CreateMlflowTrackingServer - Amazon SageMaker

CreateMlflowTrackingServer

Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store. For more information, see Create an MLflow Tracking Server.

Request Syntax

{ "ArtifactStoreUri": "string", "AutomaticModelRegistration": boolean, "MlflowVersion": "string", "RoleArn": "string", "Tags": [ { "Key": "string", "Value": "string" } ], "TrackingServerName": "string", "TrackingServerSize": "string", "WeeklyMaintenanceWindowStart": "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.

ArtifactStoreUri

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

Type: String

Length Constraints: Maximum length of 1024.

Pattern: ^(https|s3)://([^/]+)/?(.*)$

Required: Yes

AutomaticModelRegistration

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 True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.

Type: Boolean

Required: No

MlflowVersion

The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.

Type: String

Length Constraints: Maximum length of 16.

Pattern: ^[0-9]*.[0-9]*.[0-9]*

Required: No

RoleArn

The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have AmazonS3FullAccess permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes

Tags

Tags consisting of key-value pairs used to manage metadata for the tracking server.

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

TrackingServerName

A unique string identifying the tracking server name. This string is part of the tracking server ARN.

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

TrackingServerSize

The size of the tracking server you want to create. You can choose between "Small", "Medium", and "Large". The default MLflow Tracking Server configuration size is "Small". You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.

We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.

Type: String

Valid Values: Small | Medium | Large

Required: No

WeeklyMaintenanceWindowStart

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.

Type: String

Length Constraints: Maximum length of 9.

Pattern: (Mon|Tue|Wed|Thu|Fri|Sat|Sun):([01]\d|2[0-3]):([0-5]\d)

Required: No

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 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.

ResourceLimitExceeded

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.

HTTP Status Code: 400

See Also

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