sagemaker_update_mlflow_tracking_server: Updates properties of an existing MLflow Tracking Server

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Updates properties of an existing MLflow Tracking Server

Description

Updates properties of an existing MLflow Tracking Server.

See https://www.paws-r-sdk.com/docs/sagemaker_update_mlflow_tracking_server/ for full documentation.

Usage

sagemaker_update_mlflow_tracking_server(
  TrackingServerName,
  ArtifactStoreUri = NULL,
  TrackingServerSize = NULL,
  AutomaticModelRegistration = NULL,
  WeeklyMaintenanceWindowStart = NULL
)

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.

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.