Summary

Wuhr AI Ops simplifies Linux server and Kubernetes cluster management via natural language, targeting operations teams. It offers a unified, AI-driven platform for automating tasks, monitoring infrastructure, and streamlining deployments, enhancing operational efficiency.

How It Works

The platform integrates multimodal AI models (GPT-4o, Gemini) for natural language command execution, intelligently switching between Linux and Kubernetes contexts. It features real-time monitoring (ELK, Grafana), CI/CD management, and RBAC, all orchestrated through a unified remote execution framework.

Quick Start & Requirements

• Requirements: Linux/macOS, Node.js >= 18.0.0, npm >= 8.0.0, Docker >= 20.10.0, Docker Compose >= 2.0.0, 4GB RAM, 20GB disk.
• Installation: Clone (git clone https://github.com/st-lzh/Wuhr-AI-ops.git), cd wuhr-AI-ops, then run ./install-docker.sh for one-click Docker deployment.
• Demo: https://aiops.wuhrai.com
• Video Guide: https://www.bilibili.com/video/BV11vyWBQEDV/

Highlighted Details

• AI Assistant: Supports GPT-4o, Gemini, deepseek; intelligent Linux/K8s command switching; command approval/risk detection; execution visualization; custom script execution (Python, Shell, Node.js); MCP tool integration.
• CI/CD: Visual pipeline configuration, Jenkins integration, multi-environment deployment, approval workflows, rollback.
• Monitoring: Integrates ELK for logs and Grafana for performance metrics.
• Security: RBAC, user approval, audit logs, command execution confirmation.

Maintenance & Community

Maintained by st-lzh. Support via GitHub Issues/Discussions. Active development indicated by recent updates (v2.0.0, v2.1.0).

Licensing & Compatibility

"MIT License (Modified)". Free for personal learning, non-commercial, and educational use. Commercial use, redistribution, and derivative works require explicit author authorization. Attribution is mandatory.

Limitations & Caveats

Commercial use and redistribution are restricted and require direct author permission. The "Modified" MIT license necessitates careful review for commercial adoption.