Tracer-Cloud/opensre

What it solves

OpenSRE provides a framework for building AI Site Reliability Engineering (SRE) agents that can automatically investigate and resolve production incidents. It addresses the difficulty of debugging distributed failures, where evidence is often scattered across logs, metrics, and traces, by providing a standardized environment for agentic incident response and training.

How it works

When an alert fires, the system follows a structured process:

1. Context Gathering: It fetches correlated logs, metrics, traces, and deployment history.
2. Privacy: It optionally masks sensitive identifiers before sending data to an LLM.
3. Reasoning: The agent uses a tool-calling loop to test hypotheses across connected systems.
4. Reporting: It generates a structured investigation report identifying the probable root cause with linked evidence.
5. Remediation: It suggests or executes next steps to fix the issue.
6. Notification: It posts summaries to communication tools like Slack or Telegram.

Who it’s for

This tool is designed for SREs, DevOps engineers, and developers who want to automate production debugging and root-cause analysis (RCA) using AI agents.

Highlights

• Extensive Integrations: Connects to over 60 tools across observability (Grafana, Datadog, Sentry), infrastructure (Kubernetes, AWS, GCP), and databases (PostgreSQL, MongoDB).
• Training & Evaluation: Includes synthetic incident simulations and end-to-end tests to benchmark and improve agent performance.
• Flexible LLM Support: Compatible with various providers including Anthropic, OpenAI, Gemini, and local models via Ollama.
• Runbook Awareness: The agent can read and apply existing runbooks automatically during investigations.