Operations | Monitoring | ITSM | DevOps | Cloud

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.

Join Datadog's Chief Product Officer Yanbing Li and OpenAI's Member of Product Staff Alexander Embiricos as they discuss emerging technologies and innovation, how they impact businesses today, and the new opportunities they create for you.

Automate Slack support questions with Datadog Workflow Automation and Bits AI Agent Builder. Datadog Workflow Automation can now trigger directly from messages posted in Slack. In this quick demo, Yuta Yoshida, Product Manager at Datadog, shows how to build an automated support workflow that: → Detects new support questions in a Slack channel→ Sends questions to a custom agent built with Bits AI Agent Builder→ Replies directly in the Slack thread with an answer and relevant documentation.

See how Datadog Journey Monitoring brings together user behavior, real-user insights, and proactive testing to track the health of critical user journeys, understand business impact, and quickly troubleshoot issues.

Modal is an AI infrastructure company rebuilding the cloud for AI, giving developers easy access to the compute needed to build and scale AI applications without managing the underlying complexity. Operating across more than 20 cloud providers and launching approximately 26 million containers daily, Modal relies on Datadog to unify observability across its infrastructure, applications, networking, and CI—helping its engineers detect 99% of incidents within five minutes, resolve 96% of issues before customer impact, and confidently scale one of the world’s most complex AI platforms.

Engineering ships faster than ever with AI writing more of the code, but test coverage has to keep pace, or users find the broken flows first.