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Updates properties of an existing MLflow Tracking Server

Description

Updates properties of an existing MLflow Tracking Server.

Usage

sagemaker_update_mlflow_tracking_server(TrackingServerName,
  ArtifactStoreUri, TrackingServerSize, AutomaticModelRegistration,
  WeeklyMaintenanceWindowStart, S3BucketOwnerAccountId,
  S3BucketOwnerVerification)

Arguments

  • TrackingServerName

    [required] The name of the MLflow Tracking Server to update.

  • ArtifactStoreUri

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

  • TrackingServerSize

    The new size for the MLflow Tracking Server.

  • 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

  • WeeklyMaintenanceWindowStart

    The new weekly maintenance window start day and time to update. The maintenance window day and time should be in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.

  • S3BucketOwnerAccountId

    The new expected Amazon Web Services account ID that owns the Amazon S3 bucket for artifact storage.

  • S3BucketOwnerVerification

    Whether to enable or disable Amazon S3 Bucket Owenrship Verifaction whenever the MLflow Tracking Server interacts with Amazon Amazon S3.

Value

A list with the following syntax:

list(
  TrackingServerArn = "string"
)

Request syntax

svc$update_mlflow_tracking_server(
  TrackingServerName = "string",
  ArtifactStoreUri = "string",
  TrackingServerSize = "Small"|"Medium"|"Large",
  AutomaticModelRegistration = TRUE|FALSE,
  WeeklyMaintenanceWindowStart = "string",
  S3BucketOwnerAccountId = "string",
  S3BucketOwnerVerification = TRUE|FALSE
)