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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.

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Key Features

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Comprehensive Tracing

• End-to-end request tracking
• Nested span support for complex operations
• Detailed timing and performance metrics
• Error tracking and debugging

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AI-Specific Instrumentation

• Automatic tracing of LLM calls
• Model performance monitoring
• Token usage tracking
• Response quality metrics

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Integration Flexibility

• TypeScript and Python SDK support
• OpenTelemetry compatibility
• Custom span creation
• Attribute management

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Debugging Tools

• Visual trace exploration
• Error analysis
• Performance optimization
• Usage patterns

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Core Concepts

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Spans

Spans represent individual operations in your application:

• Operation timing and duration
• Context and attributes
• Error tracking
• Parent-child relationships

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Traces

Traces show the complete flow of a request:

• End-to-end request tracking
• Nested operation visualization
• Performance analysis
• Error correlation

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Attributes

Add context to your traces:

• Custom metadata
• Performance metrics
• Error details
• Operation parameters

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Error Handling

Track and debug issues:

• Exception recording
• Error status tracking
• Stack trace capture
• Error correlation

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Next Steps

• TypeScript Quick Start
• Python Quick Start