Olivier Pomel: Yeah, as a reminder, we have a broad range of customers with a long tail. And similar to what we discussed last quarter, the gross number of ads, so the accumulation in the enterprise, it was quite strong. It was very similar to what we’ve experienced. And we have a very small pale that has a large attrition rate but doesn’t have a lot of dollars attached to it. So the trends continue, which is very strong, as Olivier mentioned. New logo accumulation, both in terms of number of new logos, [NARR] (ph), and that was true when Olivier talked about the enterprise side of it, offset by this tail that has very little dollars associated with it.
Olivier Pomel: Yeah, and just to comment on that, remember the bottom half of our customer represent around 1% of our revenue and the lower increase in customer number comes from the very, very low end, which is customers that pay us in the tens of dollars a month. Those customers, we’re getting a little bit less of those to start with. I think that’s part of the economic environment and the churn is a little bit higher than it used to be there too. So that’s why this number is a little bit depressed right now. That being said, we had a record number of new logos over $100,000. We’re doing very well in the enterprise. We’re doing very well in the new market. We’re also doing very well at the high end of the SMB. So we are very happy with all of the segments we’re targeting with our sales and marketing motions today.
On the enterprise side, we actually mentioned a few of those very exciting contracts on the call. We get really, really excited when we see very traditional enterprises moving to the cloud and adopting us and concentrating on us in a [indiscernible]. David is there — we can’t see it. In the room David is smiling because he’s excited when he sees the dental care companies, he’s excited when he sees the network of convenience stores where we even instrument the fuel pumps. So these are great developments for us and we’re leaning hard into that.
Operator: Thank you. One moment for our next question. And our next question comes from Kash Rangan of Goldman Sachs.
Kash Rangan: Hello. Thank you very much. Good to see you. I’m sure that you’re all smiling at your results. Two things. One is, with respect to LLM monitoring, which was demoed at the DASH conference, which was, I thought, absolutely fascinating. I know you quantified, Ollie, at 2.5 percentage points of growth coming from generative AI workloads. How do we think about the revenue option for LLM monitoring at an early stage? I also have a second question, slightly more controversial. If we run into customers that think they’re spending their bills for Datadog or getting to be a little bit on the larger side that is a sign of success, but how do you ensure that that success does not work against the company that it opens up the door for price competition from others. Thank you so much and congrats.
Olivier Pomel: Yes, on the LLM Ops side, I think it’s too early to tell how much revenue opportunity there is in the tooling specific to LLM Ops. When you think of the whole spectrum of tools, the closer you get to the developer side, the harder it is to monetize, and the further you get towards operations and infrastructure, the easier it is to monetize. We can ship things that are very useful and very accretive to your platform because they get you a lot of user, a lot of attention, and a lot of stickiness that are harder to monetize. So we’ll see where on the spectrum that is. We know though is that the broader generative AI up and down the stack, you know, from the components themselves or the GPUs all the way up to the models and the various things that are used to orchestrate them and store the data and move the data around.
All of that is going to generate a lot of opportunity for us. We said right now it’s concentrated among the AI native largely model providers, but we see that it’s going to broaden and concern a lot more of our customers down the road. And your second question was, so when we grow a lot, we are very successful with some customers. How do we not create a long-term issue where they spend a lot of money and that gets competition? Look, it’s a great situation to be in to have customers spend a lot of money on you and have to justify that value over time, I think it’s very healthy. I think that — again, that’s what drives innovation and great product development. And our role there is to make sure we have a healthy partnership with customers every single step of the way.
And we charge them an order on magnitude less than what they spend for their cloud infrastructure. Maybe two orders of magnitude less than what they spend on their R&D. And so we think we should be in a position of leverage, where if we do our jobs right, we show a lot of value for our customers, we save them a lot of money, we make them a lot faster, and we have them generate a lot more revenue. So that’s how we see things and how we hold ourselves to.
Operator: Thank you. One moment for our next question. And our next question comes from Alex Zukin of Wolfe Research.
Alex Zukin: Hey, guys. Thanks for taking the question, and congrats on a great quarter. Maybe just two quick ones for me. Olivier, you mentioned the federal opportunity or you mentioned the federal activity in the quarter with a deal that was pretty interesting. Is that something that we picked up as an area of excitement for you guys. Can you maybe just talk about what the opportunity there is over the next 12 months and beyond? Maybe stock rank is a priority for you guys? And then I’ve got a quick follow up.
Olivier Pomel: So I missed the domain you’re talking about.
David Obstler: Fed.
Olivier Pomel: Oh, Fed. So that’s definitely an area of investment for us. It’s a — look, we are happy with two things. Happy with the fact that we’re moving further and further into the various level of certifications needed. We’re happy with the early success with some agencies where we are spreading and [indiscernible] agencies and now getting to grow some of those world to world. But we’re only scratching the surface of what we can do inside. And there’s a lot more we need to do. Some of it on the certification side and the product side, and some of it on the go-to-market side and making sure we have all of the parts of the motion working. So I expect that to be one of the main areas of investment on the go-to-market side next year in terms of new markets we’re going after.
Kash Rangan: And then maybe on the — back on the AI question. I guess maybe just drill a little bit deeper within those AI native companies, the criticality of their data guide uses? Meaning, are you seeing something different where in a world where these applications become more prevalent, there’s the opportunity to kind of expand wallet share as observability becomes even more important? And how should we think about the growth opportunities from those types of workloads in either 2024 or 2025?
Olivier Pomel: Yeah, so, in general, the more complexity there is, the more useful observability is, the more you shift value from writing code to actually understanding it and observing it. So to caricature, if you spend a whole year writing five lines of code that are really, really deep, you actually know those five lines really well. Maybe you don’t know the ability for it because you’ll see you understand exactly how they work and what’s going on with them. On the other hand, if — thanks to all the major advances of technology and all of the various open source and AI, and you can just very quickly generate thousands of lines of code, ship them and start operating them, you actually have no idea how these work, what they do, and you’ll need a lot of tooling and observability to actually understand that and keep track on that and secure it and do everything you need to do with it all the time.
