non-GAAP net income per share is expected to be $0.38 to $0.40 per share based on approximately 360 million weighted average diluted shares outstanding. For the fiscal year 2024, we expect revenue to be in the range of $2.62 billion to $2.63 billion, which represents 23% to 24% year-over-year growth.

Non-GAAP operating income is expected to be in the range of $620 million to $630 million, which implies an operating margin of 24%, and non-GAAP net income per share is expected to be in the range of $1.62 to $1.66 per share, based on approximately 360 million weighted average diluted shares outstanding. Some additional notes to our guidance, we expect net interest and other income for the fiscal year 2024 to be approximately $125 million. Next, we expect to pay cash taxes in the range of $20 million to $25 million, and we continue to apply a 21% non-GAAP tax rate for 2024 and going forward. Finally, we continue to expect capital expenditures and capitalized software together to be in the 3% to 4% of revenues range in fiscal 2024. Now to conclude, as Oli mentioned, we are pleased with our execution in the first half of 2024 and plan to continue to help our customers observe, secure and act in their modern cloud environments.

I want to thank Datadogs worldwide for their efforts in this. With that, we will open up the call for questions. Operator, let’s begin the Q&A.

Q&A Session

Operator: Thank you. [Operator instructions] Our first question is going to come from the line of Sanjit Singh with Morgan Stanley. Your line is open, please go ahead.

Sanjit Singh: Yes, thank you for taking the questions and congrats on Q2. I wanted to get your assessment of the demand environment, the spend environment, and your description of how the usage trends played out by end market and in-market versus enterprise was super helpful. Microsoft had noted that they saw some weaker usage trends in June. I just want to get a sense of if you look across your geographies, or even across some of your key verticals, anything that stood out sort of positive or negative in June going into July in terms of the usage trends?

David Obstler: Yes, thanks Sanjit, and hello. Again, as I think you’ve noted, we’ve said that we experienced strength in our enterprise segment and stability in our SMB segment, and that continued throughout the quarter. As far as the more recent trends for what we’re seeing towards the end of the quarter and also in July, very similar trends to what we saw in Q2 and for the first half of the year, so a continuation of higher usage growth than we saw in the comparable periods in the previous year.

Sanjit Singh: Understood. Then Oli, maybe for you, I know at the investor day, you sort of outlined the thoughts and strategy on M&A and identified the criteria. It sounds like your corp-dev team sees a lot of opportunity but the bar was pretty high, was the message from investor day a couple of months ago. I wanted to double-check your latest thinking on the M&A strategy with respect to potentially being–looking at more strategic or transformational, larger size deals. Has anything changed in the way you view M&A as part of the Datadog growth strategy?

Olivier Pomel: No, there’s no change to the way we see things. Because we have this [indiscernible] strategy where we’re building a consolidator and we’re bringing together many different use cases into one shared platform, we have very broad interest and a very ambitious road map in many different directions, so as a result, we cast a very wide net when it comes to M&A. There are many possible potential fits for us. Historically we’ve been very successful with doing a lot of small and medium-sized deals. At any point in time, we are going to look at a lot of deals that might be small or big. We expect the bigger deals to be fewer and far between as the bar is very high for those, and today we’re also not looking into anything that would be very material to the business.

Sanjit Singh: Understood, thank you Oli.

Operator: Thank you, and one moment as we move onto our next question. Our next question comes from the line of Raimo Lenschow with Barclays. Your line is open, please go ahead.

Raimo Lenschow: Perfect, thank you. Has there been any impact, or what are you seeing in terms of a reaction from customers around the Cloudstrike outage, because that’s obviously an event that impacted the whole industry. You guys, I’m sure, saw some of the ramifications there. Just talk a little bit about how that impacted you in the quarter, but also what it means to customer conversations. Thank you.

Olivier Pomel: Yes, so obviously this is something that was very much in the news, was very visible. It was particularly visible because it affected devices, airport kiosks basically and point of sale, that are in the field in front of consumers, and it was pretty much everywhere at once, so very visible incident. That being said, in the grand scheme of observability, it’s very unremarkable, so the Crowdstrike isn’t very visible to everyone, everywhere, but every single day there’s a hundred or a thousand companies that are having their Crowdstrike moment because they have outdated software–you know, third party software [indiscernible] they have built and that caused large business disruptions [indiscernible] and that’s what we deal with pretty much all the time.

What you see in the public eye is really a reflection of the value we provide every single day to our customers when it comes to preventing these issues, and whenever those issues happen, to remediate them extremely quickly. Of course, we had all of the interactions you can imagine with our customers around–you know, in terms of how to use our product to come back online, debug and everything, given the fix in that case was very, very manual – there was really no good way to automate it. But again, we see that every single day, that’s what we do.

Raimo Lenschow: Okay, perfect. Then maybe it was just me, but it did feel like you mentioned logs quite a bit on this earnings call. Do you see any change–like, your product is getting more mature and the innovation that is coming through is obviously very visible, but do you see a change in the market with recent movements in terms of vendors, that that kind of opens up a little bit more from your perspective? Thank you, and congrats from me as well.

Olivier Pomel: Yes, we definitely think there is going to be more opportunity in the future, which is why we’re investing heavily both in terms of making large [indiscernible] to scale, that’s Flex Logs in particular, and also going further in terms of the sophistication of the functionality we can offer to customers so they can build very complex processes around those. We talked about log workspace also in the call, log workspace is particularly interesting for customers who have used other platforms and have built pipelines basically that must process a lot of logs data, and so we build that for them and that’s been very well received so far. All of that is in service of going after these opportunities.

Raimo Lenschow: Perfect, thank you.

Operator: Thank you, and one moment for our next question. Our next question is going to come from the line of Mark Murphy with JP Morgan. Your line is open, please go ahead.

Mark Murphy: Thank you so much, and I’ll add my congrats. Olivier, it’s great to see the announcement of LLM Observability reaching GA. I think we’re all looking at this tremendous wave of hyperscaler commitments that are going to be ramping in the second half of this year, and it’s all for training of these next-gen AI models. Since you’re more exposed to the–excuse me, since you’re less exposed to that training and you’re more driven by the inferencing, I’m wondering if you can just help us understand how the spending pattern or activity changes as the AI models go live and reach the inferencing stage. I’m basically looking for any way to assess how much spending is ultimately going to develop into the inferencing, where you have an opportunity.

Olivier Pomel: Yes, look – as you know, it’s still early. We do see customers that are moving increasingly into production, and we have a few of those. We named a couple as early customers of LLM Observability – I think the two we named were WHOOP, the fitness band, and AppFolio. We see many more that are lining up and that are going to do that, but in the grand scheme of things, looking at the whole market, it’s still very early. I would say the best proxy you can get from the future demand there is the growth of the model providers and the AI natives, because they tend to be the ones that currently are being used to provide AI functionality into other applications, and largely in production environments, and so what we said there, the harbinger of what’s to come.

Mark Murphy: Okay, and then as a quick follow-up, maybe for David, a couple of the consumption model software companies had recently commented that in June and July, they were seeing more cloud cost control or optimization, specifically among the digital natives, and so your results are solid. I don’t think you mentioned that, but could you just comment on how the optimization activity is trending now between the digital natives and the enterprises heading into the back half?

David Obstler: Yes, as you know, we’ve said that–so when you look at the time series, the peak of the optimization was in Q2, Q3 last year, and we’ve had a time series of higher usage growth for our clients month to month since then, and that’s continued through the first half of the year and into July. The usage growth, as we talked about, is stronger in the enterprise and in the larger users, but it has been fairly stable in the SMB, so we’re seeing some more–when you look at the chart and the line, enterprise usage growth being higher than it had been and SMB being stable.

Olivier Pomel: For us, I will add that the digital natives are largely SMB and midmarket, they’re not enterprise. Even when you look at the digital natives, there is two stories depending on whether you talk about the AI natives or the others. The AI natives are inflecting in a way that the others are not at this point, so today we see the higher growth on AI natives from traditional enterprises and stable growth but not accelerating from the rest of the pack.

Mark Murphy: Thank you very much.

Operator: Thank you. One moment for our next question. Our next question is going to come from the line of Kash Rangan with Goldman Sachs. Your line is open, please go ahead.

Kash Rangan: Hello, thank you very much. Oli, you’ve mentioned I think between–on the call, there’s been repeated instance of enterprise growing faster than SMB. I’m curious why is that the case, and is this something of a change in the trend? Have you seen SMBs actually showing better usage trends in the past, and what could cause the SMBs to start to pick up consumption? What are the things that are holding back their consumption, and what could be the unlocks from [indiscernible], because the enterprise is doing well, so obviously the product portfolio is being well received, so what’s stopping the SMBs? Thank you so much once again.

Olivier Pomel: Yes, I don’t know that there is that much of a trend just yet to look at, or there is too much to say at this point. This is just the way the numbers came up over the past quarter or so. I would say, look, there’s many reasons why the SMBs could be more careful in terms of the macro environment, the fact that they have maybe less runway, immediate runway with consolidation and things like that compared to large enterprises, and some of them may be are further along also in that log journey, so the growth there is more tied to their overall growth, as opposed to they’re still transitioning to a next-gen and cloud environment. These are all potential factors. But look, there is no–at this point, I wouldn’t call it a major, super-important difference. I think we’ll have to see what this looks like in a few quarters.

Kash Rangan: Got it, and one for David, if I could. How strong is the delta between enterprise consumption growth versus SMB? Are we talking orders of magnitude or meaningful percentage, or a big percentage?

Olivier Pomel: No, no. We’re just [indiscernible] a few points, but different trends. That’s it.

David Obstler: Yes, we’re just basically commenting on the line–you know, as we said, they have been around each others, and we’re really commenting more on, as Oli mentioned, enterprise, things like they may have been more careful in the increase of spending. Consolidation continues to be a factor in going to a common platform, but as Oli mentioned, these are sort of comments on the way things are evolving, but we still have pretty similar metrics in all the different segments.

Olivier Pomel: It’s something that we noted because we–you know, it’s a little bit counterintuitive in that when you look at the overall market, the enterprise is where we have the most mature competition, the most scaled competition, and we are doing better. That part is scaling faster than, I would call it, the less competitive side of the market. But again, not too much to read into it just yet, we’re just informing you of the trend.

Kash Rangan: Thank you so much.

Operator: Thank you, and one moment as we move onto our next question. Our next question is going to come from the line of Kirk Materne with Evercore ISI. Your line is open, please go ahead.

Kirk Materne: Yes, thanks very much, and I’ll add my congrats on the quarter. Olivier, I was wondering if you could just talk a little bit more about the LLM Observability product that Mark referenced. When people are thinking about bringing on LLMs into their organization, do they want the observability product in place already, or are they testing out LLMs and then bringing you on after the fact? I’m just wondering, it’s sort of a chicken and egg question, I’m wondering if you’re someone they want to talk to before they start moving things into production, or it’s after they get something going, they bring you in after the fact?

Olivier Pomel: I think the first thing I’d say, we expect this market to change a lot over time because it is far from being mature, and so a lot of things that might happen today in a certain way might happen in two years in a very, very different form. That being said, the way it works typically is customers build applications user developer tools, and there’s a whole industry that has emerged around developer tools and playgrounds and things like that for LMs, and so they use not one but 100 different things to do that, which is fairly similar to what you might find on the IDE side or coded [indiscernible] side for the more traditional development. There’s lots of different–it’s a very fragmented environment on that side.

When they start connecting the LLMs to the rest of the application, then they start to need visibility that includes the other components, because the LLM doesn’t work in a vacuum, it’s plugged into a front end, it works with authentication and security, it works with–connects to other systems and databases and other services to get the data, and at that point, they need to be integrated with the rest of the observability. For the customers that use the LLM Observability product, they use us for all the rest of their stacks, and it would make absolutely no sense for them to operate their LLMs in isolation completely separately and not have the visibility across all applications, so at that point it’s a no-brainer that they need everything to be integrated in production.

Kirk Materne: That’s helpful. Then David, we can kind of infer your implied [indiscernible] 4Q. I was just wondering, some of the elections in Europe have come up on a couple other calls in terms of [indiscernible] that have been distractions. I was just wondering if you had any thoughts on how you think the U.S. election might impact usage, if at all, or if you have any thoughts on that. I realize you guys were a lot smaller last time we had a presidential election.

David Obstler: No, we are not forecasters like that. As you know, usage growth has many factors. The effect of the election on the operation of modern cloud applications is not something that has been a very significant change in usage patterns, for instance, in the European elections, and we wouldn’t anticipate any here as well.

Olivier Pomel: No impact. The only impact on us of the U.S. election is we’re trying not to schedule our earnings call on the same day.

Kirk Materne: We would appreciate that! Thank you. Thanks guys.

David Obstler: Thank you.

Operator: Thank you. One moment as we move onto our next question. Our next question comes from the line of Fatima Boolani with Citi. Your line is open, please go ahead.

Fatima Boolani: Good morning. Thank you for taking my question. Oli, I wanted to start with you. You and David both talked about improving usage trends, but I wanted to take a step back and ask you, have you seen the quality of the usage improve by virtue or by extension of your introduction of the cloud cost management SKUs – you talked about the Kubernetes with the Autoscaling, and then the original cloud cost management SKU. I’m wondering if it’s maybe a spurious correlation now that customers have that much more visibility into the mechanics of what they’re spending with you, they’re actually more inclined to drive usage because it’s higher fidelity. Just any commentary on that would be helpful, and then I have a follow-up for David, please.

Olivier Pomel: Yes, I mean, look – in general, customers have invested a lot in understanding their spend, whether that’s on us or on their cloud providers, and as a result, we can say that there’s less, call it overhang of things customers are spending they don’t understand, which is always bad in the long term, so I think customers understand much better the value of what they’re getting in the cloud in general this year than they did two years ago, before this whole optimization movement started. They want more in terms of visibility into what they spend, what actually creates value for them and where they can optimize in the future, so that’s definitely a virtuous cycle that we embark on with our customers in terms of building the right products for that.

Fatima Boolani: I appreciate that. David, as you all kind of roll out more, what I would call resource-intensive or compute-intensive SKUs, like logs, Flex Logs, logs workspaces, I’m wondering if you can shed a little bit of light on some of the gross margin characteristics differ by product pillar. I’m just looking at some of the sequential compression in gross margin, so just wanted to get a better understanding of what are some of the more resource-intensive products that you’re anticipating scaling, that could keep a lid on gross margins in the next couple of quarters. Thank you.

David Obstler: Yes, I’ll just go into the numbers first, and then Oli on the engineering side of it. But essentially what we’ve said consistently is that gross margins have operated in a range, they’ve operated towards the top of the range, but there will be variability quarter to quarter as we launch functionality, often having to do with growing out functionality and then optimizing it, and so the movements, the slight movements that we’ve seen quarter to quarter have been the result of that. I’ll turn it over to Oli for more on the engineering.

Olivier Pomel: Yes, there’s definitely nothing to read into the small movements in the gross margins from the product mix perspective. A lot of what happens is we build new features, maybe some of these new features will have more computing impact, more storage impact or something else, maybe also they won’t be fantastically optimized on day one from a code efficiency perspective, or maybe sometimes we’ll focus more on building more things as opposed to optimizing them, because these are the same people, same resources that work on both. What you should expect to see is some ebbs and flows on that number as we keep shooting new features and we keep optimizing. In general, we feel good about the gross margins. We’re not constrained in terms of what we can build by the margin profile we have, and also should we need them, we have many levers to improve these margins as well, so I wouldn’t read too much into the small changes, and we’d expect some more of those small changes in the future.

[Indiscernible] we feel good about that.

Fatima Boolani: Thank you so much.

Operator: Thank you, and one moment for our next question. Our next question is going to come from the line of Matt Hedberg with RBC. Your line is open, please go ahead.

Matt Hedberg: Great, thanks guys. Oli, in your prepared remarks, you talked a lot about security and noted data security as a new growth engine from a product perspective. I’m curious, can you talk about how customers might leverage that offering versus maybe other traditional data security offerings in maybe, like, DLP for instance?

Olivier Pomel: Yes, it’s interesting because the–in many ways, we’ve been doing data security for a while now. On top of our logging product, we started building essentially data scanning which was very successful with customers. We expanded that to cover data flows inside APM traces, that flows between the front end and the back end and really the monitoring. We basically heard our customers ask for more – basically they wanted to not just do data in transit but also see where data was exposed [indiscernible], and so that’s what we extended to the rest of data security. You can see customers coming to that from two different sides on our end. One is customers adopting our security suite, and data security is little by little becoming part of [indiscernible] security in general.

But we also see customers coming to it from the log and ATM side, basically, where they start from the applications and they want to track where the data is, so it serves both sides, basically, and it plays to the strategy we have integrating both observability and security into one platform.

Matt Hedberg: Got it, super helpful. Then as we get into 3Q and the U.S. Fed spending quarter, what are your thoughts on federal spending just in general might play out in Q3 relative to your assumptions?

Olivier Pomel: Well, we are building out the capacity for it, so. We have build-up to do on several sides. We have the go-to-market capacity to build, we also are still pursuing more government certifications and government-specific deployments to open up some more of the market there, but that’s definitely [indiscernible] investment for us.

Matt Hedberg: Got it. Thanks a lot, guys. Well done.

Operator: Thank you, and one moment for our next question. Our next question comes from the line of Jake Roberge with William Blair. Your line is open, please go ahead.

Jake Roberge: Thanks for taking the questions. I just want to follow up on the enterprise strength that you saw in the quarter. Are you starting to see enterprises re-engage with their cloud migration efforts which is helping drive that growth, or is the strength more related to just general platform usage and expansion?

Olivier Pomel: They never stopped their enterprise migrations. I think maybe some of the usage was not growing as quickly for some time, maybe some short term optimization efforts were ongoing, but the direction was always the same. Also, they never stopped growing with us in the cloud, so we definitely saw that throughout the past couple of years. Some of the strength we see today has to do with the fact that to serve their–the emergence of AI has reaffirmed for them the need to go to the cloud sooner rather than later so they can build the right kind of applications, they have the right kind of data available to build these applications. But also, we have more to offer, like we have–we can do more–consolidate more of what they were using before, and that gives us more avenues to grow these customers in the short term.

David Obstler: I think we’ve said over the quarters that one enterprise is very early in their journey, and there is a lot of white space too that we said a couple quarters ago, the enterprises had started to resume more normal activity and deploying of the modern cloud applications, and as Oli mentioned, there’s opportunities also for consolidation in the cloud platform, that we’ve talked about many times.

Olivier Pomel: I’d point you to the numbers we shared, I think two quarters ago in terms of our enterprise penetration and the average size of our contracts with enterprises, which are still fairly small. There’s a lot of runway there, and the growth–although the count is not predicated on the growth of the enterprises themselves, they’re still early in their transformation.

Jake Roberge: Okay, very helpful. Then you’ve talked a decent amount about the demand you’re seeing from AI native customers, but how are you thinking about driving growth with your own AI solutions, like Bits AI and LLM Observability, and when do you think those start to layer more meaningfully into the model? Thanks.

Olivier Pomel: Yes, I mean right now, the first area of direct application of Bits AI is in incident management and incident resolution, so that is tied more to the SKUs we’re selling there in terms of incident management. But this area is not the only ingredient of that product. Part of it is what we had already in terms of the mechanics of incident management, part of it is also the new Encore product we announced, and part of it is going to be the [indiscernible] and we’re integrating all that to have a fantastic end-to-end experience for our customers that almost makes them want to have incidents–no, actually they still don’t want to have incidents, but the point here is it should really help them.

Operator: Thank you, and we’ll move onto our next question. Our next question comes from the line of Koji Ikeda with BofA. Your line is open, please go ahead.

Koji Ikeda: Yes, great. Thanks guys. Thanks for taking the questions. Just one from me. I wanted to ask on the usage growth trends. In the prepared remarks, you said a lot about trends exiting this quarter versus 2Q of last quarter, and the first half of this year being better than the first half of last year. But the question here is, how did Q2 this year compare to Q1 this year? Thank you.

David Obstler: Yes, so we had normal seasonality related to the number of days in the quarter and customer behavior in–as they launch new applications, so we saw–we really look at it because of the seasonality over quarters, so the usage growth exhibited the same patterns improvement over last year’s similar period, looking at the days, as it did in the first quarter.

Koji Ikeda: Got it, David. One quick follow-up, if I may here. The follow-up would be, I know in the Q, you give a net new revenue growth split between existing and new. I was wondering if we could get that mix now, or maybe at least some color in that mix – last quarter was 70% coming from net new from existing. Was it higher or lower this quarter from that 70% mark?

David Obstler: It’s going to be 75/25 – 25 from new, 75 which would be–what we said all along is that as net retention recovers and usage growth is higher than the previous comparable period, as you go back through our history, you will see that the amount from existing customers relative to new logos has generally increased.

Koji Ikeda: Great, thank you very much.

Operator: Thank you, and one moment for our next question. Our next question is going to come from the line of Yi Fu Lee with Cantor Fitzgerald. Your line is open, please go ahead.

Yi Fu Lee: Thank you so much for taking my question, and congrats on the quarter. In terms of the new products that were launched at DASH, a lot of stuff going on in LLM, AI apps, etc. Olivier and David, which one are you most bullish near term, and then longer term?

Olivier Pomel: Well you know, it’s always hard to have a favorite child in all of the amazing things that we’re shipping. Look, I think the short term, the ones that are going to have the most impact are the ones that relate to the products that already have scale, so anything we do that facilitates the deployment of [indiscernible] at scale has a large impact. Everything we do that makes–that changes the economics of logs or opens up new markets within our legacy logging area user base has a huge impact. What we’re doing with OpenTelemetry has a large impact because it’s a big trend in the industry, and we’re making bold moves there. Longer term, look – we think there’s a very large opportunity for us to do a lot of automation we have with our customers, and you see that, whether that’s on the observability side or the security side, with all the diverse ways in which we are taking action into the product, we are fixing things for customers, we’re driving them to take the next step.

We are organizing the tracking of the workflows that they’re running from end to end, so this is a longer build, but I think in the long run it makes a very large difference in terms of value we can provide to our customers.

Yi Fu Lee: Excellent, Oli. Just a quick follow-up for David – NRR is at the mid 110 level. What needs to happen in order for Datadog to go back to above the 120 level? I mean, it sounds like the trends are very, very healthy month to month, quarter over quarter, so just some commentary around [indiscernible] for me, thank you.

David Obstler: Yes, we don’t give that forecast. The components are the use of existing products and the cross-sell, and so as you mentioned both of those have been stronger in the first half of this year than they were last year, and we’ll see what happens, but we don’t give guidance or forecast on net retention. Thanks.

Yi Fu Lee: Thank you very much.

Operator: Thank you, and one moment for our next question. Our next question comes from the line of Patrick Colville from Scotiabank. Your line is open, please go ahead.

Patrick Colville: All right, terrific. Thank you so much for having me on. [Indiscernible], David, one of the themes you’ve talked about in the past is competitive dynamics in observability. There have been a lot of corporate transactions in the space over the past year, so I guess how are you seeing competition versus your open source peers, platform peers, peers that are private versus a couple quarters ago?

Olivier Pomel: In general, the competition is very much unchanged. There’s nothing super specific to say about that. I think we have some of the scale players that have been disappearing to a certain extent as a result of the transactions you mentioned, but we expect that to play out more in the midterm than in the very short term in the marketplace. We do have scale competition still in terms of product companies that are competing with us on observability, and there’s no change in the posture there. We like the way we’re performing, and a number of the large deals we’ve mentioned, we were displacement or wins against some of these folks – we feel very good about that. Then on the low end, there’s been pretty much a rotating cast of sub-scale companies that are going after that market, and that will also unchanged in the [indiscernible] pretty much, so nothing to report there.

I think largely when we build products, we build it with customers, we don’t build it with competition in mind, the few exceptions being when we see large [indiscernible] opportunities in the market because of big changes and big transactions that you mentioned already.

Patrick Colville: Okay, very helpful. I guess David, looking at the 3Q revenue guidance, it looks like the kind of buoyant trend you saw this quarter will continue. Can you just put a fine pin, if possible, on the trend we saw through July and thus far in August?

David Obstler: Yes, I think what we’ve seen since the quarter, as we mentioned, is a continuation of better usage trends relative to the comparable period last year, so more of the same. In our guidance philosophy, it hasn’t changed – we take those trends, as much information as we have, and apply discount and conservatism, given that we don’t control the consumption of our clients, we observe it. It’s a very similar methodology to what we’ve used in previous quarters and a continuation of the trends we’ve seen in the first half of the year.

Patrick Colville: Terrific, thank you so much.

Operator: Thank you, and one moment for our next question. Our next question comes from the line of Taz Koujalgi with Wedbush Securities. Your line is open.

Taz Koujalgi: Hey guys, thanks for taking my question. I have a question for David on your sequential revenue growth this quarter. I’m trying to reconcile the comments you made about the usage growth in this quarter being better than last year, because if you look at the revenue growth sequentially, that’s slowed down. I think it’s the lowest Q2 sequential growth in the longest time. One more question was, if you look at the sequential growth for the last three, four quarters, it’s really accelerating since your optimization trends, and that trend kind of, I guess, it buckled this quarter because the Q-over-Q growth in Q2 was lower than what you had last year, so just trying to reconcile the commentary about usage growth being strong but then the revenue growth sequentially looks a little bit lighter than last year.

David Obstler: Yes, a lot of that has to do with what we said, which is that in the second half of December, clients are not at their desks and new deployments have been frozen, so we generally find that the usage or revenue run rate growth goes down or is the same, and then we find a recovery as people get back to their desks in Q1. Then we find in Q2, a similar linearity pattern that we see in all Q2s, which is how it’s sort of people work, and so we didn’t see anything out of the ordinary in terms of the time series of Q4 to Q1 to Q2.

Taz Koujalgi: Got it, and just one follow-up – David, you mentioned that revenue is the best metric for your business, we shouldn’t be looking at billings and RPO bookings. But I’m just wondering, any color your can provide on the first half bookings growth this year? It’s been flat year-over-year but you’re recent increasing it. That’s, I think, the lowest bookings growth again in any first half of your year. Any more commentary beyond what you already provided? Is the renewal base lighter in the first half? Should we expect an acceleration in the second half? Any more color on the bookings momentum?

David Obstler: No. If you look at the latest 12 months of all these trends, they all eventually converge around revenues. It has to do with, as we’ve mentioned in every earnings call, when bills go out, whether the deals are multi-year or single-year, etc., so no, all of that essentially balances out back to the metrics that we direct you to, which is revenue and then ARR, so no, nothing in it.

Taz Koujalgi: Thank you.

Operator: Thank you, and I would now like to hand the conference back over to Olivier Pomel for any further remarks.

Olivier Pomel : Thank you, and just to close the call, I want to thank again everybody who was involved in DASH this year, so that means obviously the product engineering teams who shift these amazing products, and there were lots of them. It means the go-to-market teams that have relayed the message to our customers. That means the marketing and community teams that did such a fantastic job putting on the show, and of course that means the customers who showed up in large numbers with enthusiasm, and who have been the life of the conference. Thank you everyone, and we’ll see you next quarter.

Operator: This concludes today’s conference call. Thank you for participating. You may now disconnect. Everyone have a great day.