Datadog, Inc.

and thank you for standing by welcome to the second quarter 2024 data dog earnings conference call at this time all participants are in a listen-only mode after the speaker's presentation there will be a question and answer session to ask a question during this session you will need a press star 1 1 on your telephone you will then hear an automated message advising you your hand is raised to withdraw your question please press star 1 1 again please be advised that today's conference is being recorded I would now like to hand the conference over to your speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead.

Thank you, Michelle. Good morning, and thank you for joining us to review Datadog's second quarter 2024 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pommel, 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 31st, 2024. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended June 30th, 2024 and other filings with the SEC. This information is also available on the investor relations section of our website along with a replay of this call. We will also discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com. With that, I'd like to turn the call over to Olivier.

Thanks, Yuka, and thank you all for joining us this morning. We had a very productive second quarter. First, we welcomed thousands of Datadog users to our Dash conference in June. where we announced a broad range of exciting new products and new features for customers to observe, secure, and act in their cloud environment. And we continue to add new customers and help existing ones as they grow in the cloud. Let me start with a review of our Q2 financial performance. Revenue was $645 million, an increase of 27% year-over-year and above the high end of Organus 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. 49% of customers were using four or more products up from 45% a year ago. 25% 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. This includes our efforts in digital experience monitoring, an area of observability which includes synthetics and real-world 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 product analytics at Dash, we are excited to go further and allow our customers to consolidate more of their usage and business insights into Datadog. Now, let's discuss this quarter's business drivers. Overall, the business environment for Datadog was roughly unchanged from last quarter. Our customers overall are growing their cloud usage, while some are continuing to be cost-conscious. In Q2, we saw existing customer usage growth that was broadly in line with our expectations and consistent with the overall improved trend that we 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 lines, with newer products growing faster from a smaller base. Finally, churn continues to be low, and gross revenue retention was stable in the mid to high 90s, highlighting the mission-critical nature of our platform for our customers. Moving on to R&D. We had our Dash user conference in late June, and we are excited to announce many new products and features for our users. There's too much for us to cover in detail, But let me review just some of the announcements we made in the past three months. In the next-gen AI space, we announced the general availability of LLM observability, which allows application developers and machine learning engineers to efficiently monitor, troubleshoot, and secure LLM applications. With LLM observability, companies can accelerate the deployment of AI applications into production environments and reliably operate and scale them. We also expanded Bits.ai with new capabilities. As a reminder, Bits.ai is a Datadog built-in AI copilot. In addition to being able to summarize incidents and answer questions, we previewed at Dash the ability for Bits.ai to operate as an agent and perform autonomous investigations. With this capability, Bits.ai proactively surfaces key information and performs complex tasks, such as investigating alerts and coordinating incident response. Taking a step back and looking at our customer base, we continue to see a lot of excitement around AI technologies. Our customers are telling us that they are leveling up on AI and ramping up experimentations with the goal of delivering additional business value with AI. And we can see them doing this. Today, about 2,500 customers use one or more of our AI integrations to get visibility into their increasing use of AI. We also continue to grow our business with AI native customers which increased to over 4% of our ARR in June. We see this as a sign of the continuing expansion of this ecosystem and of the value of using Datadog to monitor the production environment. I will note that over time, we think this metric will become less relevant as AI usage in production broadens beyond this group of customers. Last but not least, we announced TOTO, our first foundational model for time series forecasting. which delivered state-of-the-art performance on all 11 benchmarks. In addition to the technical innovations devised by our research team, TOTO derives its record performance from the quality of our training dataset and points to our unique ability to train, build, and incorporate AI models into our platform that will meaningfully improve operations for our customers. Moving on from AI, we have a lot more to show in observability. we announced the general availability of FlexLogs, which extends our logging without limits approach and allows our customers to scale storage and compute separately for cost efficiency. And our customers can today use our new Log Workspace for log analysis. Log Workspace is an advanced analytics feature that allows users to connect data sets, build and visualize complex queries, and create reusable composable views and reports. It is particularly relevant to customers who previously built sophisticated analysis and workflows in legacy log management tools. We announced the general availability of data jobs monitoring, which allows data engineers to detect and fix issues with their Spark and Databricks workloads and to optimize the cost and performance of their data jobs. Moving and transforming large amounts of data has grown in importance and become a mission-critical capability for many businesses a trend that we believe will continue with the adoption of AI. With this, our data observability set of products is expanding. Data jobs monitoring works alongside our data streams monitoring product, which helps customers understand their queuing pipelines involving components such as Kafka or RabbitMQ. And we're increasingly providing visibility for data lakes and data warehouses such as Snowflake to deliver end-to-end data observability across customers' data resources. Moving on from data observability, we introduced Kubernetes Auto Scaling to allow customers to optimize for cost and performance by automatically rightsizing Kubernetes resources. For our customers using OpenTelemetry, the Datadog agent will embed a fully configurable OpenTelemetry collector, giving hotel 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. And shifting left, Our new live debugger enables developers to step through code directly in production environments and find the exact root cause of production errors. As I mentioned earlier, we are building up on our success in digital experience monitoring, and we announced product analytics, providing in-depth product and user insights for product managers and business owners. In the cloud security space, we launched a new application security capability called Code Security. which allows our customers to detect and prioritize code-level vulnerability in their production applications. We also announced data security, which allows our customers to automatically pinpoint sensitive data, starting in AWS today and expanding to other environments in the future. And 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 serverless functions. without requiring agents to be installed. Finally, in the cloud service management space, we're going further to allow our customers to take action directly within the Datadog 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 incident management workflows fully integrated with observability. So 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 into 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 FlexLogs. 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 loading 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 the 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 use in their on-premise environment. They have now adopted a total of 17 Datadog products. Next, we signed a seven-figure annualized expansion with a large American insurance company. This customer had been using Datadog for full-stack observability at one business unit. With this expansion, they have chosen Datadog as their enterprise-wide observability provider. In comparing us to the performance of other tools, this customer measured stronger developer adoption and fewer incidents with Datadog. And in displacing its legacy APM and log management, they expect to save over $1 million annually on tool costs alone. Finally, we signed a high seven-figure annualized expansion with a leading online gambling and entertainment platform. This longtime customer uses Datadog as its strategic observability partner, enabling full visibility across infrastructure, applications, logs, networks, and their public front end. with users spanning from hands-on keyboard engineers all the way to their C-level executives. This renewal supports this customer's expansion into new use cases, to have security embedded into the operations by using all of our cloud security products, to build a culture of cost accountability with cloud cost management, and to take action by using incident management and workflow automation. And this customer, to date, has adopted 19 products in the data platform. And that's it for another productive quarter from our go-to-market teams. Now, let me say a few words on our longer-term outlook. Overall, we continue to see no change to the multi-year trend towards digital transformation and cloud migration. We are seeing continued experimentation with new technologies, including next-gen AI, And we believe this is just one of the many factors that will drive greater use of the cloud and next-gen infrastructure. As indicated by our many announcements at our DAG 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. And David Galleries 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 Sigma, Wells Fargo, or Walmart. He will help us drive the next chapter of growth and scale at Datadog. With that, I will turn it over to our CFO, David.