quantumtaskai-caprover/CAPROVER_MONITORING_SETUP.md

CapRover Monitoring and Logging Optimization

1. Enhanced Logging Configuration

Django Logging (Already Optimized)

Your current logging setup in settings.py is good. Additional optimizations:

# Add to settings.py
LOGGING_LEVEL = config('LOGGING_LEVEL', default='INFO')

# Performance monitoring
PERFORMANCE_MONITORING = {
    'SLOW_QUERY_THRESHOLD': 1.0,  # Log queries slower than 1 second
    'MEMORY_THRESHOLD': 100,       # MB
}

2. Application Performance Monitoring (APM)

Option A: Django Debug Toolbar (Development)

Already configured for DEBUG=True environments.

Option B: Simple Performance Middleware

Add custom middleware for production monitoring:

# In core/middleware.py
class PerformanceMonitoringMiddleware:
    def __init__(self, get_response):
        self.get_response = get_response

    def __call__(self, request):
        import time
        start_time = time.time()
        
        response = self.get_response(request)
        
        duration = time.time() - start_time
        if duration > 2.0:  # Log slow requests
            logger.warning(f"Slow request: {request.path} took {duration:.2f}s")
        
        response['X-Response-Time'] = f"{duration:.3f}"
        return response

3. CapRover Native Monitoring

Enable App Monitoring

1. CapRover Dashboard → Apps → quantumtaskai → App Configs
2. Enable: "Log Rotation"
3. Set: "Max Log Size" to 100MB
4. Set: "Max Files" to 5

Resource Limits

# In captain-definition (advanced)
{
  "schemaVersion": 2,
  "dockerfilePath": "./Dockerfile.captain",
  "containerHttpPort": 80,
  "resources": {
    "memory": "512m",
    "cpu": "0.5"
  }
}

4. External Monitoring Options

Option A: Netdata (Lightweight)

1. One-Click Apps → Search "Netdata"
2. Deploy with default settings
3. Access: Monitor system resources in real-time

Option B: Grafana + Prometheus (Advanced)

1. Deploy Prometheus from One-Click Apps
2. Deploy Grafana from One-Click Apps
3. Configure Django metrics export

5. Health Checks and Uptime Monitoring

Application Health Endpoint

Create a health check endpoint in Django:

# In core/views.py
from django.http import JsonResponse
from django.core.cache import cache
from django.db import connection

def health_check(request):
    """Application health check endpoint"""
    try:
        # Test database
        with connection.cursor() as cursor:
            cursor.execute("SELECT 1")
        
        # Test Redis
        cache.set('health_check', 'ok', 10)
        cache_status = cache.get('health_check') == 'ok'
        
        return JsonResponse({
            'status': 'healthy',
            'database': 'ok',
            'cache': 'ok' if cache_status else 'error',
            'timestamp': timezone.now().isoformat()
        })
    except Exception as e:
        return JsonResponse({
            'status': 'unhealthy',
            'error': str(e)
        }, status=500)

External Uptime Monitoring

• UptimeRobot (Free tier available)
• Pingdom
• StatusCake

Monitor: https://quantumtaskai.captain.your-domain.com/health/

6. Log Analysis

Centralized Logging (Optional)

1. Deploy ELK Stack (Elasticsearch, Logstash, Kibana)
2. Configure Django to send logs to Logstash
3. Analyze logs in Kibana dashboard

Simple Log Analysis

# Monitor application logs
docker logs -f [container-id]

# Search for errors
docker logs [container-id] 2>&1 | grep -i error

# Monitor performance
docker logs [container-id] 2>&1 | grep "Slow request"

7. Alerts and Notifications

Webhook Notifications

Set up webhooks for critical alerts:

• High memory usage
• Database connection failures
• Application errors
• Long response times

Email Notifications

Configure Django to send email alerts for critical issues using your existing email setup.