Running in production · Independent · 19 Oct 2026

pydantic/logfire

AI observability platform for production LLM and agent systems.

← Running in production

In simple English

When you run an app for other people, things break in ways you did not expect. This tool watches your code while it runs and shows you every step on a screen. You can see how long database queries take and what your artificial intelligence model is saying. It helps you find bugs fast without reading endless text files. The client library is free and open source, but you need an account on their server to see the dashboard.

What it is

Logfire is a monitoring platform built by the creators of Pydantic. It wraps OpenTelemetry (a standard way to collect data from software) to record logs, metrics, and traces from Python applications.

What it is good for

Solo developers building web apps or artificial intelligence agents who need to see why an error happened in production without digging through raw server logs.

Stars4.5k
LicenceMIT
Latestv5.2.0 (2026-10-13)checked 19 Oct 2026
Last code change2026-10-19
Written inPython
Setup effort
2 / 5
Payoff
4 / 5
Good
  • Integrates with popular web frameworks like FastAPI with a single line of setup.
  • Displays complex Python objects and data structures clearly in the dashboard.
  • Queries your telemetry data using standard SQL so you can use existing reporting tools.
Watch for
  • The server application and user interface are closed source and require a hosted account or enterprise purchase.
  • Adds external network calls to your application to send telemetry data while it runs.
  • Requires a paid plan for higher data volumes as your application grows.
Replaces

Raw text log files and traditional application performance monitoring tools.

Works well with

FastAPI web framework and Pydantic data validation libraries.

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Install
pip install logfire
logfire auth

Independent: reviewed for Repo Radar outside the daily editions. Every independent repository

On Stack Radar: AI & Automation › AI Development & Evaluation › AI Observability.

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