Experiments

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LLM Observability, Experiment view. Heading: 'Comparing 12 experiments across 9 fields'. Line graph visualization charting the accuracy, correctness, duration, estimated cost, and other metrics of various experiments.

LLM Observability Experiments supports the entire lifecycle of building LLM applications and agents. It helps you understand how changes to prompts, models, providers, or system architecture affect performance. With this feature, you can:

  • Create and version datasets
  • Run and manage experiments
  • Compare results to evaluate impact

Cookbooks

For in-depth examples of what you can do with LLM Experiments, see Datadog’s provided Jupyter notebooks.

Further reading

Documentation, liens et articles supplémentaires utiles:

Set up and use LLM Observability ExperimentsDOCUMENTATION more more Create and monitor LLM experiments with DatadogBLOG more more Datadog LLM Observability natively supports OpenTelemetry GenAI Semantic ConventionsBLOG more more Driving AI ROI: How Datadog connects cost, performance, and infrastructure so you can scale responsiblyBLOG more more