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Monitor\n\nAn agentic system that uses open-source AI agents to continuously monitor, diagnose, and report on Kubernetes cluster health.\n\n## Architecture\n\n```\n┌──────────────────────────────────────────────────┐\n│               Orchestrator Agent                  │\n│  (Aggregates findings, correlates issues,         │\n│   produces actionable recommendations)            │\n└──────────┬───────────┬────────────┬──────────────┘\n           │           │            │\n    ┌──────▼──┐  ┌─────▼────┐  ┌───▼───────────┐\n    │  Pod    │  │  Node    │  │  Log/Metric   │\n    │ Health  │  │ Health   │  │  Analyzer     │\n    │ Agent   │  │ Agent    │  │  Agent        │\n    └─────────┘  └──────────┘  └───────────────┘\n           │           │            │\n           └───────────┼────────────┘\n                       │\n            ┌──────────▼──────────┐\n            │  K8s API Server     │\n            │  + Metrics Server   │\n            └─────────────────────┘\n```\n\n## Tech Stack (100% Open Source)\n\n| Component       | Technology           | License     |\n|----------------|----------------------|-------------|\n| Agent Framework | CrewAI              | Apache 2.0  |\n| LLM            | Ollama (Llama 3.1)   | MIT         |\n| K8s Runtime    | Kind                 | Apache 2.0  |\n| Backend        | FastAPI              | MIT         |\n| Frontend       | React + Vite         | MIT         |\n| K8s Client     | kubernetes-python    | Apache 2.0  |\n\n## Prerequisites\n\n- Python 3.11+\n- Node.js 18+\n- Docker\n- Kind\n- Ollama (with llama3.1 model)\n- kubectl\n\n## Quick Start\n\n```bash\n# 1. Start Ollama and pull the model\nollama pull llama3.1\n\n# 2. Create Kind cluster\n./scripts/setup-kind.sh\n\n# 3. Deploy sample workloads\nkubectl apply -f k8s-manifests/\n\n# 4. Start backend\ncd backend\npip install -r requirements.txt\nuvicorn api.main:app --reload --port 8000\n\n# 5. Start frontend\ncd frontend\nnpm install\nnpm run dev\n```\n\n## Project Structure\n\n```\n├── backend/\n│   ├── agents/          # CrewAI agent definitions\n│   │   ├── pod_health.py\n│   │   ├── node_health.py\n│   │   ├── log_analyzer.py\n│   │   └── orchestrator.py\n│   ├── api/             # FastAPI endpoints\n│   │   ├── main.py\n│   │   └── websocket.py\n│   ├── k8s_client/      # Kubernetes API wrappers\n│   │   ├── pods.py\n│   │   ├── nodes.py\n│   │   ├── logs.py\n│   │   └── metrics.py\n│   └── models/          # Pydantic models\n│       └── schemas.py\n├── frontend/\n│   └── src/\n│       ├── components/  # React components\n│       ├── pages/       # Page views\n│       ├── services/    # API client\n│       └── hooks/       # Custom React hooks\n├── scripts/            # Setup and utility scripts\n├── k8s-manifests/       # Sample deployments for testing\n└── docker-compose.yml\n```\n\n## How It Works\n\n1. **Pod Health Agent** scans all pods for CrashLoopBackOff, OOMKills, image pull failures, and excessive restarts\n2. **Node Health Agent** checks node readiness, CPU/memory/disk pressure, and identifies cordoned nodes\n3. **Log/Metric Analyzer Agent** collects logs and metrics, detects anomalies and error patterns\n4. **Orchestrator Agent** receives reports from all agents, correlates findings, and produces a prioritized health report with recommendations\n\nAll agents run locally via Ollama — no data leaves your machine.","readmeExcerpt":"K8s Agent Watch — AI-Powered Kubernetes Cluster Health Monitor An agentic system that uses open-source AI agents to continuously monitor, diagnose, and report on Kubernetes cluster health. 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