Whylogs
Open source standard for data logging and ML monitoring.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Whylogs?
Whylogs is an open-source library that enables developers to log and monitor their machine learning models' performance. It provides a robust way to track changes in data distributions over time, which is crucial for maintaining model reliability.
Key differentiator
“Whylogs stands out as an open-source tool that provides a simple yet powerful way to log and monitor ML models' performance without the need for heavy infrastructure.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Primary development focus is on Python, with limited official support for other languages
Logging at scale can introduce significant latency and resource usage
Fit analysis
Who is it for?
✓ Best for
Teams needing to monitor and log their ML models' performance
Projects where maintaining model reliability is crucial due to changing data distributions
Developers looking for a lightweight, easy-to-integrate solution for logging
✕ Not a fit for
Real-time monitoring of streaming data (Whylogs focuses on batch processing)
Teams requiring complex, real-time alerting systems beyond basic logging capabilities
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Next step
Get Started with Whylogs
Step-by-step setup guide with code examples and common gotchas.