Amazon SageMaker Canvas setup and permissions management (for IT administrators)
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::App in the AWS CloudFormation User Guide.
Topics
- Grant Your Users Permissions to Upload Local Files
- Set Up SageMaker Canvas for Your Users
- Configure your Amazon S3 storage
- Grant permissions for cross-account Amazon S3 storage
- Grant Users Permissions to Use Large Data across the ML Lifecycle
- Encrypt Your SageMaker Canvas Data with AWS KMS
- Store SageMaker Canvas application data in your own SageMaker space
- Grant Your Users Permissions to Build Custom Image and Text Prediction Models
- Grant Your Users Permissions to Perform Time Series Forecasting
- Grant Users Permissions to Use Amazon Bedrock and Generative AI Features in Canvas
- Update SageMaker Canvas for Your Users
- Request a Quota Increase
- Grant Users Permissions to Import Amazon Redshift Data
- Grant Users Permissions to Collaborate with Studio Classic
- Grant Your Users Permissions to Send Predictions to Amazon QuickSight
- Applications management
- Configure Amazon SageMaker Canvas in a VPC without internet access
- Set up connections to data sources with OAuth
