The Deconstructed Database at Datadog - SRE Track

As Datadog scaled to handle over a hundred trillion daily events, our engineering teams built their own custom query engines to keep things fast. While this helped teams move quickly, it also created silos that made it tough to analyze data across different products. To keep growing and support AI, we had to find a way to bring these engines together using open standards without slowing anyone down or risking reliability.

In this session, Principal Engineer Julien Le Dem shares how Datadog turned its query engines into a more flexible, composable system. He’ll discuss how we’re defining clear contracts that improve performance and give teams autonomy, while breaking down those old silos. He’ll also walk through how we’re using and contributing to major open-source technologies to build it. You’ll walk away with insights on how you can use modern open standards to make your own purpose-built engines more flexible and resilient, even at a massive scale.