phoenix-observability

LLM observability is enabled by collecting OpenTelemetry-based traces across your LLM framework to debug pipelines and monitor production latency. This platform supports self-hosted deployment using PostgreSQL or SQLite to capture and evaluate system traces.

You can evaluate LLM outputs using LLM-as-judge evaluators for quality assessment alongside versioned test datasets. This enables regression testing and allows you to compare prompts, models, and configurations through structured experiments.

OpenTelemetry tracing for LLM systems is used to collect end-to-end visibility into application pipelines for debugging and auditing. It captures execution paths across any LLM framework to help verify model behavior and monitor production reliability.

A self-hosted database is required to run this observability platform, with support for either PostgreSQL or SQLite. This open-source deployment model ensures you maintain full control over tracing data and evaluation datasets locally.

Debug LLM pipelines by analyzing collected OpenTelemetry traces to identify latency bottlenecks and audit model behavior. The platform provides interactive playground testing and versioned datasets to isolate performance issues across configurations.

The best way to compare prompts and models is by running structured experiments against versioned datasets to measure quality differences. Interactive playground testing further allows simultaneous evaluation across multiple models to optimize configurations.