Datadog, Inc. (NASDAQ:DDOG) Q1 2024 Earnings Call Transcript

Datadog, Inc. (NASDAQ:DDOG) Q1 2024 Earnings Call Transcript May 7, 2024

Datadog, Inc. beats earnings expectations. Reported EPS is $0.44, expectations were $0.3533. Datadog, Inc. isn’t one of the 30 most popular stocks among hedge funds at the end of the third quarter (see the details here).

Operator: Good day, and thank you for standing by. Welcome to the First Quarter 2024 Datadog Earnings Conference Call. At this time, all participants are in listen-only mode. After the speakers’ presentation, there’ll be a question-and-answer session. [Operator Instructions] Please be advised that today’s conference is being recorded. I would now like to hand the conference over to your first speaker today, Yuka Broderick, Vice President of Investor Relations. Please go ahead.

Yuka Broderick: Thank you, Marvin. Good morning, and thank you for joining us to review Datadog’s first 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 second quarter and fiscal year 2024 and related notes and assumptions, our gross margins and operating margins, our product capabilities, our ability to capitalize on market opportunities and usage optimization trends. The words anticipate, believe, continue, estimate, expect, intend, will, and similar expressions are intended to identify forward-looking statements or similar indications of future expectations.

These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-K for the year ended December 31, 2023. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended March 31, 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 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 are pleased with our execution at the start of 2024. First, we have continued to broaden our platform across observability, cloud security, software delivery, as well as closing the loop with Cloud Service Management. We also kept supporting our customers’ adoption of new technologies, including next-gen AI and large language models. And we have continued to add new customers and to see existing customers increase our usage growth and product adoption. Let me start with a review of our Q1 financial performance. Revenue was $611 million, an increase of 27% year-over-year and above the high end of our guidance range. We ended the quarter with about 28,000 customers, up from about 25,500 last year.

We had about 3,340 customers with an ARR of $100,000 or more, up from about 2,910 last year. These customers generated about 87% of our ARR. And we generated free cash flow of $187 million, with a free cash flow margin of 31%. Turning to platform adoption. Our platform strategy continues to resonate in the market. As of the end of Q1, 82% of customers were using two or more products, up from 81% a year ago; 47% of customers were using four or more products, up from 43% a year ago; 23% of our customers were using six or more products, up from 19% a year ago; and 10% of our customers were using eight or more products, up from 7% last year. We continue to see robust growth in our three pillars of observability, infrastructure monitoring, APM and log management.

But we also have many younger products that are becoming more meaningful contributors to our business over time. For example, our products outside of infrastructure monitoring, APM suite, and log management exceeded $200 million in ARR in Q1. And as a reminder, within the APM suite, we include core APM, Synthetics, RUM, and Continuous Profiler. And as we look at the 12 products that we launched between 2020 and 2022, those now contribute about 11% to our ARR. Of those 12 products, eight are over $10 million in ARR, which is a nice milestone for these relatively new additions. And we are seeing some products grow faster than we initially expected. For example, Database Monitoring is already 1% of our revenue with strong and growing product penetration across our customer base.

So, we are very pleased with the progress of our newer products, even though we know we have much further to go with them. Now let’s discuss this quarter’s business drivers. In Q1, we saw usage growth from existing customers that was higher than in Q4, and this usage growth in Q1 was similar to what we experienced in Q2 and Q3 of 2022. As a reminder, that was a period when we started to see a normalization of usage following the accelerated growth we had experienced in 2021. Overall, we saw healthy growth across our product lines. And as usual, our newer products grew at a faster rate on a smaller base. While some of our customers are continuing to be cost-conscious, we are seeing optimization activity reduce in intensity. As an illustration, the optimizing cohort we identified several quarters ago did grow sequentially again this quarter.

We also see that customers are adopting more products and increasing usage with us. We think this shows that they are moving forward with their cloud migration and digital transformation plans and that we are executing on opportunities to consolidate point solutions into our platform. And finally, churn continues to be low with gross revenue retention stable in the mid-to-high 90%s, highlighting the mission-critical nature of our platform for our customers. Moving on to R&D. We had another very productive quarter. In the next-gen AI space, we announced general availability of Bits AI for Incident Management. By using Bits AI for Incident Management, incident responders get auto-generated incident summaries to quickly understand the context and scope of a complex incident.

And users can also query Bits AI to ask about relative incidents and perform tasks on the fly from incident creation to resolution. We’re also continuing to see more interest in AI from our customers. As a data point, ARR from our next-gen AI customers was about 3.5% of our total, a strong sign of the growing ecosystem of companies in this area. To have customers understand AI technologies and bring them into production applications, our AI integrations allow customers to pull their AI data into their Datadog platform. And today, about 2,000 of our customers are using one or more of these AI integrations. And we’ve continued to keep up with the rapid innovation in this space, for example, adding a new integration in Q1 with the NVIDIA Triton Inference Server.

In the Cloud Service Management area, we released Event Management in a general availability. Our customers face increasing complexity at scale, causing the volume of alerts and events to explode, which makes it difficult for teams to identify, prioritize, summarize, and route issues to the right responders. Event Management addresses this challenge by automatically reducing a massive volume of events and alerts into actionable insights. These are then used to generate tickets, call an incident, or trigger an automated remediation. And by combining event management with Watchdog, Bits AI, and Workflow Automation, Datadog now provides a full AIOps solution that helps teams automate remediation, proactively prevent outages, and reduce the impact of incidents.

In the observability space, our log management product continues to expand in capability. In March, we made Error Tracking for logs generally available. Error Tracking intelligently combines millions of errors from logs into a manageable number of issues for customers. And beyond Error Tracking, we are delivering new features to allow our customers to do more with their logs within the Datadog platform, starting with new query capabilities such as enhanced full-tech search and support for advanced sub-queries, both highly desired by our customers. We also continue to make progress with Flex Logs. As a reminder, Flex Logs allow customers to easily scale storage and compute separately, which in turn allows for new very high volume use cases in a cost-effective manner.

While Flex Logs remains in limited availability, we are seeing a high level of interest from customers, many of whom want to retain logs for long-term purposes such as audit, security, and compliance. And we’re pleased to see that with only a limited set of customers so far, Flex Logs already exceed $10 million in ARR today. In the Digital Experience area, we launched Mobile App Testing in general availability, giving access to fast, low-code, reliable testing on real mobile devices, which was a big challenge for customers given the wide range of devices and operating systems in use by consumers. And in Cloud Cost Management, we’ve added full support for Google Cloud, so FinOps and DevOps teams can optimize their Cloud spend across their AWS, Azure, and GCP footprints.

Cloud Cost Management is another of our newer products that exceeds the $10 million ARR milestone. And we believe there’s significantly more opportunity for us to have our customers there. As usual, I’d like to thank our product and engineering teams for the quarter, and I’m looking forward to the many announcements we’ll make at our DASH conference in late June here in New York. Now, let’s move on to sales and marketing. We’ve been pleased to once again add some exciting new customers and expand with many more. So, let’s go through a few examples. First, we signed a three-year seven-figure expansion with a leading online grocery business. This customer has used Datadog as their platform of choice for several years now. And as they migrate to Azure, they are looking to ensure reliability and security as they deploy at scale.

With this renewal, they are adding Cloud Security Management, Application Security Management, and Cloud SIEM to enable a shift to a DevSecOps culture in their organization. And this customer expects to add seven products for a total of 14 across the Datadog platform. Next, in two deals over the past six months, we had a seven-figure expansion with a medical device company. This customer was primarily using our infrastructure monitoring and APM suite, but its legacy logging solution was becoming cost-prohibitive, while the lack of correlation across siloed teams was causing frustration and higher times to resolution. With this expansion, the customer plans to adopt nine products and consolidate its log management tool as well as four other commercial and cloud-native tools into Datadog.

Next, we signed a high six-figure expansion with an athletic apparel company. This company had a dozen disparate monitoring tools, which wasted time and was impacted operations, revenue, and customer experience. With this expansion, the company plans to consolidate out of four commercial and open-source point solutions. They also expect to save millions of dollars over the next several years while providing a great consumer experience. Next, we signed a high six-figure expansion with a European division of one of the world’s largest car makers. This customer has chosen Datadog as its observability vendor in many business units globally. And in Europe, they currently monitor about a quarter of the applications with us and are migrating hundreds of applications to fully move to Datadog in the next two years.

With this expansion, this customer is using eight products in the Datadog platform. Next, we signed a six-figure land with the division of a Fortune 500 industrial company. The company is moving its e-commerce application to Google Cloud. They felt that existing on-prem monitoring tools would not transition well to the cloud and are starting with three of our products as they are confident in Datadog’s ability to keep innovating in modern cloud and serverless environments. Finally, we signed a six-figure land with one of the world’s largest communication infrastructure companies. This company started a cloud migration a couple of years ago and found itself limited by fragmented tooling and lack of data correlation. In contrast, the Datadog Service Catalog gives them a single view for performance, ownership, security, SLOs, and KPIs, which this customer believes is a unique capability among the vendors it considered and which aligns with their goal of delivering centralized observability across the business.

And this customer is adopting seven Datadog products initially and consolidating out of four tools. And that’s it for another productive quarter from mobile to market teams. Let me now say a few words on our longer-term outlook. Overall, we continue to see no change in a multi-year trend towards digital transformation and cloud migration. We are seeing improved usage growth with less impact from optimization than we had seen in the last few quarters. For those customers who are remaining cost focused, we are very happy to help them get value from their observability solutions and consolidate into the Datadog platform to achieve time and cost savings. Meanwhile, we are seeing continued experimentation with new technologies, including a growing adoption of AI, which we believe will be an accelerator of technical innovation and cloud migration over time.

And we’re working every day to innovate and help our customers adopt new technologies with confidence and become better businesses in the process. With that, I will turn it over to our CFO. David?

David Obstler: Thanks, Olivier. Q1 revenue was $611 million, up 27% year-over-year and up 4% quarter-over-quarter. To dive into some of the drivers of the Q1 performance, first, regarding usage growth. In Q1, we saw sequential usage growth from existing customers that was higher than the usage growth in Q4. Q1’s usage growth was similar to what we experienced in Q2 and Q3 of 2022. And given this growth and of a larger base, our sequential ARR dollars added was the highest since Q4 2021. During Q1, we experienced a linearity pattern that was very typical for us, which included usage growth in March that was higher than January and February. Regarding usage growth by customer size in Q1, we saw usage growth accelerate across our larger customers, those with $100,000 of annual spend or higher.

And we saw particularly strong usage growth with our largest customers who spend multiple millions of dollars with us annually. Geographically, we experienced stronger year-over-year revenue growth in international markets than in North America. And finally, for our retention metrics, our trailing 12-month net revenue retention was in the mid-100%s in Q1 — sorry, in the mid-110%s in Q1, similar to last quarter. Our trailing 12-month gross revenue retention continues to be stable in the mid to high 90%s. Now moving on to our financial results. Billings were $618 million, up 21% year-over-year. Billings duration increased year-over-year. Sequential billings growth was seasonally lower as it was in Q1 2023. Remaining performance obligations, or RPO, was $1.73 billion, up 52% year-over-year, and current RPO growth was in the low 40%s growth year-over-year.

RPO duration increased year-over-year but was down quarter-over-quarter, as we saw fewer multi-year deals relative to last quarter. In general, we are continuing to see an increasing interest with our larger customers in multiyear commitments, which results in longer RPO duration in both total and current RPO. As a reminder, our RPO has been and continues to be lumpy, an effect that may be amplified as our customers move towards multi-year deals. We continue to believe revenue is a better indication of our business trends than billings and RPO, as those can fluctuate relative to revenue based on the timing of invoicing and the duration of customer contracts. Now let’s review some key income statement results. Unless otherwise noted, all metrics are non-GAAP.

We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. First, gross profit in the quarter was $509 million, representing a gross margin of 83.3%. This compares to a gross margin of 83.4% last quarter and 80.5% in the year-ago quarter. We continue to experience efficiencies in cloud costs, reflected in our cost of goods sold as our engineering teams pursue cost savings and efficiency projects. Our Q1 OpEx grew 14% year-over-year and increased from 10% year-over-year growth last quarter. As discussed last quarter, we intend to invest in headcount in 2024, and we have accelerated hiring in sales and marketing and R&D to execute on our growth plans. Q1 operating income was $164 million, or 27% operating margin compared to 28% last quarter and 18% in the year-ago quarter.

And now turning to the balance sheet and cash flow statements. We ended the quarter with $2.8 billion in cash, cash equivalents, and marketable securities. Cash flow from operations was $212 million in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $187 million for a free cash flow margin of 31%. Now for our outlook for the second quarter and the fiscal year 2024. Our guidance philosophy remains unchanged. As a reminder, we base our guidance on trends observed in recent months and apply conservativism on these growth trends. So, for the second quarter, we expect revenue to be in the range of $620 million to $624 million, which represents a 22% year-over-year growth. Non-GAAP operating income is expected to be in the range of $134 million to $138 million, which implies an operating margin of 22%.

In Q2, we will be holding our DASH User Conference, which we estimate to cost about $11 million. Our operating income guidance reflects this event. Non-GAAP net income per share is expected to be $0.34 to $0.36 per share based on approximately 360 million weighted average diluted shares outstanding. For fiscal year 2024, we expect revenue to be in the range of $2.59 billion to $2.61 billion, which represents 22% to 23% year-over-year growth. Non-GAAP operating income is expected to be in the range of $585 million to $605 million, which implies an operating margin of 23%, and non-GAAP net income per share is expected to be in the range of $1.51 to $1.57 per share based on approximately 361 million weighted average diluted shares outstanding.

Now for some additional notes on our guidance. First, we expect net interest income and other income together for fiscal 2024 to be approximately $110 million. Next, we expect cash taxes in 2024 to be in the $20 million to $25 million range, and we continue to apply a 21% non-GAAP tax rate for 2024 and going forward. And finally, we continue to expect capital expenditures and capitalized software together to be 3% to 4% of revenues in fiscal 2024. To summarize, we are pleased with how we started 2024 and I want to thank Datadogs worldwide for their efforts. And now with that, we will open the call for questions. Operator, let’s begin the Q&A.

See also 12 Best Artificial Intelligence Stocks to Buy Now According to Wall Street Analysts and 25 Cheap Cars That Will Make You Look Rich.

Q&A Session

Operator: Thank you. At this time, we’ll conduct a question-and-answer session. [Operator Instructions] Our first question comes from the line of Sanjit Singh of Morgan Stanley. Your line is now open.

Sanjit Singh: Thank you for taking the questions. It was encouraging to see that usage trends continue to improve, at least sequentially Q1 over Q4. I wanted to see if you could put like the usage trends you’re seeing in your business in context of like the broader cloud landscape. And we’re seeing some really nice results out of the hyperscalers. Obviously, those are much larger businesses and can be in different product areas. But when we think about the tailwinds of like cloud migrations and also AI workloads starting to come on board, how is that playing out in Datadog’s business versus what we may be seeing from, like, the hyperscalers who are — who seem to be accelerating to a higher degree?

Olivier Pomel: Yeah. Hi, Sanjit, this is Olivier. So, I think, in general, the — it’s hard to be — to draw a precise quarter-by-quarter, one-to-one mapping between the revenue and the cloud providers and our revenue. I think you pointed out there are things in their products that don’t relate to us directly or things that — revenue that don’t relate to us directly. We have products that don’t tie one-to-one with infrastructure on their end. But in general, over the longer term, we are very exposed to the growth trend you will see with the cloud providers and the correlation you’ve seen in the past between our businesses we expect will remain in some form in the future. We’re also very exposed to the same tailwind of obviously cloud migration, but also AI adoption.

I will say also on AI adoption that some of the revenue jumps you might see from the cloud providers might relate to supply of GPUs coming online and a lot of training clusters being provisioned, and those typically won’t generate a lot of new usage for us. We tend to be more correlated with the live applications, production applications, and inference workloads that tend to follow after that and that are more tied to all of these applications going into production. So, these are the things to factor. But overall, same trends, just not a one-to-one timing.

Sanjit Singh: That makes complete sense. And I was wondering if you had any comments on how usage trends coming out of March would seem to be stronger than in the beginning of Q1, how that sort of played out in April?

David Obstler: Sure. Hey, Sanjit. How are you? David here. As we always say, we try to look into the next month, but that’s a small time set. In this case, the April trends continue to exhibit higher sequential growth rates than the year-ago quarter. But we caution everybody that one month does not a quarter make and we’ll continue to update that next quarter as we report.

Olivier Pomel: And the seasonality in Q1, I would say, is very usual. Every year, there’s a drop around the holidays in Q1, then January starts slowly and then it accelerates into March. And we’ve seen that pretty much every single year so far, and we’ve seen it this year as well.

Sanjit Singh: Appreciate the color. Thanks, Olivier. Thanks, David.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Mark Murphy of JPMorgan. Your line is now open.

Mark Murphy: All right. Thank you so much, and congratulations on the revenue acceleration during the quarter. Olivier, I’m wondering how commonly are customers in your GenAI cohort using Datadog to monitor for bias and hallucinations within their AI models as opposed to just keeping the systems running? And also, do you see more concentration of customers within that cohort, or is there actually more diversity as more of the models move beyond the training stage and into the inferencing stage?

Olivier Pomel: So, we have products for monitoring not just the infrastructure, but what the LLMs are doing. Those products are still not in GA. So, we’re working with a smaller number of design partners for that. I think not only these products are maturing, but also the industry around us is maturing and more of these applications are getting into production. You should expect to hear more from us on that topic in the near future. The customers we have that are the most scaled on AI workloads are the model providers themselves, and they tend to have their own infrastructure for monitoring the quality of the models. But we think they’re a good bellwether in terms of what the adoption of AI is going to be from all the other companies.

And we definitely see a trend where customers start with an API-driven or API-accessible model, build applications, and then offload some of that application to other models that typically come from the open source, and they might train, fine-tune themselves to get to a lower cost and lower time to respond.

Mark Murphy: I understand. Okay. And then, David, you had mentioned, I think last quarter that the cloud-native spending had rebounded. It was outpacing the broader business. And just to clarify, are you saying that the traditional large enterprise business during Q1 you picked up in terms of the cloud migration activity, as their hyperscalers might have suggested, was that — I’m just wondering if you could double click on that comment and whether there was something really noticeable intangible there among the large enterprise, more traditional businesses.

David Obstler: Yeah. We saw — we said we saw growth accelerate in our larger customers, including the larger cloud natives and enterprise. So, we did see more normal activity, including new workloads in both of those cohorts.

Mark Murphy: Thank you.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Kash Rangan of GS. Your line is now open.

Kash Rangan: So good to go right after Mark. Congratulations to the team on very good results here. Olivier, I was wondering if you could talk about the consolidation trend that you’re talking about. It looks like the pace of consolidation and also the intensity of lands and expanse seems to be a bit more remarkable at the starting point of this calendar year. So, if you could expand on that a little bit? And one for you, David. cRPO has been accelerating, I think, at low 20%s to 30%s to 40%s over the last few quarters, but revenue expectations have not edged up pretty significantly. So, can you just talk about the lead lag effect, granted that you always try to tell us that revenue is the best indicator, but nonetheless, it’s hard to dismiss the cRPO acceleration we’ve seen off of the last three quarters? Thank you so much.

Olivier Pomel: Yeah. So, I’ll let David speak about the cRPO dynamics. But — so look, we’ve seen over the past couple of years, really the past few quarters more consideration than we’ve seen in the past, in part driven by customers wanting to — being cost-conscious, wanting to save money, but in part also by customers getting a little bit further into their cloud migration and rationalizing what they’re using as they do that. So, we keep saying that. We’ve mentioned a number of those deals in the examples we’ve given. That’s a large part of what our enterprise business is doing in particular. There’s no particular change in Q1 compared to what we’ve seen in Q4 before. Q1 is — we typically do a lot of larger deals in Q1 — in Q4 compared to Q1 seasonally, in general.

To the point you made earlier, we do see typically a bit of a lag between these big consolidation deals and the moment where we see our revenue recognized. Typically, when we consolidate products, what we’ll see is we’ll assume the ramp time for moving usage from other products to our platform over what can be a number of quarters or even years sometimes. And it might take some time for those deals to — for all those numbers to materialize in the revenue. On the flip side, we also have a number of deals where customers are growing very quickly into their usage and we capture new commitments with them that might lag a little bit their consumption and the revenue we recognize. So, we see a little bit of both. David, you want to speak a little bit more?

David Obstler: Sure. Similar to what we said last time, we are seeing our customers, particularly our larger customers, commit longer to us that can be multi-year deals or even out towards the weighted average towards annual deals as opposed to shorter-term deals. So, basically, it is a positive in that it does connote that clients are committing to Datadog more as their core platform. It is a trend that we’re seeing, particularly in larger customers. But we repeat what we said, that really how we contract and bill is not necessarily one-to-one correlated with our revenues. Our revenues are correlated with our usage. So, it’s a positive. But I think that we want to keep everybody grounded on our revenues as the most important metric, and then secondarily our ARR as predicting future revenue growth.

Kash Rangan: Wonderful. Thank you so much and congrats.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Raimo Lenschow of Barclays. Your line is now open.

Raimo Lenschow: Thank you. Going back to the workload migration that seems to be kicking back in again from listening to the hyperscalers and you talked about the timing difference there. I want to kind of ask on a different aspect here, and that’s kind of your sales capacity and the ramp in sales capacity that we should think about it. Like, can you speak about, like, where you are at the moment in terms of capacity? And then, as the market reaccelerates, like, what sort of investment should we think about there? Thank you.

Olivier Pomel: So, we’re growing sales capacity. We’ve been growing it for the past few years. We grew it a little bit slower, mostly last year as we were very careful about profitability and not getting too far ahead of ourselves in what look like a tough market. But we’re definitely growing sales capacity. And there’s a ramp model that is associated with that. So, the capacity typically lags a little bit the growth in terms of headcount, as it takes time for people to be productive, but we’re investing, we’re growing, and…

David Obstler: Yeah, long-term sales capacity is very much calibrated to revenue and ARR growth. As Oli mentioned, there are periods where it will move higher than that as we make investments and there’s periods where we might optimize. I think last year was a period where we digested previous investments, optimized a bit, and we said, this year we’re leaning into expansion of our sales capacity and investment. But long term, it correlates with revenue. And we look at that, we look at, do we have enough sales capacity relative to what we see as the demand in the market, the territories, and the expected ARR growth.

Olivier Pomel: To give you just a bit more color, like, one of the big areas of focus inside the company is ramping up, recruiting again. So, we’re recruiting a lot faster, a lot more than we were last year. And so, we had to rev up that recruiting engine again. I think they’re listening to us. I want to congratulate our business recruiting team there for doing a fantastic job, really bringing that engine back up.

Raimo Lenschow: Perfect. Hey, thank you. That’s really encouraging.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Matt Hedberg of RBC. Your line is now open.

Matt Hedberg: Great. Thanks for taking my questions, guys. Oli, you mentioned newer products continue to do really, really well. You gave some interesting data on Database Monitoring for instance. I’m wondering, are these newer products resonating up and down your customer base, or are these — some of these cross-sell statistics stronger with some of your bigger customers?

Olivier Pomel: Yeah. So, it really depends on the product. Some products are extremely broad based in terms of their appeal, and some others are really more directed at certain types of customers. For example, our products that have to do with monitoring physical networks, they tend to be more appealing to larger, older enterprises, because they are the ones with large physical footprints, whereas products like Cloud Cost Management, for example, or even Database Monitoring have very, very broad appeal, because every single customer cares about their cloud cost and every single customer is using databases that are the center of their applications and that are absolutely critical to understand. And we mentioned those products because really, like, we see that as the — our efforts paying off in terms of broadening the offering and investing in R&D.

And these are green shoots that we expect to grow into the future. Some of those products we have extremely high expectations for because they correspond to very large categories which we can think can be very meaningful to the business in the long run. Some others are surprising us a little bit. That’s why we mentioned Database Monitoring. We were not sure if it was going to be a huge category in cloud environment. But it turns out not only is there a very big problem our customers need us to solve there, but also this product hit that problem on the head from day one, really. And we expect — now we expect a lot more from it.

Matt Hedberg: Got it. Thanks a lot. Congrats on the results, guys.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Fatima Boolani of Citi. Your line is now open.

Fatima Boolani: Good morning. Thank you for taking my questions. David, you explicitly mentioned that the international book of business and activity was stronger than domestic. So, I wanted to better understand some of the more intrinsic and maybe extrinsic dynamics that are driving that divergence in terms of geographic [theater] (ph) performance. And if you could sort of help us understand if it’s an end market, a product-based or a budgetary based set of distinctions, that would be very helpful. Thank you.

David Obstler: Yeah, it’s very similar to what we’ve been saying over time. The international markets have been more immature as to their cloud migrations and their deployment of digital applications than the North American markets. And we’ve been more immature in terms of our footprint. So, we’ve talked about some examples in Investor Day and otherwise, places like Brazil and Korea, to name just a couple, where we are seeing an increase of activity as well as an increase of our deployment of our capacity, which has resulted in an uptick of international demand over time.

Olivier Pomel: Yeah. For us to be successful, there are two factors that are needed. So, first one is cloud adoption needs to happen because we can’t run it, really. And the second one is we need to deploy sales capacity and grow sales capacity. And that’s really the combination of the two. In most markets today, cloud adoption is happening. There still may be a few holdouts that are a little bit slower, and — but we’re not yet deploying enough sales capacity everywhere. And that’s one of our big areas of focus, as I mentioned earlier.

Fatima Boolani: Thank you.

Operator: Thank you. One moment for our next question. Our next question comes from the line of Brent Thill of Jefferies. Your line is now open.