k8sgpt-ai/k8sgpt

Giving Kubernetes Superpowers to everyone

What it solves

K8sGPT scans Kubernetes clusters to diagnose and triage issues, translating complex cluster errors into simple English explanations. It reduces the need for manual log diving and deep SRE expertise by codifying diagnostic patterns into analyzers.

How it works

K8sGPT uses a set of built-in analyzers (e.g., for Pods, Services, Ingress, and Nodes) to identify issues in a cluster. Once an issue is detected, the tool can send the relevant information to a configured LLM backend—such as OpenAI, Azure, Google Gemini, or local models—to generate a detailed explanation and recommendation for a fix. It also supports the Model Context Protocol (MCP) for integration with clients like Claude Desktop.

Who it’s for

It is designed for Kubernetes administrators, SREs, and developers who need to quickly identify and resolve cluster health issues without manually parsing through voluminous logs and status messages.

Highlights

  • Multi-Backend Support: Integrates with a wide range of AI providers including OpenAI, Cohere, Amazon Bedrock, Google Gemini, and local models via Ollama or LocalAI.
  • Anonymization: Masks sensitive data (like object names and labels) before sending payloads to public AI backends to protect cluster privacy.
  • Extensible Analyzers: Includes a comprehensive suite of built-in analyzers for most Kubernetes resources and allows users to write their own.
  • MCP Integration: Can be served as an MCP server, allowing AI assistants like Claude Desktop to directly analyze and query cluster health.

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