Bits AI Enables Users to Query Observability Data in Natural Language

Bits AI enables you to use natural language to make complex queries and get synthesized insights from across your entire stack. Bits AI guides end-to-end incident response by aiding investigation, facilitating cross-team collaboration, directing you to AI-suggested code fixes, and pulling up internal documentation to help responders align with your organization’s best practices. You can also ask Bits AI to help create Synthetic tests and trigger automated workflows to remediate security threats.

Query your observability data using natural language

Use conversational language to ask about all of your data, including metrics, traces, logs, cloud cost, security, and real user sessions—no more battling syntax errors
Investigate issues faster with Watchdog anomalies, alerts, incidents, faulty deployments, and more—all packaged together, to help you pinpoint the root cause
Access Bits AI wherever you’re working—on mobile, web, or Slack

Bits AI surfaces observability data, incidents, triggered alerts, and other ongoing issues from conversational prompts

Streamline incident management

Bits AI helps you declare incidents and page on-call responders
Keep everyone up to speed with automatically generated summaries and status updates
Automate housekeeping—Bits AI helps you fill in incident details, adjust the incident severity, and write the first draft of a postmortem

Bits AI helps you manage incidents by generating summaries, calibrating incident severity, drafting postmortems, and more

Remediate issues faster

Ask Bits AI to recommend and trigger Datadog workflows to automatically remediate critical issues
Quickly retrieve Confluence runbooks and other internal documentation to resolve issues faster and scale your organization’s best practices
Bits AI identifies business-critical user journeys based on RUM data and helps you create Synthetic tests to proactively monitor your applications

Improve developer productivity with code-level fixes

Diagnose errors with concise explanations generated based on rich executional context gathered by APM and Error Tracking
Resolve bugs faster in production with automatically generated code fix suggestions and unit tests
Catch and fix code quality issues before merging with suggested code fixes from Datadog Static Analysis

Datadog Error Tracking features AI-generated code fix suggestions and test cases to help engineers debug faster