Store SageMaker Canvas application data in your own SageMaker AI space

Your Amazon SageMaker Canvas application data, such as datasets that you import and your model artifacts, is stored in a Amazon SageMaker Studio private space. The space consists of a storage volume for your application data with 100 GB of storage per user profile, the type of the space (in this case, a Canvas application), and the image for your application's container. When you set up Canvas and launch your application for the first time, SageMaker AI creates a default private space that is assigned to your user profile and stores your Canvas data. You don't have to do any additional configuration to set up the space because SageMaker AI automatically creates the space on your behalf. However, if you don't want to use the default space, you have the option to specify a space that you created yourself. This can be useful if you want to isolate your data. The following page shows you how to create and configure your own Studio space for storing Canvas application data.

Before you begin

Your Amazon SageMaker AI domain or user profile must have at least 100 GB of storage in order to create and use the SageMaker Canvas application.

If you created your domain through the SageMaker AI console, enough storage is provisioned by default and you don't need to take any additional action. If you created your domain or user profile with the CreateDomain or CreateUserProfile APIs, then make sure that you set the MaximumEbsVolumeSizeInGb value to 100 GB or greater. To set a greater storage value, you can either create a new domain or user profile, or you can update an existing domain or user profile using the UpdateDomain or UpdateUserProfile APIs.

Create a new space

First, create a new Studio space that is configured to store Canvas application data. This is the space that you specify when creating a new Canvas application in the next step.

To create a space, you can use the AWS SDK for Python (Boto3) or the AWS CLI.

response = client.create_space(
    DomainId='<your-domain-id>', 
    SpaceName='<your-new-space-name>',
    SpaceSettings={
        'AppType': 'Canvas',
        'SpaceStorageSettings': {
            'EbsStorageSettings': {
                'EbsVolumeSizeInGb': <storage-volume-size>
            }
        },
    },
    OwnershipSettings={
        'OwnerUserProfileName': '<your-user-profile>'
    },
    SpaceSharingSettings={
        'SharingType': 'Private'
    }  
)

You should now have a space. Keep track of your space's name for the next step.

Create a new Canvas application

After creating a space, create a new Canvas application that specifies the space as its storage location.

To create a new Canvas application, you can use the AWS SDK for Python (Boto3) or the AWS CLI.

response = client.create_app(  
    DomainId='<your-domain-id>',
    SpaceName='<your-space-name>',
    AppType='Canvas', 
    AppName='default'  
)

You should now have a new Canvas application that uses a custom Studio space as the storage location for application data.

The space is attached to the user profile you specified in the space configuration. You can delete your Canvas application without deleting the space, and the data stored in the space remains. The data stored in your space is only deleted if you delete your user profile, or if you directly delete the space.