Create an MLflow Tracking Server

An MLflow Tracking Server is a stand-alone HTTP server that serves multiple REST API endpoints for tracking runs and experiments. A tracking server is required to begin tracking your machine learning (ML) experiments with SageMaker and MLflow. You can create a tracking server through the Studio UI, or through the AWS CLI for more granular security customization.

You must have the correct IAM permissions configured to create an MLflow Tracking Server.

Topics

• Set up IAM permissions for MLflow
• Create a tracking server using Studio
• Create a tracking server using the AWS CLI