opensre
OpenSRE is an open-source framework for building AI agents that help investigate production incidents using your infrastructure tools and workflows.
Share on XLicense: Apache-2.0
Overview
OpenSRE is an open-source framework for building AI agents for site reliability engineering and production incident response. It helps teams investigate failures when evidence is spread across logs, metrics, traces, runbooks, and Slack. Operators connect existing infrastructure tools, define workflows, and run agents on their own infrastructure. The project also provides end-to-end test scenarios and a training and evaluation environment for improving and assessing incident-response agents.
Key features
- Connect agents to existing infrastructure tools, including observability and incident-response services.
- Define workflows for production operations and incident response.
- Use end-to-end test scenarios and a training and evaluation environment for incident-response agents.
Best for
SRE and operations teams exploring AI-assisted production incident response with their own infrastructure and workflows. It is also suited to developers evaluating or improving incident-response agents.
- Upstream
- Tracer-Cloud/opensre
- Fork on GitHub
- Guo-astro/opensre
- Upstream stars
- 12k
- Category
- AI agents and LLM tools
- Language
- Python
- License
- Apache-2.0
- Forked
- 2026-10-10
- Sync status
- In syncLast synced 2026-10-11
More in AI agents and LLM tools
Hello-Agents is a tutorial for learning the principles and practice of AI agents. It guides readers from core concepts to building agent systems and applications.
Forked 2026-10-10Last synced 2026-10-11Custom license (see repository)AI agents and LLM toolsGitHub
Context Mode helps AI coding agents use less context and resume work after a conversation is compacted. It is used through MCP and hooks to handle tool output, session memory, and routing across supported platforms.
Forked 2026-10-10Last synced 2026-10-11Custom license (see repository)AI agents and LLM toolsGitHub
ARTEX is a self-hosted AI penetration testing system for exploring assets and reviewing test activity. It brings tasks, findings, asset data and approval steps into one interface.
Forked 2026-10-10Last synced 2026-10-11License: AGPL-3.0AI agents and LLM toolsGitHub
An open-source curriculum for learning AI engineering by implementing model internals, retrieval pipelines, and agent runtimes. Study through lessons, interactive labs, or staged coding projects, and inspect the code and evaluation results.
Forked 2026-10-09Last synced 2026-10-11License: MITAI agents and LLM toolsGitHub