pydantic/logfire

AI observability platform for production LLM and agent systems.

What it solves

Logfire provides a way for developers to understand exactly how their Python applications are behaving in real-time. It solves the problem of "blind spots" in production by offering deep visibility into Python objects, event-loop telemetry, database queries, and code profiling, specifically tailored for the Python ecosystem.

How it works

Logfire acts as an opinionated wrapper around OpenTelemetry, supporting all its signals (traces, metrics, and logs). It allows developers to instrument their code either manually using spans and logging calls or automatically through integrations with popular Python packages like FastAPI. The collected data is then sent to a dashboard where it can be queried using standard SQL, making it accessible to both developers and BI tools.

Who it’s for

It is designed for Python developers and engineering teams who need a powerful yet simple observability platform to monitor their applications, particularly those using Pydantic for data validation.

Highlights

  • Pydantic Integration: Built-in analytics for Pydantic validation models to track data flow.
  • SQL-based Querying: Uses standard SQL to query observability data, removing the need to learn proprietary query languages.
  • OpenTelemetry Standard: Built on OTel, ensuring compatibility with existing infrastructure and other languages.
  • Python-centric: Specialized insights for Python-specific behaviors like event-loop telemetry and rich object display.

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