HolmesGPT/holmesgpt

SRE Agent - CNCF Sandbox Project

What it solves

HolmesGPT is an AI agent designed to automate the investigation of production incidents and the identification of root causes. It eliminates the need for manual troubleshooting by querying live observability data across diverse infrastructure stacks, including Kubernetes, VMs, cloud providers, and databases.

How it works

It employs an agentic loop to interact with various data sources (toolsets) to gather evidence. It can be run in an interactive mode for human-led investigations or in "Operator mode," where it runs 24/7 in the background to spot problems and alert users via Slack. It integrates with a wide range of LLM providers (OpenAI, Anthropic, Gemini, etc.) and can fetch alerts from systems like PagerDuty or Jira and write findings back to them.

Who it’s for

Site Reliability Engineers (SREs) and DevOps engineers who manage complex, multi-cloud or hybrid infrastructure and need to reduce the time spent on root cause analysis.

Highlights

  • Broad Integration Ecosystem: Built-in toolsets for Prometheus, Grafana, Datadog, Kubernetes, AWS, Azure, GCP, and many more.
  • Data Handling at Scale: Uses server-side filtering and JSON tree traversal to handle petabyte-scale data without overflowing LLM context windows.
  • Memory Safety: Implements per-tool memory limits and output budgeting to prevent OOM kills during large dataset queries.
  • Automated Remediation: Can open GitHub PRs to fix identified issues when using the GitHub integration.
  • Infrastructure Agnostic: Works with VMs, bare metal, and containers; Kubernetes is not required for the operation of the agent itself.

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