ML activity reference - Amazon SageMaker
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ML activity reference

ML activities are common Amazon tasks related to machine learning with SageMaker that require specific IAM permissions. Each persona suggests related ML activities when creating a role with Amazon SageMaker Role Manager. You can select any additional ML activities or deselect any suggested ML activities to create a role that meets your unique business needs.

Amazon SageMaker Role Manager provides predefined permissions for the following ML activities:

ML activity Description
Access Required Amazon Services Permissions to access Amazon S3, Amazon ECR, Amazon CloudWatch, and Amazon EC2. Required for execution roles for jobs and endpoints.
Run Studio Classic Applications Permissions to operate within a Studio Classic environment. Required for domain and user profile execution roles.
Manage ML Jobs Permissions to audit, query lineage, and visualize experiments.
Manage Models Permissions to manage SageMaker jobs across their lifecycles.
Manage Endpoints Permissions to manage SageMaker endpoint deployments and updates.
Manage Pipelines Permissions to manage SageMaker pipelines and pipeline executions.
Manage Experiments Permissions to manage SageMaker experiments and trials.
Search and Visualize Experiments Permissions to audit, query lineage, and visualize experiments.
Manage Model Monitoring Permissions to manage monitoring schedules for SageMaker Model Monitor.
S3 Full Access Permissions to perform all Amazon S3 operations.
S3 Bucket Access Permissions to perform operations on specified S3 buckets.
Query Athena Workgroups Permissions to run and manage Amazon Athena queries.
Use MLflow Permissions to manage experiments, runs, and models in MLflow.
Manage MLflow Tracking Servers Permissions to manage, start, and stop MLflow Tracking Servers.
Access required to Amazon Services for MLflow Permissions for MLflow Tracking Servers to access S3, Secrets Manager, and Model Registry.