class Aws::SageMaker::Types::LabelingJobResourceConfig

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

@note When making an API call, you may pass LabelingJobResourceConfig

data as a hash:

    {
      volume_kms_key_id: "KmsKeyId",
    }

@!attribute [rw] volume_kms_key_id

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
customer managed CMK 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][1].

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]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html
@return [String]

@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobResourceConfig AWS API Documentation

Constants

SENSITIVE