--- title: "logfire vs whylogs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pydantic-logfire-vs-whylabs-whylogs" tools: ["pydantic-logfire", "whylabs-whylogs"] --- # logfire vs whylogs *GraphCanon updated Aug 9, 2026* ## Verdict Pick logfire if logfire provides specific tools for monitoring and evaluating AI systems in production environments, with strong emphasis on log management and traceability; pick whylogs if whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. [logfire](https://pydantic.dev/logfire/) reports 4.4k GitHub stars, 272 forks, and 259 open issues, last pushed Aug 8, 2026. [whylogs](https://whylogs.readthedocs.io/) has 2.8k stars, 143 forks, and 4 open issues, last pushed Jan 10, 2025. Figures are from public GitHub metadata via [logfire's repository](https://github.com/pydantic/logfire) and [whylogs's repository](https://github.com/whylabs/whylogs). | | [logfire](/tools/pydantic-logfire.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Tagline | AI observability platform for production LLM and agent systems | An open-source data logging library for ML models and data pipelines. | | Stars | 4,416 | 2,830 | | Forks | 272 | 143 | | Open issues | 259 | 4 | | Language | Python | Jupyter Notebook | | Adopt for | Logfire provides specific tools for monitoring and evaluating AI systems in production environments, with strong emphasis on log management and traceability. | whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [logfire](/tools/pydantic-logfire.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 568d | | Open issues (now) | 259 | 4 | | Full report | [trust report](/tools/pydantic-logfire/trust.md) | [trust report](/tools/whylabs-whylogs/trust.md) | ## Shared compatibility - **Python**: [logfire](/tools/pydantic-logfire.md) - Python runtime; [whylogs](/tools/whylabs-whylogs.md) - Python runtime ## Decision facts: logfire - **Adopt for:** Logfire provides specific tools for monitoring and evaluating AI systems in production environments, with strong emphasis on log management and traceability. ## Decision facts: whylogs - **Adopt for:** whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. ## Choose when ### Choose logfire if… - logfire is primarily Python; whylogs is Jupyter Notebook. - License: logfire is MIT, whylogs is Apache-2.0. - Tags unique to logfire: agent-observability, ai, ai-observability, evals. - Use Logfire when your project requires comprehensive observability tailored specifically for large language models (LLM) and agent-based systems. ### Choose whylogs if… - whylogs is primarily Jupyter Notebook; logfire is Python. - License: whylogs is Apache-2.0, logfire is MIT. - Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics. - whylogs ships Docker support for self-hosted deployment. - When you need comprehensive data visibility to track changes in datasets and model input features for ML systems ## When NOT to use logfire - Avoid using Logfire if your application does not involve LLMs or agent systems, as its features are finely tuned for these specific technologies. - Do not use if you prefer tools with broader application across different technology stacks rather than a specialized toolkit focused on Python and related frameworks. ## When NOT to use whylogs - When limited to using closed-source tools as whylogs is open source under the Apache-2.0 license - In environments where privacy-preserving features are not required or can be handled through other means ## Common questions ### What is the difference between logfire and whylogs? logfire: AI observability platform for production LLM and agent systems. whylogs: An open-source data logging library for ML models and data pipelines.. See the comparison table for live GitHub stats and shared categories. ### When should I choose logfire over whylogs? Choose logfire over whylogs when logfire is primarily Python; whylogs is Jupyter Notebook; License: logfire is MIT, whylogs is Apache-2.0; Tags unique to logfire: agent-observability, ai, ai-observability, evals; Use Logfire when your project requires comprehensive observability tailored specifically for large language models (LLM) and agent-based systems. ### When should I choose whylogs over logfire? Choose whylogs over logfire when whylogs is primarily Jupyter Notebook; logfire is Python; License: whylogs is Apache-2.0, logfire is MIT; Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics; whylogs ships Docker support for self-hosted deployment; When you need comprehensive data visibility to track changes in datasets and model input features for ML systems. ### When should I avoid logfire? Avoid using Logfire if your application does not involve LLMs or agent systems, as its features are finely tuned for these specific technologies. Do not use if you prefer tools with broader application across different technology stacks rather than a specialized toolkit focused on Python and related frameworks. ### When should I avoid whylogs? When limited to using closed-source tools as whylogs is open source under the Apache-2.0 license In environments where privacy-preserving features are not required or can be handled through other means ### Is logfire or whylogs more popular on GitHub? logfire has more GitHub stars (4,416 vs 2,830). Stars measure visibility, not whether either tool fits your constraints. ### Are logfire and whylogs open source? Yes - both are open-source projects on GitHub (logfire: MIT, whylogs: Apache-2.0). ### Where can I find alternatives to logfire or whylogs? GraphCanon lists graph-backed alternatives at [logfire alternatives](/tools/pydantic-logfire/alternatives) and [whylogs alternatives](/tools/whylabs-whylogs/alternatives) ([logfire markdown twin](/tools/pydantic-logfire/alternatives.md), [whylogs markdown twin](/tools/whylabs-whylogs/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/pydantic-logfire-vs-whylabs-whylogs.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, logfire or whylogs? logfire: Very active. whylogs: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for logfire and whylogs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [logfire trust report](/tools/pydantic-logfire/trust); [whylogs trust report](/tools/whylabs-whylogs/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pydantic-logfire`](/api/graphcanon/graph?tool=pydantic-logfire) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_