cognee/HEALTH_CHECK_SUMMARY.md

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

{
  "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

curl http://localhost:8000/health
# Returns: HTTP 200 (healthy/degraded) or 503 (unhealthy)

Readiness Check

curl http://localhost:8000/health/ready
# Returns: {"status": "ready"} or {"status": "not ready", "reason": "..."}

Detailed Health Status

curl http://localhost:8000/health/detailed
# Returns: Complete health status with component details

Kubernetes Integration

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.