StartMlflowTrackingServer - Amazon SageMaker

StartMlflowTrackingServer

Programmatically start an MLflow Tracking Server.

Request Syntax

{ "TrackingServerName": "string" }

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.

TrackingServerName

The name of the tracking server to start.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 256.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,255}

Required: Yes

Response Syntax

{ "TrackingServerArn": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

TrackingServerArn

The ARN of the started tracking server.

Type: String

Length Constraints: Maximum length of 2048.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:mlflow-tracking-server/.*

Errors

For information about the errors that are common to all actions, see Common Errors.

ConflictException

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

HTTP Status Code: 400

ResourceNotFound

Resource being access is not found.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: