create_app

create_app(**kwargs)

Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

See also: AWS API Documentation

Request Syntax

response = client.create_app(
    DomainId='string',
    UserProfileName='string',
    AppType='JupyterServer'|'KernelGateway'|'TensorBoard'|'RStudioServerPro'|'RSessionGateway',
    AppName='string',
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ],
    ResourceSpec={
        'SageMakerImageArn': 'string',
        'SageMakerImageVersionArn': 'string',
        'InstanceType': 'system'|'ml.t3.micro'|'ml.t3.small'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.8xlarge'|'ml.m5.12xlarge'|'ml.m5.16xlarge'|'ml.m5.24xlarge'|'ml.m5d.large'|'ml.m5d.xlarge'|'ml.m5d.2xlarge'|'ml.m5d.4xlarge'|'ml.m5d.8xlarge'|'ml.m5d.12xlarge'|'ml.m5d.16xlarge'|'ml.m5d.24xlarge'|'ml.c5.large'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.12xlarge'|'ml.c5.18xlarge'|'ml.c5.24xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge'|'ml.g5.xlarge'|'ml.g5.2xlarge'|'ml.g5.4xlarge'|'ml.g5.8xlarge'|'ml.g5.16xlarge'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.g5.48xlarge',
        'LifecycleConfigArn': 'string'
    },
    SpaceName='string'
)
Parameters
  • DomainId (string) --

    [REQUIRED]

    The domain ID.

  • UserProfileName (string) -- The user profile name. If this value is not set, then SpaceName must be set.
  • AppType (string) --

    [REQUIRED]

    The type of app.

  • AppName (string) --

    [REQUIRED]

    The name of the app.

  • Tags (list) --

    Each tag consists of a key and an optional value. Tag keys must be unique per resource.

    • (dict) --

      A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

      You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.

      For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.

      • Key (string) -- [REQUIRED]

        The tag key. Tag keys must be unique per resource.

      • Value (string) -- [REQUIRED]

        The tag value.

  • ResourceSpec (dict) --

    The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.

    Note

    The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.

    • SageMakerImageArn (string) --

      The ARN of the SageMaker image that the image version belongs to.

    • SageMakerImageVersionArn (string) --

      The ARN of the image version created on the instance.

    • InstanceType (string) --

      The instance type that the image version runs on.

      Note

      JupyterServer apps only support the system value.

      For KernelGateway apps , the system value is translated to ml.t3.medium . KernelGateway apps also support all other values for available instance types.

    • LifecycleConfigArn (string) --

      The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.

  • SpaceName (string) -- The name of the space. If this value is not set, then UserProfileName must be set.
Return type

dict

Returns

Response Syntax

{
    'AppArn': 'string'
}

Response Structure

  • (dict) --

    • AppArn (string) --

      The Amazon Resource Name (ARN) of the app.

Exceptions

  • SageMaker.Client.exceptions.ResourceLimitExceeded
  • SageMaker.Client.exceptions.ResourceInUse