LLM tracing

LLM tracing captures the full execution path of AI requests (prompts, tool calls, and generations) for debugging, performance optimization, and cost analysis.

LLM tracing is your essential observability layer for GenAI applications: it maps the entire request lifecycle, from initial prompt to final response, using structured spans (OpenTelemetry standard). This granular visibility is critical for debugging complex agent workflows (LangChain, LlamaIndex) and identifying bottlenecks. You get immediate, actionable metrics: track token-level usage for cost control, pinpoint latency spikes across retrieval-augmented generation (RAG) steps, and save production traces for robust evaluation and fine-tuning. Implement tracing now to move your LLM app from prototype to reliable, cost-efficient production.

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