Class: Aws::SageMaker::Types::LabelingJobResourceConfig

Inherits:

Struct

Object
Struct
Aws::SageMaker::Types::LabelingJobResourceConfig

Includes:: Aws::Structure

Defined in:: lib/aws-sdk-sagemaker/types.rb

Overview

Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.

Constant Summary collapse

SENSITIVE =

[]

Instance Attribute Summary collapse

#volume_kms_key_id ⇒ String

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
#vpc_config ⇒ Types::VpcConfig

Specifies a VPC that your training jobs and hosted models have access to.

Instance Attribute Details

#volume_kms_key_id ⇒ `String`

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.

You can only specify a ‘VolumeKmsKeyId` when you create a labeling job with automated data labeling enabled using the API operation `CreateLabelingJob`. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see [Output Data and Storage Volume Encryption].

The ‘VolumeKmsKeyId` can be any of the following formats:

KMS Key ID

‘“1234abcd-12ab-34cd-56ef-1234567890ab”`
Amazon Resource Name (ARN) of a KMS Key

‘“arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab”`

[1]: docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 22771

class LabelingJobResourceConfig < Struct.new(
  :volume_kms_key_id,
  :vpc_config)
  SENSITIVE = []
  include Aws::Structure
end

#vpc_config ⇒ `Types::VpcConfig`

Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see

Protect Endpoints by Using an Amazon Virtual Private Cloud][1: and

[Protect Training Jobs by Using an Amazon Virtual Private Cloud].

[1]: docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html [2]: docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html