SageMaker / Client / create_mlflow_app

create_mlflow_app

SageMaker.Client.create_mlflow_app(**kwargs)

Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store.

See also: AWS API Documentation

Request Syntax

response = client.create_mlflow_app(
    Name='string',
    ArtifactStoreUri='string',
    RoleArn='string',
    ModelRegistrationMode='AutoModelRegistrationEnabled'|'AutoModelRegistrationDisabled',
    WeeklyMaintenanceWindowStart='string',
    AccountDefaultStatus='ENABLED'|'DISABLED',
    DefaultDomainIdList=[
        'string',
    ],
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
)
Parameters:

  • Name (string) –

    [REQUIRED]

    A string identifying the MLflow app name. This string is not part of the tracking server ARN.

  • ArtifactStoreUri (string) –

    [REQUIRED]

    The S3 URI for a general purpose bucket to use as the MLflow App artifact store.

  • RoleArn (string) –

    [REQUIRED]

    The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow App uses to access the artifact store in Amazon S3. The role should have the AmazonS3FullAccess permission.

  • ModelRegistrationMode (string) – Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to AutoModelRegistrationEnabled. To disable automatic model registration, set this value to AutoModelRegistrationDisabled. If not specified, AutomaticModelRegistration defaults to AutoModelRegistrationDisabled.

  • WeeklyMaintenanceWindowStart (string) – The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.

  • AccountDefaultStatus (string) – Indicates whether this MLflow app is the default for the entire account.

  • DefaultDomainIdList (list) –

    List of SageMaker domain IDs for which this MLflow App is used as the default.

    • (string) –

  • Tags (list) –

    Tags consisting of key-value pairs used to manage metadata for the MLflow App.

    • (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.

Return type:

dict

Returns:

Response Syntax

{
    'Arn': 'string'
}

Response Structure

  • (dict) –

    • Arn (string) –

      The ARN of the MLflow App.

Exceptions