Class: Aws::SageMaker::Types::CreateMlflowTrackingServerRequest

Inherits:
Struct
  • Object
show all
Includes:
Aws::Structure
Defined in:
lib/aws-sdk-sagemaker/types.rb

Overview

Constant Summary collapse

SENSITIVE =
[]

Instance Attribute Summary collapse

Instance Attribute Details

#artifact_store_uriString

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

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#automatic_model_registrationBoolean

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`.

Returns:

  • (Boolean)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#mlflow_versionString

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

[1]: docs.aws.amazon.com/sagemaker/latest/dg/mlflow.html#mlflow-create-tracking-server-how-it-works

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#role_arnString

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].

[1]: docs.aws.amazon.com/sagemaker/latest/dg/mlflow-create-tracking-server-iam.html

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#tagsArray<Types::Tag>

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

Returns:



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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#tracking_server_nameString

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

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#tracking_server_sizeString

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.

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#weekly_maintenance_window_startString

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.

Returns:

  • (String)


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# File 'lib/aws-sdk-sagemaker/types.rb', line 7961

class CreateMlflowTrackingServerRequest < Struct.new(
  :tracking_server_name,
  :artifact_store_uri,
  :tracking_server_size,
  :mlflow_version,
  :role_arn,
  :automatic_model_registration,
  :weekly_maintenance_window_start,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end