Error Handling and Logging Issues

[actuallyrizzn]

Error Handling and Logging Issues

Description

Insufficient error handling, logging, and monitoring that could make debugging and maintenance difficult.

Issues Found

1. Insufficient Error Handling

• Location: Throughout application
• Problem: Many functions lack proper error handling
• Risk: Unhandled exceptions, poor user experience
• Fix: Implement comprehensive error handling

2. Missing Structured Logging

• Location: Application-wide
• Problem: No structured logging implementation
• Risk: Difficult debugging, poor monitoring
• Fix: Implement structured logging with proper levels

3. No Error Monitoring

• Location: Production monitoring
• Problem: No error tracking system (Sentry, etc.)
• Risk: Unreported production errors
• Fix: Integrate error monitoring service

4. Missing Health Checks

• Location: Application endpoints
• Problem: No health check endpoints for monitoring
• Risk: No visibility into application health
• Fix: Implement health check endpoints

5. Inconsistent Error Responses

• Location: API endpoints
• Problem: Different error response formats across endpoints
• Risk: Confusing API behavior
• Fix: Standardize error response format

6. Missing Debug Information

• Location: Error pages and logs
• Problem: Insufficient debug information in production
• Risk: Difficult troubleshooting
• Fix: Add proper debug information (with security considerations)

Proposed Solutions

1. Comprehensive Error Handling:

   from functools import wraps
   
   def handle_errors(f):
       @wraps(f)
       def decorated_function(*args, **kwargs):
           try:
               return f(*args, **kwargs)
           except Exception as e:
               logger.error(f"Error in {f.__name__}: {str(e)}")
               return jsonify({'error': 'Internal server error'}), 500
       return decorated_function

2. Structured Logging:

   import logging
   import json
   
   class JSONFormatter(logging.Formatter):
       def format(self, record):
           log_entry = {
               'timestamp': self.formatTime(record),
               'level': record.levelname,
               'message': record.getMessage(),
               'module': record.module,
               'function': record.funcName
           }
           return json.dumps(log_entry)
   
   logger = logging.getLogger(__name__)
   handler = logging.StreamHandler()
   handler.setFormatter(JSONFormatter())
   logger.addHandler(handler)

3. Error Monitoring:

   from sentry_sdk.integrations.flask import FlaskIntegration
   import sentry_sdk
   
   sentry_sdk.init(
       dsn="YOUR_SENTRY_DSN",
       integrations=[FlaskIntegration()],
       traces_sample_rate=1.0
   )

4. Health Check Endpoints:

   @app.route('/health')
   def health_check():
       try:
           # Check database connection
           db.session.execute('SELECT 1')
           return jsonify({'status': 'healthy'}), 200
       except Exception as e:
           return jsonify({'status': 'unhealthy', 'error': str(e)}), 503

5. Standardized Error Responses:

   def error_response(message, status_code=400, error_code=None):
       response = {
           'error': message,
           'status_code': status_code
       }
       if error_code:
           response['error_code'] = error_code
       return jsonify(response), status_code

6. Debug Information:

   @app.errorhandler(500)
   def internal_error(error):
       if app.debug:
           return jsonify({
               'error': 'Internal server error',
               'debug_info': str(error)
           }), 500
       return jsonify({'error': 'Internal server error'}), 500

Priority

HIGH - Critical for production monitoring and debugging.

Labels

error-handling, logging, monitoring, high-priority