class Aws::SageMaker::Types::OutputDataConfig
Provides information about how to store model training results (model artifacts).
@note When making an API call, you may pass OutputDataConfig
data as a hash: { kms_key_id: "KmsKeyId", s3_output_path: "S3Uri", # required }
@!attribute [rw] kms_key_id
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The `KmsKeyId` 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"` * // KMS Key Alias `"alias/ExampleAlias"` * // Amazon Resource Name (ARN) of a KMS Key Alias `"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"` If you use a KMS key ID or an alias of your master key, the Amazon SageMaker execution role must include permissions to call `kms:Encrypt`. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS-managed keys for `OutputDataConfig`. If you use a bucket policy with an `s3:PutObject` permission that only allows objects with server-side encryption, set the condition key of `s3:x-amz-server-side-encryption` to `"aws:kms"`. For more information, see [KMS-Managed Encryption Keys][1] in the *Amazon Simple Storage Service Developer Guide.* The KMS key policy must grant permission to the IAM role that you specify in your `CreateTrainingJob`, `CreateTransformJob`, or `CreateHyperParameterTuningJob` requests. For more information, see [Using Key Policies in Amazon Web Services KMS][2] in the *Amazon Web Services Key Management Service Developer Guide*. [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.html [2]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html @return [String]
@!attribute [rw] s3_output_path
Identifies the S3 path where you want Amazon SageMaker to store the model artifacts. For example, `s3://bucket-name/key-name-prefix`. @return [String]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OutputDataConfig AWS API Documentation
Constants
- SENSITIVE