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Trace Your Pipelines

Understand, analyze, and troubleshoot your AI pipelines using logging features and integrated services.

Tracing vs Debugging​

Tracing and debugging both help you understand how your pipeline runs, but they serve different purposes.

Tracing captures the full journey of a query — from the user's input through each processing step to the final result. A trace usually includes timestamps, the original query and its transformations, generated embeddings, retrieved documents, scoring and ranking decisions, as well as any errors or latency issues. Tracing shows how data flows through the system and when each step occurs, giving you a clear picture of what happened end to end. Tools like Langfuse or Weave make this information easy to visualize and explore.

Debugging is about getting to the root of problems. It involves analyzing detailed logs to pinpoint errors, misconfigurations, or unexpected behavior. While tracing shows you the "what" and "when," debugging helps you uncover the "why."

AI-powered applications are often complex and opaque, making it hard to understand what’s happening under the hood. When something goes wrong, tracing and debugging let you lift the veil. They’re essential for fixing issues, improving performance, and gaining insight into how your models behave. Whether you're tracking down high latency, investigating odd query results, or exploring search patterns, these tools give you the visibility you need to take action.

Tools for Debugging​

  • Pipeline logs: Capture operational details, such as the component that generated the log, log level, timestamp, and log message.
  • Pipeline debugger: Offers live component-level logs available from Pipeline Builder.
  • Remote debug with a VS Code tunnel.

Tools for Tracing​

Use integrated services to trace your deepset pipelines:

  • Langfuse: Provides deep tracing for application-level observability, including detailed spans, latency tracking, and cross-service dependencies.
  • Weights & Biases Weave: Captures ML-specific telemetry to help you track your pipeline's latency, token-count, and more.

Debug Your Pipelines​

See the following instructions, depending on how you want to debug:

  • Debug with logs
  • Debug remotely
  • Debug with Pipeline Builder

Trace Your Pipelines​