Engineering teams spend much of their incident response time investigating the problem and coordinating the response. Both tasks become harder when telemetry data lives in one place, deployment history is stored in another, and conversations unfold across chat channels and incident bridges. Responders often spend the first part of an incident rebuilding context before they can begin testing hypotheses and working toward resolution.
Datadog Incident Response includes three new AI-powered capabilities that help teams investigate incidents and coordinate responses more effectively without leaving their existing workflows. In this post, we’ll explore how you can:
Diagnose root causes with Bits Investigation as an active AI responderCatch up on active incidents with AI-generated chat summariesCapture bridge discussions in a unified incident timeline
Diagnose root causes with Bits Investigation as an active AI responder
AI can help responders investigate incidents, but the quality of an investigation depends on the context available to the AI. When telemetry data, deployment history, ownership information, and incident activity are spread across different systems, AI tools often have to fill gaps with assumptions. Those assumptions can send responders down the wrong path and prolong an incident.
