Datadog, Inc. · Q2 2026 call

Revenue growth for our non-AI customers also accelerated again this quarter to the high 20s percent year over year, up from the mid-20s last quarter and 18% in the year ago quarter.

We’re also seeing signs of rapid growth in agent activity, with a number of MCP tool calls […] growing more than 22x when compared to Q4 2025.

our 11% quarter over quarter revenue growth is the highest since Q2 2022, and our quarter over quarter revenue added of $115 million is a record by a significant margin.

This 750-strong customer group includes a broad range of AI startups, as it has in the past, but now also includes hyperscalers using Datadog Inc for in-house AI labs. In Q2, this includes 31 customers spending more than $1 million annually, of which 8 customers spent more than $10 million annually.

We also achieved strong new logo dollar bookings with particular strength in enterprise, where new logo annualized bookings more than doubled from a year ago.

The portion of our year-over-year revenue growth that relates to new customers was about 30% in Q2, up from 25% in Q1.

our trailing 12-month net revenue retention percentage was in the low 120s, similar to last quarter, and churn remains low with gross revenue retention in the mid to high 90s.

Our Q2 gross profit was $892 million for gross margin of 79.6%. This compares to a gross margin of 80.2% last quarter and […] 80.9% in the year-ago quarter. As we’ve discussed in the past, our gross margin varies from quarter to quarter with investments into innovations for our customers offset by efficiency efforts.

Regarding our largest customer, we have seen a usage reduction which is incorporated in our Q3 and full year 2026 guidance.

we expect CapEx and capitalized software together to be in the 4-5% of revenue range in fiscal 2026.

we did see a reduction in usage, and we took the liberty to fully de-risk the guidance for the rest of the year with respect to that customer. And again, the reason for that is we don’t control what’s happening to a specific customer, but we do have a great amount of control on what’s happening to everything else in the business. And the business is booming

if you back out our largest customer from our growth, you get pretty much the same growth, right? As the rest of the business has been accelerating very steadily. Actually, we’ve seen, I think now 5 quarters of continuous acceleration from the rest of the business

we do think at the end of the day inference will be the dominant workload. Anytime you train, you probably will want to infer more than you train as a rule of thumb.

in this case we did choose to fully de-risk our largest customer. And the reason for that is we don’t want that to be an overhang on what is otherwise a business that is accelerating and performing extremely well

there’s only two reasons people buy software, you know, it makes them more money or it saves them money. […] What we do for our customers today, especially as they keep adopting AI, is we help them save a lot of the money they would spend on building, running operations, or running AI agents.

how can you help me rein in my AI costs? You know, this is growing very fast and I don’t have any control on it, and I don’t know whether I’m reaching the right outcomes with that.

The future of observability is not just observing, it’s fixing. You know, it’s not waking up people in the middle of the night because something broke, but fixing it for them.

if you compare to what we have seen in the heady days of, you know, 2021, […] the growth rates are accelerating, but they’re still far below what we were seeing at that time. And so we don’t create the same issue of customers having to digest very large increases multiple years in a row.

We’ve successfully expanded quota capacity, the geography of it, and essentially that’s, as we talked about last quarter, providing returns.

the business overall is growing at the same rate. If you exclude that customer, as I said. And all the business has been accelerating overall

now we’ve actually separated the agent from our SIEM so customers can use it with other SIEMs. And we do that because the agent performs just so well and it’s been such a differentiator when we pitch the SIEM that we think we’re limiting ourselves market-wise if we just go after customers that want to replatform their SIEM and it can have a much broader appeal as an AI SOC.