# Tracer-Cloud/opensre

Build your own AI SRE agents. The open source toolkit for the AI era.

Repository: https://github.com/Tracer-Cloud/opensre
Canonical: https://ross.abutalabs.com/products/opensre
Homepage: https://discord.com/invite/opensre
Language: Python
License: Apache-2.0
License Family: permissive
Topics: ai-sre, alerting, datadog, grafana, observability, remediation, root-cause-analysis, site-reliability-engineering, slack, sre, incident-management
Last push: 2026-08-27T00:08:07+00:00

## Health v2 (maintenance only)
Score: 78/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 16
- inputs: {"age_days": 233, "days_push": 7, "days_rel": 7, "gap_med": 1.0, "n_releases_24m": 139}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10939, forks 1592 (observed 2026-08-28T04:10:44.739546+00:00)

## What it is
OpenSRE is an open-source Python framework for building AI SRE agents that investigate incidents and perform root cause analysis on your infrastructure. It integrates with 60+ existing tools like Slack, Grafana, and Datadog, and provides a training and evaluation environment for the agents.

## Use cases
- automate incident investigation and root cause analysis
- build custom AI SRE agents for my infrastructure
- analyze alerts from Slack, Grafana, and Datadog automatically
- triage on-call alerts with an LLM agent
- evaluate and train AI agents on incident response workflows
- automate remediation of production incidents

## When to choose
- you want an open-source, self-hosted alternative to commercial AI SRE tools
- your team already uses Grafana, Datadog, or Slack and wants automated incident triage
- you need to build custom SRE workflows with LLM agents and your own tooling
- you want to experiment with agent-based root cause analysis in a public-alpha toolkit

## When to avoid
- you need a fully stable, production-hardened product - it is in public alpha with evolving APIs
- you want a turnkey SaaS incident management platform rather than a build-your-own framework
- your observability stack is not among the supported integrations
- you cannot run LLM inference or send infrastructure data to models

## Facets
- artifact type: framework
- maturity: experimental
- function: agent-framework, alerting, monitoring, llm-inference, workflow-automation, developer-tools
- domain: monitoring, large-language-models, self-hosted
- platform: python, self-hosted, cli
- tags: ai-sre, incident-management, root-cause-analysis, observability, site-reliability-engineering, remediation, datadog, grafana, slack, public-alpha, devops, ai-agents, automation, docker

## Member repositories
- Tracer-Cloud/opensre (main) score 78

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:44.739546+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:17:19.557212+00:00, confidence not recorded.
  - readme: https://github.com/Tracer-Cloud/opensre (fetched 2026-08-28T04:10:44.739546+00:00, sha 5c199503b876)
  - homepage: https://discord.com/invite/opensre (fetched 2026-08-29T08:16:03.034676+00:00, sha 98e58da39ac1)
  - registry_pypi: https://pypi.org/pypi/opensre/json (fetched 2026-08-29T08:16:03.044372+00:00, sha e4f23b87df33)
- Data as of 2026-08-30T08:39:29.467469+00:00.