SageMaker / Client / start_mlflow_tracking_server

start_mlflow_tracking_server#

SageMaker.Client.start_mlflow_tracking_server(**kwargs)#

Programmatically start an MLflow Tracking Server.

See also: AWS API Documentation

Request Syntax

response = client.start_mlflow_tracking_server(
    TrackingServerName='string'
)
Parameters:

TrackingServerName (string) –

[REQUIRED]

The name of the tracking server to start.

Return type:

dict

Returns:

Response Syntax

{
    'TrackingServerArn': 'string'
}

Response Structure

  • (dict) –

    • TrackingServerArn (string) –

      The ARN of the started tracking server.

Exceptions

  • SageMaker.Client.exceptions.ResourceNotFound

  • SageMaker.Client.exceptions.ConflictException