cerberus-django 0.1.4

Django middleware for capturing and streaming HTTP request metrics via WebSocket

Cerberus Django

A Django middleware for capturing and streaming HTTP request metrics to a backend analytics server via WebSocket. Designed for high-performance, non-blocking operation in both WSGI and ASGI environments.

Features

• Non-blocking: Events are queued and sent asynchronously via a background thread
• WSGI & ASGI Compatible: Works with both synchronous and asynchronous Django deployments
• Privacy-First: Built-in HMAC-SHA256 hashing for PII (IP addresses) before transmission
• Custom Metrics: Attach application-specific metrics to any request
• Automatic Reconnection: WebSocket client handles connection failures gracefully
• Zero Configuration Required: Sensible defaults with optional customization

Installation

pip install cerberus-django

Quick Start

1. Add to Django Settings

# settings.py

INSTALLED_APPS = [
    # ... your apps
]

MIDDLEWARE = [
    'django.middleware.security.SecurityMiddleware',
    # ... other middleware
    'cerberus_django.CerberusMiddleware',  # Add Cerberus
]

# Cerberus Configuration
CERBERUS_CONFIG = {
    'ws_url': 'wss://your-analytics-server.com/ws/events',
    'token': 'your-api-key',
    'client_id': 'your-client-id',
}

2. That's It!

Cerberus will now capture metrics for every HTTP request and send them to your analytics backend.

Configuration

All configuration is done via the CERBERUS_CONFIG dictionary in your Django settings:

Key	Required	Description
ws_url	Yes	WebSocket URL for the analytics backend
token	Yes	API key for authentication
client_id	Yes	Unique identifier for your application
backend_url	No	HTTP URL to auto-fetch the HMAC secret key
secret_key	No	HMAC secret key for PII hashing (auto-fetched if backend_url is set)

Example Configurations

Basic (no PII hashing):

CERBERUS_CONFIG = {
    'ws_url': 'wss://analytics.example.com/ws/events',
    'token': 'sk-your-api-key',
    'client_id': 'my-django-app',
}

With automatic secret key fetching:

CERBERUS_CONFIG = {
    'ws_url': 'wss://analytics.example.com/ws/events',
    'token': 'sk-your-api-key',
    'client_id': 'my-django-app',
    'backend_url': 'https://analytics.example.com',  # Will fetch secret from /api/secret-key
}

With manual secret key:

CERBERUS_CONFIG = {
    'ws_url': 'wss://analytics.example.com/ws/events',
    'token': 'sk-your-api-key',
    'client_id': 'my-django-app',
    'secret_key': 'your-hmac-secret-key',  # For consistent PII hashing
}

Custom Metrics

Attach custom metrics to any request by adding them to the response:

from rest_framework.decorators import api_view
from rest_framework.response import Response

@api_view(['GET'])
def my_endpoint(request):
    # Your business logic
    items = process_items()

    response = Response({'items': items})

    # Add custom metrics (will be included in the event)
    response.data['_cerberus_metrics'] = {
        'items_processed': len(items),
        'cache_hit': True,
        'processing_time_ms': 42,
    }

    return response

The _cerberus_metrics key is automatically extracted from the response and included in the event payload. It will not be sent to the client.

Event Payload

Each event sent to your analytics backend includes:

{
    "api_key": "your-api-key",
    "client_id": "your-client-id",
    "token": "your-api-key",
    "source_ip": "hashed-ip-address",
    "endpoint": "/api/users/",
    "scheme": true,
    "method": "GET",
    "custom_data": {
        "items_processed": 10,
        "cache_hit": true
    }
}

Privacy & Security

PII Hashing

When a secret_key is configured, source IP addresses are hashed using HMAC-SHA256 before transmission:

• Consistent: Same IP always produces the same hash (enabling analytics)
• Irreversible: Original IP cannot be recovered from the hash
• Secure: Uses cryptographically strong HMAC-SHA256

What's Captured

Field	Description	Privacy
source_ip	Client IP address	Hashed if secret_key configured
endpoint	Request path	Sent as-is
method	HTTP method (GET, POST, etc.)	Sent as-is
scheme	Whether HTTPS was used	Sent as-is
custom_data	Your custom metrics	Sent as-is

What's NOT Captured

• Request/response bodies
• HTTP headers
• Query parameters
• Cookies or session data
• Authentication tokens

Debug Mode

Enable debug logging to troubleshoot issues:

export CERBERUS_DEBUG=true

Or in your Django settings:

import os
os.environ['CERBERUS_DEBUG'] = 'true'

This will log:

• Middleware initialization
• WebSocket connection attempts
• Events being queued and sent
• Any errors encountered

Architecture

┌─────────────────────────┐     ┌──────────────────────────────┐
│   Django Request        │     │   Background Thread          │
│   (WSGI or ASGI)        │     │   (Daemon)                   │
├─────────────────────────┤     ├──────────────────────────────┤
│ CerberusMiddleware      │     │  Event Loop                  │
│   └── queue.put(event)  │────▶│    └── WebSocket.send()     │
└─────────────────────────┘     └──────────────────────────────┘
         │                                    │
         │  Thread-safe Queue                 │  Async WebSocket
         └────────────────────────────────────┘

• Middleware: Runs synchronously in the request/response cycle
• Queue: Thread-safe queue.Queue for passing events
• Background Thread: Daemon thread with its own event loop for async WebSocket communication

This architecture ensures:

• No blocking of HTTP requests
• No event loop conflicts in WSGI mode
• Automatic cleanup when the process exits (daemon thread)

Requirements

• Python 3.9+
• Django 4.0+
• websockets 12.0+
• requests 2.28+

Development

# Clone the repository
git clone https://github.com/gpotrock/cerberus.git
cd cerberus

# Install development dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/
ruff check src/ --fix

# Type checking
mypy src/

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request