Tracing
Overview
Learn about Autoblocks Tracing and how it helps you monitor and debug your AI applications.
Tracing Overview
Autoblocks Tracing provides powerful observability for your AI applications, helping you understand and debug complex AI workflows. It integrates with OpenTelemetry to provide detailed insights into your application’s behavior.Key Features
Comprehensive Tracing
- End-to-end request tracking
- Nested span support for complex operations
- Detailed timing and performance metrics
- Error tracking and debugging
AI-Specific Instrumentation
- Automatic tracing of LLM calls
- Model performance monitoring
- Token usage tracking
- Response quality metrics
Integration Flexibility
- TypeScript and Python SDK support
- OpenTelemetry compatibility
- Custom span creation
- Attribute management
Debugging Tools
- Visual trace exploration
- Error analysis
- Performance optimization
- Usage patterns
Core Concepts
Spans
Spans represent individual operations in your application:- Operation timing and duration
- Context and attributes
- Error tracking
- Parent-child relationships
Traces
Traces show the complete flow of a request:- End-to-end request tracking
- Nested operation visualization
- Performance analysis
- Error correlation
Attributes
Add context to your traces:- Custom metadata
- Performance metrics
- Error details
- Operation parameters
Error Handling
Track and debug issues:- Exception recording
- Error status tracking
- Stack trace capture
- Error correlation