Whylogs

Open source standard for data logging and ML monitoring.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

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

Strength Radar

Data logging for…Monitoring of da…Integration with…Lightweight and …

Honest assessment

Strengths & Weaknesses

↑ Strengths

Data logging for ML models

Monitoring of data distribution changes

Integration with various storage backends

Lightweight and easy to integrate into existing pipelines

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

None

Starts at

See website

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.

View Setup Guide →