LLM Proxy Debugging & Tracing
Master the art of debugging LLM proxy requests. Learn request inspection, response logging, error diagnosis, and performance analysis to build reliable AI-powered applications.
Debugging Tools
Essential tools for proxy troubleshooting
Request Inspector
View full request details including headers, body, and routing decisions.
Response Logger
Capture and analyze API responses with timing and token metrics.
Trace Viewer
Visualize request flow through proxy layers and providers.
Error Analyzer
Diagnose errors with stack traces and suggested fixes.
Performance Profiler
Identify bottlenecks and optimize proxy latency.
Request Replay
Replay failed requests for debugging and testing.
Request Tracing
Follow requests through the proxy pipeline
Logging Configuration
Set up comprehensive logging for debugging
Configure JSON-formatted logs for easy parsing and analysis in log aggregation systems.
logging: format: json level: debug output: stdout fields: - request_id - duration - tokens
Enable sampling for high-traffic proxies to reduce log volume while maintaining visibility.
sampling: enabled: true rate: 0.1 # 10% of requests errors: 1.0 # Log all errors slow_requests: 1.0
Common Error Patterns
Diagnose and fix frequent proxy issues
Timeout, connection refused, and network issues when connecting to AI providers.
Invalid API keys, expired tokens, and permission denied errors.
Provider rate limits exceeded. Configure backoff and retry strategies.
Invalid request format, missing parameters, or unsupported model names.
Master Proxy Debugging
Learn to diagnose and fix issues quickly with comprehensive debugging tools and best practices for LLM proxy operations.