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

```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.