Amazon SageMaker now offers a fully managed MLflow Capability

This article announces that Amazon SageMaker now offers a fully managed MLflow capability, allowing data scientists to use familiar MLflow constructs to organize, track, and analyze ML experiments, while administrators can set up MLflow with better scalability, availability, and security.

Specifically, the article covers:

• MLflow integration with SageMaker for tracking experiments across various environments
• Rich visualizations and model evaluation capabilities in MLflow
• Automatic registration of MLflow models in SageMaker Model Registry
• Deployment of MLflow models to SageMaker Inference
• Tracking metrics during model training for reproducibility
• Availability and pricing details
• Getting started resources (developer guide and blog)