Open-Source Observability · pydantic

logfire

Pydantic Logfire is an open-source Python SDK for observability of LLM and agent systems, built on OpenTelemetry. It provides tracing, metrics, and logging with Python-native insights, SQL querying, and integrations for frameworks like FastAPI. The backend platform is closed-source but can be self-hosted under enterprise license.

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Source: GitHub — github.com/pydantic/logfire

4.4k

GitHub stars

255

Forks

Python

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	pydantic/logfire
Owner	pydantic
Primary language	Python
License	MIT — OSI-approved
Stars	4.4k
Forks	255
Open issues	240
Latest release	v4.37.0 (2026-06-12)
Last updated	2026-07-08
Source	https://github.com/pydantic/logfire

What logfire is

Logfire wraps OpenTelemetry to provide Python-centric observability with support for traces, metrics, and logs. It includes built-in integrations for FastAPI, Pydantic validation, and popular Python packages, exposes data queryable via standard SQL, and can export to any OTel-compatible backend or the managed Logfire platform.

Quickstart

Get the logfire source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/pydantic/logfire.git2cd logfire3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

LLM and Agent System Monitoring

Purpose-built observability for production LLM applications and AI agents. Provides rich event tracing and span visualization tailored to LLM execution patterns.

Python Web Framework Instrumentation

Deep integration with FastAPI and other Python frameworks. Automatic tracing of HTTP requests, database queries, and application logic with minimal manual instrumentation.

Pydantic-Based Data Validation Analytics

Built-in insights into Pydantic model validation events and data flows. Ideal for applications using Pydantic for schema validation and seeking observability into validation patterns.

Implementation considerations

Requires SDK installation (pip install logfire) and authentication (logfire auth) before use; managed platform access is prerequisite for managed observability.
Can integrate manually via spans and logging calls, or auto-instrument popular packages (FastAPI, databases, HTTP clients) to reduce boilerplate.
Data export is OpenTelemetry-native; can route to managed Logfire platform or any OTel-compatible backend (e.g., Jaeger, Datadog, self-hosted OTEL Collector).
Python version compatibility badge present but specific minimum version not stated in provided data; review PyPI package details.
SQL querying capability available; requires familiarity with data schema or documentation to write effective queries.

When to avoid it — and what to weigh

Non-Python Environments Requiring Native Observability — Logfire SDK is Python-specific. While TypeScript and Rust SDKs exist separately, the Python SDK does not provide native observability for polyglot systems without cross-language orchestration.
On-Premises Deployment Without Enterprise License — The Logfire backend platform is closed-source. Self-hosting requires an enterprise license, which is a commercial arrangement. Open-source SDK alone cannot run the full platform.
Strict Open-Source Backend Requirements — If your organization requires a fully open-source, auditable backend, Logfire platform does not meet that requirement. You can export to third-party OTel backends, but Logfire's managed platform is proprietary.
Minimal Setup or Low Operational Overhead — Logfire requires authentication, configuration, and integration with a backend (managed or self-hosted). Projects seeking zero-touch logging should consider simpler alternatives.

License & commercial use

Logfire Python SDK is licensed under MIT License, a permissive OSI-approved open-source license. The license permits commercial use, modification, and distribution with minimal restrictions (retain attribution and license).

MIT License permits commercial use of the SDK without additional licensing fees. However, accessing the managed Logfire platform or self-hosting the backend requires commercial arrangement. Self-hosting is available under enterprise license (terms and pricing not provided). Review commercial terms with Pydantic for managed or enterprise deployment before production use.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

SDK is open-source (code auditable). MIT License does not include warranties. Project has a security policy (linked in README). Managed platform backend is closed-source; audit trail for data handling not visible. Self-hosting requires enterprise license and Logfire platform deployment (security posture of backend unknown). SDK exports data via OpenTelemetry; ensure transport layer (TLS) is configured. Authentication required (logfire auth); token management best practices should be reviewed.

Alternatives to consider

Datadog APM + Python Agent

Mature, closed-source observability platform with native Python support, broader integrations, and SaaS-only deployment. Less Python-centric than Logfire but more established for enterprise production.

Jaeger + OpenTelemetry SDK (direct)

Fully open-source tracing backend with OTel client instrumentation. Lower-level, requires more manual configuration but no vendor lock-in and greater transparency.

New Relic Python Agent

Commercial APM platform with strong Python support, rich integrations, and ease-of-use. Proprietary backend; alternative to Logfire's managed service model.

Software development agency

Build on logfire with DEV.co software developers

Start with the Logfire SDK (pip install logfire) and authenticate today. Evaluate against your observability requirements and backend strategy (managed vs. self-hosted). Review commercial terms for production deployment.

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logfire FAQ

Can I use Logfire SDK without the managed Logfire platform?

Yes. The SDK is OpenTelemetry-compliant and can export to any OTel-compatible backend (e.g., Jaeger, Datadog, self-hosted OTEL Collector). Managed Logfire platform is optional but recommended for ease-of-use.

Is the MIT License sufficient for my commercial product?

MIT permits commercial use of the SDK code. However, if you need the managed Logfire platform or self-hosted backend, commercial terms (including pricing and SLA) apply. Review Pydantic's commercial offerings.

What Python versions does Logfire support?

Not explicitly stated in provided data. Badge present on PyPI suggesting version support. Consult PyPI package page or documentation for specific version requirements.

How does Logfire compare to standard logging or print debugging?

Logfire provides structured tracing with spans, correlation IDs, context propagation, and SQL queryability across distributed systems. Standard logging is linear and unstructured; Logfire is purpose-built for observability of complex applications.

Work with a software development agency

Adopting logfire is usually one piece of a larger software development effort. As a software development agency, DEV.co provides software development services and web development expertise — pairing senior software developers and web developers with your team to design, build, and operate open-source observability software in production.

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