# Health Check System Implementation Summary ## What Was Implemented ### 1. Core Health Check Module (`cognee/api/health.py`) - **HealthChecker class**: Comprehensive health checking system - **Pydantic models**: Structured response models for health data - **Component checkers**: Individual health check methods for each backend service - **Status determination logic**: Proper classification of healthy/degraded/unhealthy states ### 2. Enhanced API Endpoints (`cognee/api/client.py`) - **`GET /health`**: Basic liveness probe (replaces existing basic endpoint) - **`GET /health/ready`**: Kubernetes readiness probe - **`GET /health/detailed`**: Comprehensive health status with component details ### 3. Backend Component Health Checks #### Critical Services (Failure = HTTP 503) - **Relational Database**: SQLite/PostgreSQL connectivity and session validation - **Vector Database**: LanceDB/Qdrant/PGVector/ChromaDB connectivity and index access - **Graph Database**: Kuzu/Neo4j/FalkorDB/Memgraph connectivity and schema validation - **File Storage**: Local filesystem/S3 accessibility and permissions #### Non-Critical Services (Failure = Degraded Status) - **LLM Provider**: OpenAI/Ollama/Anthropic/Gemini configuration validation - **Embedding Service**: Embedding engine accessibility check ## Key Features ### 1. Production-Ready Design - Proper HTTP status codes (200 for healthy/degraded, 503 for unhealthy) - Structured JSON responses with detailed component information - Response time tracking for performance monitoring - Graceful error handling and detailed error messages ### 2. Container Orchestration Support - Kubernetes-compatible liveness and readiness probes - Docker health check support - Proper startup and runtime health validation ### 3. Monitoring Integration - Detailed component status for observability platforms - Performance metrics (response times) - Version and uptime information - Structured logging for troubleshooting ### 4. Robust Error Handling - Individual component failures don't crash the health system - Detailed error messages for troubleshooting - Timeout handling and performance tracking - Graceful degradation for non-critical services ## Response Format Example ```json { "status": "healthy", "timestamp": "2024-01-15T10:30:45Z", "version": "1.0.0-local", "uptime": 3600, "components": { "relational_db": { "status": "healthy", "provider": "sqlite", "response_time_ms": 45, "details": "Connection successful" }, "vector_db": { "status": "healthy", "provider": "lancedb", "response_time_ms": 120, "details": "Index accessible" }, "graph_db": { "status": "healthy", "provider": "kuzu", "response_time_ms": 89, "details": "Schema validated" }, "file_storage": { "status": "healthy", "provider": "local", "response_time_ms": 156, "details": "Storage accessible" }, "llm_provider": { "status": "healthy", "provider": "openai", "response_time_ms": 25, "details": "Configuration valid" }, "embedding_service": { "status": "healthy", "provider": "configured", "response_time_ms": 30, "details": "Embedding engine accessible" } } } ``` ## Files Created/Modified ### New Files 1. `cognee/api/health.py` - Core health check system 2. `examples/health_check_example.py` - Usage examples and monitoring script 3. `HEALTH_CHECK_IMPLEMENTATION.md` - Detailed documentation 4. `HEALTH_CHECK_SUMMARY.md` - This summary file ### Modified Files 1. `cognee/api/client.py` - Enhanced with new health endpoints ## Usage Examples ### Basic Health Check ```bash curl http://localhost:8000/health # Returns: HTTP 200 (healthy/degraded) or 503 (unhealthy) ``` ### Readiness Check ```bash curl http://localhost:8000/health/ready # Returns: {"status": "ready"} or {"status": "not ready", "reason": "..."} ``` ### Detailed Health Status ```bash curl http://localhost:8000/health/detailed # Returns: Complete health status with component details ``` ### Kubernetes Integration ```yaml livenessProbe: httpGet: path: /health port: 8000 readinessProbe: httpGet: path: /health/ready port: 8000 ``` ## Benefits Achieved 1. **Comprehensive Monitoring**: All critical backend services are monitored 2. **Production Ready**: Proper HTTP status codes and error handling 3. **Container Orchestration**: Kubernetes and Docker compatibility 4. **Observability**: Detailed metrics and status information 5. **Troubleshooting**: Clear error messages and component status 6. **Performance Tracking**: Response time metrics for each component 7. **Graceful Degradation**: Distinguishes critical vs non-critical failures ## Implementation Notes - Health checks are designed to be lightweight and fast - Critical service failures result in HTTP 503 (service unavailable) - Non-critical service failures result in degraded status but HTTP 200 - All health checks include proper error handling and timeout management - The system is extensible for adding new backend components This implementation provides a robust, enterprise-grade health check system that meets the requirements for production deployments, container orchestration, and comprehensive monitoring.