The following pages explain how IT administrators can configure Amazon SageMaker Canvas and grant permissions to users within their organizations. You learn how to set up the storage configuration, manage data encryption and VPCs, control access to specific capabilities like generative AI foundation models, integrate with other AWS services like Amazon Redshift, and more. By following these steps, you can tailor SageMaker Canvas for your users based on your organization's specific requirements.
You can also set up SageMaker Canvas for your users with AWS CloudFormation. For more information, see AWS::SageMaker AI::App in the AWS CloudFormation User Guide.
Topics
Grant Users Permissions to Use Large Data across the ML Lifecycle
Store SageMaker Canvas application data in your own SageMaker AI space
Grant Your Users Permissions to Build Custom Image and Text Prediction Models
Grant Users Permissions to Use Amazon Bedrock and Generative AI Features in Canvas
Grant Your Users Permissions to Send Predictions to Amazon QuickSight
Configure Amazon SageMaker Canvas in a VPC without internet access
