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OpenSRE is an open-source framework for building AI SRE agents that investigate production incidents using your existing observability stack, cloud context, and runbooks. It connects to 60+ integrations, runs a structured RCA pipeline, and delivers findings to Slack, local files, or your messaging channel of choice.
Install OpenSRE, run onboarding, then investigate a sample alert:
See the full walkthrough in Quickstart.
Yes. Deploy the gateway as a FastAPI app using the repo Dockerfile or your host’s Python workflow. Set LLM_PROVIDER and the matching provider key (for example ANTHROPIC_API_KEY when LLM_PROVIDER=anthropic). See Deployment and Environment variables.
OpenSRE supports Anthropic, OpenAI, OpenRouter, Gemini, Bedrock, Azure OpenAI, and CLI-backed providers via LLM_PROVIDER plus the matching API key. Full provider matrix, defaults, and troubleshooting: LLM providers.
Usually yes. OpenSRE integrates with observability (Datadog, Grafana, Sentry), cloud (AWS, Kubernetes), incident tools (PagerDuty, OpsGenie), databases, and messaging (Slack, Telegram). Browse the Integrations overview catalog and run opensre integrations verify after setup.
Running opensre starts the interactive incident-response shell. Describe issues in plain language, stream investigations live, and ask follow-up questions in the same session. Slash commands (/help, /investigate, /verify datadog) are documented in Interactive Shell Commands.
OpenSRE supports reversible masking before external LLM calls and command-history redaction via Interactive Shell Privacy. Anonymous product telemetry can be disabled with OPENSRE_NO_TELEMETRY=1. For vulnerability reports, email support@opensre.com.