django-jaeger-middleware-plus 0.1.4

A Django middleware for distributed tracing with Jaeger

Django Distributed Tracing

A comprehensive Django middleware package for distributed tracing with Jaeger, supporting HTTP requests, Database queries, Redis operations, Celery tasks, and RocketMQ messaging.

I read Jaeger - Distributed Tracing System on github and make it plus.

Features

• HTTP Request Tracing: Automatic tracing of incoming HTTP requests and outgoing HTTP calls
• Database Query Tracing: Track Django ORM queries with performance metrics
• Redis Operation Tracing: Monitor Redis commands and operations
• Celery Task Tracing: Distributed tracing across Celery task queues
• RocketMQ Message Tracing: Trace message production and consumption
• Configurable Components: Enable/disable specific tracing components
• Performance Monitoring: Track slow queries, long-running requests, and bottlenecks
• Error Tracking: Automatic error logging and span tagging

Installation

pip install django-jaeger-middleware-plus

Quick Start

1. Add to Django Settings

# settings.py

INSTALLED_APPS = [
    # ... other apps
    'jaegertrace',
]

MIDDLEWARE = [
    'jaegertrace.middleware.TraceMiddleware',
    # ... other middleware
]

# Required: Service name for tracing
TRACING_SERVICE_NAME = "my-django-service"

Configuration Reference

Tracer Configuration

TRACER_CONFIG = {
    "sampler": {
        "type": "const",        # const, probabilistic, rate_limiting
        "param": 1,             # Sample rate (0.0 to 1.0)
    },
    "local_agent": {
        "reporting_host": "localhost",
        "reporting_port": 6832,
    },
    "trace_id_header": "trace-id",
    "baggage_header_prefix": "jaeger-",
    "logging": True,
    "metrics": False,
}

Component Configuration

# settings.py

TRACING_CONFIG = {
    "http_requests": {
        "enabled": True,
        "trace_headers": True,  # Inject tracing headers
        "ignore_urls": ["/health", "/metrics", "/favicon.ico"],  # URLs to skip
        "max_tag_value_length": 1024,  # Max length for tag values, default 1024
    },
    "database": {
        "enabled": True,
        "slow_query_threshold": 100,  # Milliseconds
        "log_sql": True,  # Include SQL in spans
        "ignore_sqls": ["SHOW TABLES", "DESCRIBE"],  # SQL commands to skip, default ["SHOW TABLES", "DESCRIBE"]
        "max_query_length": 1000,  # Truncate long queries, default 1000
    },
    "redis": {
        "enabled": True,
        "log_command": True,  # Include command in spans
        "ignore_commands": ["PING", "INFO"],  # Redis commands to skip
        "max_command_length": 500,  # Truncate long commands, default 500
    },
    "celery": {
        "enabled": True,
        "ignore_tasks": [],  # Celery tasks to skip
    },
    "rocketmq": {
        "enabled": True,
        "trace_message_body": False,  # Include message content
        "ignore_topics": [],  # RocketMQ topics to skip
    },
}

Usage

1. Using the Traced HTTP Client

from jaegertrace.httpclient import HttpClient

# Create a traced HTTP client
client = HttpClient()

# Make requests - automatically traced
response = client.get("/users/123")
response = client.post("/users", json={"name": "John"})

Production Considerations

Sampling

In production, consider using probabilistic sampling to reduce overhead:

TRACER_CONFIG = {
    "sampler": {
        "type": "probabilistic",
        "param": 0.1,  # Sample 10% of traces
    }
}

Performance Impact

• Database query tracing adds minimal overhead (~1-2ms per query)
• HTTP request tracing adds ~5-10ms per request
• Redis tracing adds ~1ms per operation
• Consider disabling SQL logging in production

Resource Usage

• Each span consumes ~1KB of memory
• Jaeger agent buffers traces locally before sending
• Monitor memory usage with high-throughput applications

Troubleshooting

Common Issues

1. Traces not appearing in Jaeger

   • Check Jaeger agent connectivity
   • Verify sampling configuration
   • Check service name configuration

2. High memory usage

   • Reduce sampling rate
   • Disable detailed logging (SQL, message bodies)
   • Check for span leaks (unfinished spans)

3. Performance degradation

   • Tune slow query thresholds
   • Disable non-essential component tracing
   • Use asynchronous reporting

Debug Mode

Enable debug logging to troubleshoot issues:

# settings.py

LOGGING = {
    'loggers': {
        'django_tracing': {
            'handlers': ['console'],
            'level': 'DEBUG',
            'propagate': False,
        },
    },
}

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

Email me with any questions: [e-mail].