SageMaker AI monitoring workflow connects Evidently reports to MLflow

AWS published guidance on monitoring discriminative machine learning models using Amazon SageMaker AI with MLflow. The workflow uses open-source Evidently to generate monitoring reports.

The post shows how teams can organize and compare monitoring results in MLflow, scale the process through pipelines, and trigger drift notifications.

For production ML teams, this is a reminder that model quality management depends on repeatable monitoring infrastructure after deployment, not only training metrics.