#[non_exhaustive]
pub struct OutputDataConfig { /* private fields */ }
Expand description

Provides information about how to store model training results (model artifacts).

Implementations§

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that 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 KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. 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 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 in the Amazon Web Services Key Management Service Developer Guide.

Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.

Creates a new builder-style object to manufacture OutputDataConfig.

Trait Implementations§

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