Thank you for joining us, and welcome to the DigitalOcean First Quarter 2024 Earnings Conference Call. I would now like to hand the call over to Rob Bradley, Vice President of Investor Relations. Please proceed.

Thank you, Rochelle, and good morning. Thank you all for joining us to review DigitalOcean's First Quarter 2024 financial results. Joining me today are Padmanabhan Srinivasan, our Chief Executive Officer; and Matt Steinfort, our Chief Financial Officer. After our prepared remarks, we will open the call up to a question-and-answer session. Before we begin, let me remind you that certain statements made on the call today may be considered forward-looking statements, which reflect management's best judgment based on currently available information. I refer specifically to the discussion of our expectations and beliefs regarding our financial outlook for the second quarter and full year of 2024. Our actual results may differ materially from those projected in these forward-looking statements. I direct your attention to the risk factors contained in the company's 10-Q filed with the Securities and Exchange Commission and those referenced in today's press release that is posted on our website. DigitalOcean expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements made today. Additionally, non-GAAP financial measures will be discussed on this conference call and reconciliations to the most directly comparable GAAP financial measures are also available in today's press release as well as in our updated investor presentation that outlines the financial discussion on today's call. A webcast of today's call is also available on our website in the IR section. With that, I'd like to turn the call over to our CEO, Padmanabhan Srinivasan. Patty?

Thank you, Rob. Good morning, everyone, and thank you for joining us today as we review our first quarter results. After my first 3 months in the role, I'm pleased with both the solid execution and durable growth we delivered in Q1 and the early progress we are making to position the company to take advantage of the material growth opportunities that are in front of us. In my remarks today, I will briefly highlight our first quarter results, share some initial observations from my first 90 days, provide several examples of our increasing product velocity, and discuss our progress pursuing the tremendous AI growth opportunity. Before I get too deep into my remarks, I want to highlight our Q1 performance, which was solid across the board. Revenue growth accelerated quarter-over-quarter, and we continue to deliver strong adjusted EBITDA and free cash flow margins, while increasing investments in our higher-growth businesses, demonstrating the strength of our business model. We are also encouraged by the improving growth fundamentals. Net dollar retention continued to slowly rise from our low last summer, increasing as expected to 97%. Our core product usage grew faster in Q1 than it did in Q4 of 2023. We're also seeing a strong uptake of our still early-stage AI and machine learning platforms. While we still have a lot of work ahead, our Q1 results are very encouraging. Matt will walk you through more of the details later in this call. I will start my deeper commentary with some initial observations after my first quarter as CEO. I've spent a meaningful portion of my first 90 days with customers, partners, and employees. The feedback and insights I have received have only increased the excitement and optimism I have for DigitalOcean and our growth potential. More than anything, I've been thrilled with the positive and constructive feedback that I've gotten from our customers. We have an incredibly loyal customer base that relies on DigitalOcean to run their businesses, that want to do more with us as they grow, and they also have very clear feedback on how we can help them accelerate. Most of the builders and scalers on our platform run revenue-generating software products on DigitalOcean and have come to know and love us for our simplicity, our valuable technical content, and our compelling price to value. I've been actively engaging and listening to them, and they have helped validate some of the hypotheses that I have long held about DigitalOcean. Number one, that the market opportunity for cloud platforms is large and growing and is only increasing with the advances of AI and machine learning technologies. Our customers are optimistic about their own long-term growth prospects and are telling us that they see opportunities to expand their business with DigitalOcean. Our platform matches what growing technology businesses require as a scalable and performing platform, a platform which is simple to get started on and scales with them, a platform that is cost-effective and more importantly, provides transparency of ROI with robust technical support, both directly from us and also from our passionate community of developers. My conversations with dozens of customers offered key insights into the gaps in our platform and highlighted the emerging needs of our core target customer. This reinforces our mission, and we are going to continue to focus on product innovation and ensuring we delight our customers and the developer ecosystem. Their endorsement of DigitalOcean is powerful, and we will work tirelessly to earn and retain their business while attracting net new customers. With this backdrop, let me give you an update on what we've been working on recently. Over the past few weeks, we have made demonstrable progress accelerating our product innovation and the velocity of our new releases. Let me share a few highlights with you. First, we recently introduced turnkey data protection for our customers by launching daily droplet backups in true distillation fashion to make it super simple for developers. This capability enables one-click droplet data protection, providing peace of mind from accidental deletion through automatic retention of the 7 most recent copies. In parallel, we also improved the speed of our snapshot capability by up to 6x, enabling customers to back up even larger droplets much faster than before. While it is still early days, we are seeing robust adoption from both existing and new customers, enabling daily backups. We have already seen more than 1,300 new customers enabling daily backups and a 150% month-over-month increase in overall droplets being backed up daily, just between March and April of this year. We also rolled out new additions to our premium droplet offerings, expanding these premium options to memory and storage-optimized families with high-performance, non-volatile memory express SSDs and 5x increased networking throughput over regular droplets, alongside our flexible egress bandwidth allowance. These new memory and storage-optimized droplets are ideal for memory-, data-, network-, and bandwidth-intensive workloads. We are very excited for the potential they will offer to new and existing customers across a variety of use cases like caching, databases, and many others as they get ramped up. Also in Q1, we introduced horizontal scaling for Managed Kafka, continuing our focus on making the complex simple for our customers. Horizontal scaling for Kafka is particularly critical for our customers who manage large volumes of streaming data and want to prioritize scaling bandwidth and highly performing end-user experiences. This facilitates the right provisioning of nodes in support of fluctuating workload requirements, enabling customers to handle spike data volumes and traffic, improve the reliability of their clusters, and optimize their resources. A few other notable releases we are excited to highlight since our last call include a series of app platform improvements such as CPU-based autoscaling and dedicated egress IT support from our platform. Turning to our managed hosting cloud-based offering. In January, we were proud to launch cloud-based autonomous. With a few months in the market now, the initial feedback from customers and community has been very positive with over 650 customers adopting the new capability to date. Alongside autonomous, we shipped a number of other crucial items to simplify and secure our managed hosting offering for our customers. These include DNS made easy to simplify DNS management for users, and integration with PacStack to provide an extra layer of vulnerability detection and alerting, and most recently in April, client billing, the first 2 launched for our plant agency suite that will automate and streamline various agency workflows to enable simpler, more efficient, and more agile operational support to help our agency customers grow on the DigitalOcean platform. More to come on this throughout the rest of this year. These examples are just a few highlights from the list of capabilities we continue to add in our mission to simplify the cloud for our customers. We will continue to listen closely to our customers and strive to accelerate our delivery velocity to ensure our customers are positioned for success as they grow on our platform. We know that when our customers win, we all win, and our focus remains squarely on delivering a rapid cadence of new releases aimed at delighting our customers, enabling them to scale their businesses, and ultimately increasing our net dollar retention. Before turning it over to Matt, I would like to share some updates on what we are seeing across the AI landscape. It is an exciting time in AI, and you can see that every day in the headlines that you read. Companies across virtually every vertical that you can imagine are eager to incorporate AI into their value proposition. While large language models or LLM get most of the headlines, we are learning that our target customers, many of which are software vendors, are looking to consume a variety of different AI models into their offerings like fraud detection, sentiment analysis, natural language processing, live translation, demand forecasting, and of course, LLM-based models like image and video generation, coding assistance, Q&A box, and many more. We are seeing strong revenue growth for our early-stage AI solutions as we continue to ramp up our initial GPU capacity through the first part of this year, and our expectations are that demand will continue to outstrip supply for the foreseeable future. As of March, our ARR grew to $19 million, most of which is our Platform as a Service offering, representing a 128% annualized increase from December 2023, driven by demand for both AI model training and consumption of models, also known as inferencing. In addition to our existing AI platform as a service that helps AI and machine learning developers consume a variety of open-source models, we also launched our GPU-based Infrastructure as a Service offering in January of 2024 and are seeing strong traction with GPU hours sold and consumed, increasing 67% just from March to April of this year. The growing customer base for our AI Infrastructure as a Service offering are both venture-backed start-ups as well as established businesses. Over the last 4 weeks, we have onboarded several customers that came to us for our availability, simplicity, and support. Customers are using our AI platform as a Service and Infrastructure as a Service platform for a variety of use cases, including text and video generation, AI coding copilots, recommendation algorithms, model hosting services, and many more. Let me give you a couple of concrete examples. First is a venture-backed customer that is a leading AI-driven storytelling platform that helps build marketing storyboards, visual manuals for complex products, and comics all from textual prompts. Another customer example is an AI assistant tool that developers leverage to code with greater speed, flexibility, and accuracy. These are just 2 new examples of customers that we have seen this year as the AI market continues to quickly grow and evolve. I've spent a significant portion of my time and attention in my first 90 days working directly with these customers to understand their needs deeply and translate that into our longer-term AI strategy. Our customer needs, while similar, are quite distinct from the needs of large enterprise customers using hyperscalers or large language model builders who use the raw infrastructure from GPU form providers. To put this in perspective, over a decade ago, DigitalOcean identified and delivered an innovative compute solution with a clear product-market fit that was not being effectively addressed by the larger cloud providers, creating an easy on-ramp for developers, start-ups, and entrepreneurs to learn, test, and scale their businesses by simplifying cloud computing. We see a similar opportunity emerging now to democratize access to AI and machine learning capabilities, not only by providing simple access to GPU capacity via infrastructure as a service but also by integrating AI and machine learning into the developer experience itself to transform how developers build and run their workloads on our platform. Like many cloud platform providers, we are simultaneously turning up incremental capacity to meet near-term demand while also rapidly learning and evolving our AI strategy. While we are certainly in the very early innings of this transformative growth opportunity, we continue to believe that software more than hardware will be DigitalOcean's long-term differentiator and competitive advantage, especially for our target customers. We are confident in the strategic direction we are taking and believe that AI will be a meaningful growth contributor in 2024 and in the years ahead. We will make the right choices on investment this year as we continue to see positive results. We will share more on our plans on this front over the course of this year. To close my comments, I'm pleased with our performance in the early months of 2024, and I'm optimistic about our near- and long-term growth potential. We have a very solid performance and growing core business. Our revenue growth accelerated quarter-over-quarter, DR improved and profitability and cash flow margins were all very healthy. We are accelerating our pace of innovation and delivering new capabilities in rapid cadence, which will help our customers grow on our platform, thereby increasing our net dollar retention. Our AIML solutions are resonating very strongly with our customers, and we are working to turn up incremental capacity over the balance of the year to keep up with robust demand. There's a lot of work to do to take full advantage of our opportunity, but we are moving in the right direction and continue to make steady, rapid, and respectable progress each quarter. I will now turn the call over to Matt to provide details on our financial results and on our outlook for Q2 and for the balance of the year. Matt?

Thanks, Patty. Good morning, everyone, and thanks for joining us today to review our first quarter results. Revenue growth continued to improve quarter-over-quarter. We are seeing positive signals from our key growth drivers, and we continue to deliver attractive adjusted EBITDA and free cash flow margins, while we increase investment in our AI platform to pursue this material growth opportunity. This morning, I will provide a deeper look into the first quarter results before providing our financial outlook for Q2 and for the full year. Revenue in the first quarter was $184.7 million, which was up 12% year-over-year and up sequentially from the fourth quarter of 2023. We had $19 million of annual recurring revenue or ARR in the quarter, which was the largest organic quarterly increase we generated since the second quarter of 2022 and was 82% higher than the incremental ARR we generated in Q1 2023. Contributing to this growth was steady incremental revenue from new customers, improving net dollar retention from our existing installed base, and healthy contributions from our managed hosting and AI platforms. Revenue from new customers in their first 12 months remained both steady and a key element of our solid growth foundation in Q1. As we discussed in February, improving our net dollar retention, or NDR, is a major focus area and a key driver for accelerating our overall growth rate as we move through this year. As anticipated, MBR improved to 97% in Q1 and has continued to steadily increase since we reached our low point in July of 2023. We continue to see steady and historically consistent levels of churn, and we are seeing modest month-over-month improvements in our net expansion, which is expansion net of contraction as our customers are slowly returning to growth. The work that we are doing on both accelerating our product roadmap and continuing to enhance our customer success motions should enable us to continue to increase our net dollar retention as we seek to remove it as a headwind and eventually return it to a tailwind of our overall growth. Our managed hosting product, Cloudways, another key growth driver, contributed revenue of $22 million in the first quarter and grew 34% year-over-year. While we will see a slower year-over-year growth rate from Cloudways as we lap the managed hosting price increase that we made in April of last year, we do anticipate managed hosting continuing to be one of our faster-growing platforms for the foreseeable future. As Patty described, we are still in the early innings with our AI and machine-learning solutions. But the rate of growth of both the leading indicators and our revenue on this new platform is already meaningful. Our AI and machine learning platform contributed $4 million in revenue in Q1, and we exited Q1 with an ARR of more than $19 million, a 128% annualized increase. This strong growth came despite our being capacity-constrained in the majority of the first quarter as we navigated supply chain challenges and turned up the first wave of servers that we had ordered in Q4 of 2023. We are consistently selling through our available capacity as it comes online, and we saw our hours sold on H 100s increased 67% in April, just over March in just a single month. We will continue to add the next waves of our planned incremental capacity over the balance of the year and anticipate that demand for our AI solutions will continue to be robust. Turning to the P&L. Gross margin was 61%, which was an increase from 56% in the first quarter of the prior year. The largest factors in this 500 basis point improvement were the success of our ongoing cost optimization efforts and our having grown into infrastructure investments from prior periods. As is the nature of our business, incremental investments in equipment, space, power, and networking caused modest step-function increases to the cost of goods that are then smoothed as we fill the capacity with incremental revenue. Given our planned AI investments, we anticipate that gross margin will moderate somewhat in the coming quarters. Adjusted EBITDA margin was 40% in the first quarter, in line with the prior quarter as we continue to diligently manage expenses. Our healthy profitability in our core platform continues to provide us the flexibility to make additional investments in R&D to accelerate our product roadmap and to invest in our higher-growth opportunities such as AI. Diluted net income per share was $0.15 and non-GAAP diluted net income per share was $0.43. GAAP and non-GAAP diluted earnings per share increased by $0.32 and $0.15, respectively, on a year-over-year basis. While we have been cash flow positive since 2021, it is notable that we are now posting positive net income quarters on a GAAP basis, which is a further indication of the profitability of our core DigitalOcean business. Adjusted free cash flow margin was $34 million or 19% of revenue, which was an improvement from 16% of revenue in Q1 of 2023. As we have said previously, free cash flow margin is a more meaningful metric on an annual or trailing 12-month basis, and quarterly free cash flow margin will vary given the timing of capital spend and other working capital impacts. Turning to our customer metrics. Average revenue per customer increased 8% year-over-year to $95.13. The number of builders and scalers on our platform, those that spend more than $50 per month was $158,000, an increase of 8% year-over-year. Their revenue growth year-over-year was 13%, ahead of our overall growth rate of 12%. The number of builders and scalers on our platform, which represent 87% of our revenue, increased by 1,300 during the quarter. The increase in our higher spend and higher growth customers is a result of our focus and concentration of our marketing, product development, and customer success investment on these builders and scalers. Along with the increase in our higher-value customers, we did see total customer count decline by 7,400 quarter-over-quarter. This change was due to a reduction of 8,700 of our lowest spending customers, our learners, with that reduction collectively representing only around $100,000 a month of recurring revenue as the average spend for those customers was less than $10. Our balance sheet remains very strong as we ended the quarter with $419 million of cash and cash equivalents. During the first quarter, we leveraged our material cash balance and free cash flow to repurchase 200,000 shares of common stock for $8 million as part of our ongoing share buyback. Looking forward and building on our steady growth in Q1, we expect Q2 revenue to be in the range of $188 million to $189 million, representing 11% year-over-year growth at the midpoint of our guidance range. For the second quarter, we expect adjusted EBITDA margins to be in the range of 37% to 38% and non-GAAP diluted earnings per share to be $0.38 to $0.40 based on approximately $102 million to $103 million and weighted average fully diluted shares outstanding. With improving MDR and the strong demand for our AI platform that we saw in Q1, we are increasing the bottom end of our full-year revenue guide by $5 million, projecting revenue to be in the range of $760 million to $775 million for the year, a $2.5 million increase in the midpoint of our guidance range and representing year-over-year growth of 10% to 12% for the branch. On the profitability side, we continue to drive operating leverage in our core DigitalOcean platform, enabling us to increase investment in our faster-growing managed hosting and AI and machine learning platforms while maintaining attractive overall margins. We continue to execute the plan we articulated in February and continue to project our adjusted EBITDA margin for the full year to be in the range of 36% to 38%. We also maintain our forecast range for full-year adjusted free cash flow margin at this point. As we continue to see positive signals from our AI solutions over the balance of this year, we will continuously assess whether to deploy additional capital to further accelerate our AI growth, which may result in reductions to our free cash flow margins to support that. We are also maintaining our non-GAAP diluted earnings per share guidance, which we expect to be in the range of $1.60 to $1.67. That concludes our prepared remarks, and we'll now open the call to Q&A.

Your first question comes from the line of Raimo Lenschow of Barclays.

Congrats from me for a great quarter. First question on AI. If you think about the speed or the evolution of AI adoption, there is like training, inference, sorry. And what are you seeing at the moment on the platform side? And how do you think that will kind of evolve for you? And then a number of questions on NRR. If you think about it, it's obviously a lagging indicator. How do you think the weaker periods coming out kind of impacting NRR going forward?

Okay. Great. Thank you for the question, Raimo. I'll start with the AIML question, and then I'll let Matt chime in with the NRR question. So from an AIML perspective, as I said, it is a very exciting traction, but I have to remind that we are in very early innings, not just at DigitalOcean but as a market as a whole. So I think for us, we are super focused on the needs of our customers. Our customers are a little different, as I described in my prepared remarks. A lot of our customers are tech businesses that build and run software applications on the DigitalOcean platform. They need a variety of different AI models, not just LLM, and they are mostly AI extenders. So if you take the example of LLM that a lot of people are familiar with these days, you can inject data and fine-tune and extend current AI models. So that's a lot of what our customers are looking to do, not just in LLM, but in other models as well. Typically, our customers are AI extenders and AI consumers. Our AI value proposition is twofold, as I explained. We have recently introduced the Infrastructure as a Service. The dominant use case right now is model building and model extension and fine-tuning and also model inferencing across different parts of our data center infrastructure. We also have a very robust platform-as-a-service offering with Gradient, the platform we acquired through Paperspace, which is also undergoing considerable enhancements as we speak. So this platform as a service has a much wider aperture in the sense that it deals with AI and machine learning throughout the life cycle of software development. So we have both that as well as the raw infrastructure as a service to fine-tune and build and train and infer these AI models. So as I said, we are very happy with the progress in Q1. We will be focused on serving our customer segment, primarily with our AI strategy, and we feel very confident that we are now starting to really understand the evolving needs of our customers and what they are actually looking for, both in model training and inferencing. And as I said, these are very early innings. A lot of attention is now on model building and fine-tuning and training. But the long-term use case is going to be super heavy on inferencing, and we have both those phases covered with our Platform as a Service and Infrastructure as a Service.

We are encouraged by the gradual increase in net dollar retention that we've experienced monthly since July of last year. Historically, churn hasn't posed a significant challenge for us during this time, nor in the previous year. The primary concern has been net expansion, which is the difference between expansion and contraction. We have observed consistent improvement in this area, contributing to the enhancement of net dollar retention. Contraction is improving slightly each month, while expansion was the last area to reach its lowest point last year and has remained steady in recent months. We see positive signs, but we anticipate slow and steady growth in net dollar retention, and we are pleased with the progress made. The product development efforts and enhanced focus on customer success will further support these improvements. We are focused solely on factors within our control, without relying on any macroeconomic improvements or market shifts to drive higher growth in our guidance.

Your next question comes from the line of Pinjalim Bora with JPMorgan.

Great. Congrats on the quarter. I wanted to ask you, Patty, the AI strength is definitely possible here. But I want to ask you if you are seeing attach rate of the core digital ocean offering as people create applications around the AI workloads. Is that flywheel AI driving more core DigitalOcean services starting to happen?

Good question, Pinjalim. Nice to hear from you. So the way I'm looking at it is that there are 2 ways that this cross-sell or this cross-attach happens. One, our traditional DigitalOcean core customers that are now starting to use our both Platform as a Service as well as our infrastructure to consume some of the AI models that I was talking about. So it is still very early, but we have a handful of examples of some of our top customers that are trying to leverage our infrastructure for things like fraud detection models and things like that. So we are starting to see early signs of that happening. The other thing which is really interesting is start-ups and other model heavy companies that are coming to take advantage of our GPU as well as our platform infrastructure that we've quickly realized that for them to scale their model and deploy it and as they start getting into the inferencing mode, they need a lot of the core cloud primitives that a platform like DigitalOcean offers from compute, network, storage, bandwidth, and having a global geo footprint to get inferencing with the lowest possible latency as close to their customers as possible. So we are starting to see very healthy early signs of these model-based companies quickly realizing that for them to go live and start getting into the inferencing mode, they need a lot more than just raw CPU horsepower. They need all of the cloud primitives. Yes, there are idiosyncrasies on how storage or networking works in the world of AI. But these cloud primitives are absolutely essential as the models get deployed and get into inferencing mode. And that's something that we are already seeing a lot of signs.

I have a two-part question for Matt. Regarding Paperspace, I believe the expectation was that it would contribute around three points to growth this year. It appears that you are already at about three points of growth. Are you still anticipating that level of contribution, possibly a bit more? Also, concerning EBIT, it looks like the increase isn't translating into the full year. Is there something related to the timing of expenses or any adjustments expected in the second half?

Yes. We're still very confident in our AI platform contributing 3% overall growth to the company. So that, as you said, we remain confident in. And we're encouraged by the early signs that we're seeing in that business. And I think that's what gave us the comfort to increase the bottom end of the guide and to increase the midpoint. From an expense standpoint, yes, the investments as they come on, what drives the EBITDA, some of that will happen in the latter half of the year as we increase our investment in R&D and we invest in additional space and power to accommodate the AI growth. So as we said, it's in our business, looking at it on an annual basis is way better than looking at individual quarters for free cash flow and in a certain extent, even gross margin and adjusted EBITDA because our expenses when we take down incremental space or power or it wouldn't hit EBITDA, but for gross margin, if we take down additional equipment, it's lumpy. It has a slight negative impact on the margins, and then we grow into it in the following quarter, which is what you saw from the increase in the EBITDA from the fourth quarter to the first quarter of this year.

Your next question comes from the line of William Kingsley Crane with Canaccord.

So I want to touch back on the Paperspace conversations. Well, I believe you have plans to create a more native link a shared dashboard between Paperspace and the core DigitalOcean interface sometime this year. So could you just talk more about what you can do from a product perspective to encourage those potential cross-pollination opportunities? And just what other gating factors you think you could address to encourage this?

Thank you for your question. It's a great one, and we are discussing it regularly in our product meetings. Our primary objective is to effectively address the use cases our customers are choosing us for. We want to ensure we have the necessary infrastructure, including the right GPU fabrics, networking, and various storage types needed by model builders, trainers, and extenders, as well as for inferencing. We're very focused on achieving this. Over the next few quarters, we expect to see significant progress in uniting these two environments, both from an infrastructure perspective and in terms of user experience. We are indeed considering this, but we prefer that the connection between the two areas develops naturally rather than pushing our customers to engage before they're ready. This connection is occurring on its own, and I anticipate that in the upcoming quarters, there will be substantial interaction between the two areas due to the natural technology convergence between our current Paperspace offering and the DigitalOcean core platform, including our App Platform and enhanced storage and droplet infrastructure that will also utilize the GPU infrastructure. Over the next six months, you can expect to see this natural convergence and we will continue to share updates on cross-sell activities. Right now, our main focus is to thoroughly address the needs of customers looking to leverage our platform as a service and the GPU infrastructure. So stay tuned, as we have many exciting developments planned for the next six months.

That's really helpful. And so then either for Patty or Matt, look, to take a step back, you're building an exciting technology business, but you're also highly profitable with a great financial model. That's been core to the DigitalOcean identity for a long time. I know you just had a sharp day in the past quarter. As we approach the next chapter of your growth story, how is employee sentiment? And how are you communicating that profitable technology mission internally?

Yes. Great question. So outside of spending time with customers, my #2 in terms of time spent over the last 90 days has been with our employees also known as Sharks. And the employee sentiment, I don't want to speak out of turn, but I think it is very robust. A lot of optimism, especially seeing the product velocity pick up over the last several weeks. And I only had time to go over the tip of the iceberg. Literally, I have only talked about 3 or 4 of a dozen or more product releases just in the last 4 weeks. So the innovation pace has visibly picked up across the company, and that is a massive rallying cry for the company. So the Sharks are super excited to get back into technology innovation. And as we do it, we get a tremendous amount of excitement from our community. And that is a major force multiplier for us internally to see the community really step up and take notice, and they are our best evangelists. So you can actually see the action in various threads on X, Discord, and other social media where there is a question from one of our customers. In addition to our employees jumping to answer that question, it is often the community that provides the first level support and engage in a debate with customers and prospects. So that is a major force multiplier for us internally. So I want to say that there's a lot of excitement internally, primarily driven by the pace of innovation. And we're also accelerating some talent addition, especially in the AIML space. We're getting the core DigitalOcean engineering team to also contribute a lot on our AI journey. And just the enhancements that I rattled off in my prepared remarks in terms of our core innovation has really energized. And then on the go-to-market side, it is still very nascent for us. We have a very robust customer service, customer support motion, and we are just in the early stages of taking all of the innovation that we are pushing out and translating that into a sustainable drumbeat of content and community amplification. So overall, I would say the company is energized and we are starting to grow in the same direction across the company.

Your next question comes from the line of Joshua Baer with Morgan Stanley.

I did want to ask about the sequential downtick in the learner customer cohort segment just for any context there. And then as a follow-up, somewhat related, just wondering more broadly if sort of doing any strategy shift away from maybe going after some of those smaller customers thinking about moving more upmarket to land more strategic customers that can expand and use more products on the platform.

Thanks, Josh. The strategy remains unchanged; we have an excellent platform for developers, entrepreneurs, and small growing technology companies to experiment and expand their businesses. The shift you noticed last quarter stemmed from a few factors. We are concentrating on the builders and scalers on our platform, which are not necessarily moving upmarket in the industry; they are simply our larger customers where we see significant expansion potential. Much of the feedback that Patty mentioned when speaking to customers aligns with what we've previously communicated: we believe we can capture a larger share of existing customers' budgets by removing product obstacles and adding valuable capabilities. The decline in learners is not substantial; we had 476,000 learners, and the decrease of 8,700 represented just 1.5 points of that total. This isn't a significant drop, and it was likely influenced by our stricter screening of small customers. We are always working to keep bad actors off our platform since they either don't pay or their activities are not beneficial to the online community. We've intensified our efforts in this area, which contributed to a smaller number of new additions this quarter, leading to a slight decrease in learners. However, I don't see this as a long-term trend; it reflects our strong focus on builders and scalers this quarter and some enhancements to our security practices.

Your next question comes from the line of Tim Horan with Oppenheimer.

Could we focus on the GPU CapEx spend a little bit? It feels like you're still capacity-constrained, maybe you can go into that a little bit. And can you give us a little color on maybe the payback that you think you'll get for this? And I know you touched on quite a bit the cross-selling capability. It would seem like more spend on CapEx here will help out the overall revenue growth. But any color on what you're thinking with your CapEx spend?

Yes, we acknowledged that we faced capacity constraints in the first quarter, and we are continuing to invest the capital we committed at the end of last year as part of our plan. Over the course of this year, we will increase our investments to enhance revenue growth, which is integral to our strategy. We are closely monitoring this process, and as we gain more insights into the specific needs of our target customers — which differ from those of larger customers purchasing from hyperscalers or substantial GPU farms — we will assess whether to allocate additional capital beyond what was initially planned. When considering the return profile for the business, it’s essential to view it in two distinct categories. First is our Platform as a Service offering, acquired from Paperspace, which aligns with our traditional cloud services involving software capabilities around the hardware. The payback period here is slightly lower than that of our core DigitalOcean business, although the gross margins are not considerably different. Then, in the GPU as a service or hardware segment, similar statistics apply regarding H-100 costs, inclusive of networking and other expenses. Generally, the going rate for GPU or H-100 services per hour yields approximately $0.50 in annual recurring revenue for every dollar of capital expenditure invested. Paybacks are typically seen in under three years, but the margins are lower than for our core service. It's an intriguing market dynamic, as one supplier currently dominates the majority of inventory, facing high demand, and market prices remain quite stable across all providers. Over time, we will observe how pricing evolves, especially concerning the current hourly rates for H-100 services. However, we anticipate significant improvements in the cost structure in the coming years as additional suppliers enter the market and as operational efficiencies in deploying these capabilities at scale are realized.

Your next question comes from the line of Michael Cikos with Needham.

I do just want to circle up on the expansion of the overall portfolio of services that you guys have. I think DigitalOcean, obviously very well-known historically for its product with the droplet. But wanted to see just given how this portfolio has expanded, are you actually seeing a shift as far as where you're landing with new customers? Are they landing on products outside Droplet, or does Droplet remain that bread and butter when we think about how customers are coming to the DigitalOcean platform?

Thank you for the question. Patty mentioned an impressive list of new capabilities we've introduced. We don't see this as expanding our portfolio but rather enhancing our existing capabilities. The company started as an infrastructure-as-a-service provider selling droplets, which consist of compute, bandwidth, and storage. Over the last decade, we've added Platform as a Service offerings like managed databases and Kubernetes, which are essentially extensions of our core infrastructure services. Our customers have evolved from individual developers and hobbyists to small tech firms and software providers running their businesses on our platform. The products Patty listed are simply additional capabilities that our customers need as they utilize our Platform as a Service and Infrastructure as a Service. They require more flexibility in configuring products with varying compute, storage, and bandwidth ratios. They also need features that simplify their experience since they often lack large IT teams. For instance, auto-scaling helps them manage their infrastructure more effectively. We don't consider any of our products or services as outside our core target customer market. As our customers grow and change, we must adapt alongside them to ensure they can easily utilize the cloud.

Okay. And then the other question, more of a follow-up here on the 2Q guide. We obviously have the 11% growth in hand, which is a slight deceleration sequentially. Can you just remind us what is that, I guess, Cloudways price increase that we're going to be lapping? How much of a headwind does that represent when we think about the growth we're looking at in Q2?

Yes, it's interesting to observe the focus on year-over-year metrics as I transition from a different market into the software space. Year-over-year metrics can be somewhat misleading because they reflect past performance, whereas the changes in growth from quarter to quarter are more relevant to what's happening now. Looking at our guidance from Q1 to Q2, we're forecasting increased incremental revenue, indicating that our annual recurring revenue is on an upward trajectory. This suggests our current growth is strengthening rather than slowing down. However, as you mentioned, when examining year-over-year, there is a slight deceleration. Some of this is due to a price increase in our Cloudways business from a year ago. The 34% growth we reported for Cloudways in Q1 includes about 10 percentage points from that price increase, which we will not have in our second quarter results.

Your next question comes from the line of James Fish with Piper Sandler.

Patty, in your opening remarks, you guys talked about discovering gaps in the product portfolio with customer conversations. What were those gaps that DigitalOcean needs to focus in on? Or were the release of products like backup and cash and capabilities of those gaps? And really, are those gaps on the AI side too? Or what's the differentiation on this infrastructure GPU as a service launch against some of the larger players out there like the hyperscalers core we land, especially if we start to get supply more balanced in time?

Thank you, Jim, for your questions. Let me start with the first one about the learnings I mentioned in my prepared remarks, specifically from a core DigitalOcean perspective. These learnings are reflected in our current product delivery, which involves numerous enhancements. As Matt mentioned, our Platform as a Service offering is relatively new compared to our droplets. As we increasingly focus on builders and scalers, there are features they desire from us to aid in their growth. You can expect us to introduce many new capabilities related to advanced reporting, management, infrastructure visibility, security enhancements, advanced networking, and global load balancing. These are the types of features our advanced scalers and builders are seeking from DigitalOcean as their operations expand and their businesses grow. I see these as excellent opportunities for us to further develop our platform in alignment with our customers' growth. Regarding your second question about differentiation from AI, specifically from an Infrastructure as a Service perspective, this situation feels strikingly similar to DigitalOcean's origin story. We aim to democratize infrastructure accessibility for AI builders, extenders, and companies wishing to deploy applications. The ease of getting started with our Infrastructure as a Service is a significant advantage, and we have received feedback indicating that many customers find it much simpler to initiate with us. We are not just providing bare metal GPU services; we are also implementing various orchestration layers. It's not just about raw H-100 boxes; there are numerous complexities involved, especially for small startups or independent software vendors in areas like ad tech who want to utilize various AI models. A lot of technology is required to build or even extend models, and customizing those models to fit specific environments, like incorporating RAG for context, presents additional challenges. Even as a consumer of models, navigating these complexities can be daunting. Our software has always prioritized simplicity, and our Platform as a Service facilitates this across the entire life cycle of AI and machine learning development. Our Infrastructure as a Service covers everything from bare metal to orchestrated abstractions, simplifying the process for our customers. While we are experiencing growing momentum, we are committed to thoroughly understanding our customers' needs because we don't want to merely address transient spikes in demand. Our goal is to create a sustainable business, and we believe that providing inferencing represents a viable long-term AI business model that will support us in the coming years.

Very helpful and thorough answer and Matt, if I could sneak in one with you. You guys are reiterating your free cash flow margins at this point, which probably means that 15% to 17% CapEx range is still what you're thinking. But GPU purchasing seems to be relatively strong. I'm getting a guess. That's why CapEx was a little bit elevated versus what we were all thinking this quarter. Is it still on pace for that $50 million at this time? Or should we interpret your language around potential free cash flow margins coming down in the coming quarters as this is running ahead of plan? And really, are you thinking about using other GPU providers this year?

I wouldn't say we're ahead of plan; we're still deploying the capital we committed last year. We have good visibility into our current capital spending. We're encouraged by the progress in the AI business, and we're learning a lot. Patty has only been here a couple of months, and we're evaluating our customers' needs, understanding what customers we can attract, their requirements, and the right technology configuration. As we continue to see positive signs and growth, we'll decide if we want to spend any additional capital beyond what was planned. We're on track with our current plan and not behind or ahead concerning the capital intensity of our business. We're just expressing that we're encouraged, and as we see more positive developments, we'll provide updates on whether we plan to increase our spending.

That concludes our Q&A session. I will now turn the conference back over to Padmanabhan Srinivasan for the closing remarks.

Thank you very much. As you just heard, we are accelerating our pace of innovation and delivering new capabilities in a very rapid cadence, which will help our customers grow on our platform. As I alluded to, there's still a lot of work to do to take full advantage of our opportunity, but I'm very excited that we are moving in the right direction and continue to make steady, rapid, and respectable progress quarter-over-quarter. So with that, I would like to thank everyone for their time and talk to you all soon.

Thank you. That concludes today's conference call. Thank you all for joining. You may now disconnect.