Role Manager FAQs

A: You can access Amazon SageMaker Role Manager through multiple location in the Amazon SageMaker AI console. For information about accessing role manager and using it to create a role, see Using the role manager (console).

A: Personas are preconfigured groups of permissions based on common machine learning (ML) responsibitilies. For example, the data science persona suggests permissions for general machine learning development and experimentation in a SageMaker AI environment, while the MLOps persona suggests permissions for ML activities related to operations.

A: ML activities are common AWS tasks related to machine learning with SageMaker AI that require specific IAM permissions. Each persona suggests related ML activities when creating a role with Amazon SageMaker Role Manager. ML activities include tasks such as Amazon S3 full access or searching and visualizing experiments. For more information, see ML activity reference.

A: Yes. Roles created using the Amazon SageMaker Role Manager are IAM roles with customized access policies. You can view created roles in the Roles section of the IAM console.

A: You can view created roles in the Roles section of the IAM console. By default, the prefix "sagemaker-" is added to every role name for easier search in the IAM console. For example, if you named your role test-123 during role creation, your role shows up as sagemaker-test-123 in the IAM console.

A: Yes. You can modify the roles and policies created by Amazon SageMaker Role Manager through the IAM console. For more information, see Modifying a role in the AWS Identity and Access Management User Guide.

A: Yes. You can attach any AWS or customer-managed IAM policies from your account to the role that you create using Amazon SageMaker Role Manager.

A: The maximum limit for attaching managed policies to an IAM role or user is 20. The maximum character size limit for managed policies is 6,144. For more information, see IAM object quotas and IAM and AWS Security Token Service quotas name requirements, and character limits.

A: Any conditions that you provide in Step 1. Enter role information of the Amazon SageMaker Role Manager, such as subnets, security groups, or KMS keys, are automatically passed to any ML activities selected in Step 2. Configure ML activities. You can also add additional conditions to ML activities if necessary. For example, you might also add InstanceTypes or IntercontainerTrafficEncryption conditions to the Manage Training Jobs activity.

A:You can add tags to your role in Step 3: Add additional policies and tags of the Amazon SageMaker Role Manager. To successfully manage AWS resources using tags, you must add the same tag to both the role and any associated policies. For example, you can add a tag to a role and to an Amazon S3 bucket. Then, because the role passes the tag to the SageMaker AI session, only a user with that role can access that S3 bucket. You can add tags to a policy through the IAM console. For more information, see Tagging IAM roles in the AWS Identity and Access Management User Guide.

A: No. However, after creating a service role in the role manager, you can go to the IAM console to edit the role and add a human access role in IAM console.

A: A user federation role is directly assumed by a user to access AWS resources such as access to the AWS Management Console. A SageMaker AI execution role is assumed by the SageMaker AI service to perform a function on behalf of a user or an automation tool. For example, when a user opens a Studio Classic instance, Studio Classic assumes the execution role associated with the user profile in order to access AWS resources on the behalf of the user. If the user profile does not specify an execution role, then the execution role is specified at the Amazon SageMaker AI domain level.

A: If you use a custom web application to access Studio Classic, then you have a hybrid user federation role and SageMaker AI execution role. Be sure that this role has least privilege permissions for both what the user can do and what Studio Classic can do on the associated user’s behalf.

A: AWS IAM Identity Center Studio Classic Cloud Applications use a Studio Classic execution role to grant permissions to federated users. This execution role can be specified at the Studio Classic IAM Identity Center user profile level or the default domain level. User identities and groups must be synchronized into IAM Identity Center and the Studio Classic user profile must be created with IAM Identity Center user assignment using CreateUserProfile. For more information, see Launch Studio Classic with IAM Identity Center.