amazonka-sagemaker-2.0: Amazon SageMaker Service SDK.
Copyright(c) 2013-2023 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellSafe-Inferred
LanguageHaskell2010

Amazonka.SageMaker.CreateInferenceExperiment

Description

Creates an inference experiment using the configurations specified in the request.

Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.

Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based on your specified configuration.

While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.

Synopsis

Creating a Request

data CreateInferenceExperiment Source #

See: newCreateInferenceExperiment smart constructor.

Constructors

CreateInferenceExperiment' 

Fields

  • dataStorageConfig :: Maybe InferenceExperimentDataStorageConfig

    The Amazon S3 location and configuration for storing inference request and response data.

    This is an optional parameter that you can use for data capture. For more information, see Capture data.

  • description :: Maybe Text

    A description for the inference experiment.

  • kmsKey :: Maybe Text

    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 that hosts the endpoint. The KmsKey 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 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 in the Amazon Simple Storage Service Developer Guide.

    The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.

  • schedule :: Maybe InferenceExperimentSchedule

    The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.

  • tags :: Maybe [Tag]

    Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.

  • name :: Text

    The name for the inference experiment.

  • type' :: InferenceExperimentType

    The type of the inference experiment that you want to run. The following types of experiments are possible:

    • ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
  • roleArn :: Text

    The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

  • endpointName :: Text

    The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.

  • modelVariants :: NonEmpty ModelVariantConfig

    An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.

  • shadowModeConfig :: ShadowModeConfig

    The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.

Instances

Instances details
ToJSON CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

ToHeaders CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

ToPath CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

ToQuery CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

AWSRequest CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Generic CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Associated Types

type Rep CreateInferenceExperiment :: Type -> Type #

Read CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Show CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

NFData CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Eq CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Hashable CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

type AWSResponse CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

type Rep CreateInferenceExperiment Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

type Rep CreateInferenceExperiment = D1 ('MetaData "CreateInferenceExperiment" "Amazonka.SageMaker.CreateInferenceExperiment" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "CreateInferenceExperiment'" 'PrefixI 'True) (((S1 ('MetaSel ('Just "dataStorageConfig") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe InferenceExperimentDataStorageConfig)) :*: S1 ('MetaSel ('Just "description") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))) :*: (S1 ('MetaSel ('Just "kmsKey") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: (S1 ('MetaSel ('Just "schedule") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe InferenceExperimentSchedule)) :*: S1 ('MetaSel ('Just "tags") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [Tag]))))) :*: ((S1 ('MetaSel ('Just "name") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: (S1 ('MetaSel ('Just "type'") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 InferenceExperimentType) :*: S1 ('MetaSel ('Just "roleArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text))) :*: (S1 ('MetaSel ('Just "endpointName") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text) :*: (S1 ('MetaSel ('Just "modelVariants") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (NonEmpty ModelVariantConfig)) :*: S1 ('MetaSel ('Just "shadowModeConfig") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 ShadowModeConfig))))))

newCreateInferenceExperiment Source #

Create a value of CreateInferenceExperiment with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:dataStorageConfig:CreateInferenceExperiment', createInferenceExperiment_dataStorageConfig - The Amazon S3 location and configuration for storing inference request and response data.

This is an optional parameter that you can use for data capture. For more information, see Capture data.

CreateInferenceExperiment, createInferenceExperiment_description - A description for the inference experiment.

CreateInferenceExperiment, createInferenceExperiment_kmsKey - 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 that hosts the endpoint. The KmsKey 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 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 in the Amazon Simple Storage Service Developer Guide.

The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.

CreateInferenceExperiment, createInferenceExperiment_schedule - The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.

CreateInferenceExperiment, createInferenceExperiment_tags - Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.

CreateInferenceExperiment, createInferenceExperiment_name - The name for the inference experiment.

CreateInferenceExperiment, createInferenceExperiment_type - The type of the inference experiment that you want to run. The following types of experiments are possible:

  • ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.

CreateInferenceExperiment, createInferenceExperiment_roleArn - The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

CreateInferenceExperiment, createInferenceExperiment_endpointName - The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.

$sel:modelVariants:CreateInferenceExperiment', createInferenceExperiment_modelVariants - An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.

$sel:shadowModeConfig:CreateInferenceExperiment', createInferenceExperiment_shadowModeConfig - The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.

Request Lenses

createInferenceExperiment_dataStorageConfig :: Lens' CreateInferenceExperiment (Maybe InferenceExperimentDataStorageConfig) Source #

The Amazon S3 location and configuration for storing inference request and response data.

This is an optional parameter that you can use for data capture. For more information, see Capture data.

createInferenceExperiment_kmsKey :: Lens' CreateInferenceExperiment (Maybe Text) Source #

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 that hosts the endpoint. The KmsKey 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 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 in the Amazon Simple Storage Service Developer Guide.

The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.

createInferenceExperiment_schedule :: Lens' CreateInferenceExperiment (Maybe InferenceExperimentSchedule) Source #

The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.

createInferenceExperiment_tags :: Lens' CreateInferenceExperiment (Maybe [Tag]) Source #

Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.

createInferenceExperiment_type :: Lens' CreateInferenceExperiment InferenceExperimentType Source #

The type of the inference experiment that you want to run. The following types of experiments are possible:

  • ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.

createInferenceExperiment_roleArn :: Lens' CreateInferenceExperiment Text Source #

The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

createInferenceExperiment_endpointName :: Lens' CreateInferenceExperiment Text Source #

The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.

createInferenceExperiment_modelVariants :: Lens' CreateInferenceExperiment (NonEmpty ModelVariantConfig) Source #

An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.

createInferenceExperiment_shadowModeConfig :: Lens' CreateInferenceExperiment ShadowModeConfig Source #

The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.

Destructuring the Response

data CreateInferenceExperimentResponse Source #

See: newCreateInferenceExperimentResponse smart constructor.

Constructors

CreateInferenceExperimentResponse' 

Fields

Instances

Instances details
Generic CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Associated Types

type Rep CreateInferenceExperimentResponse :: Type -> Type #

Read CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Show CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

NFData CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

Eq CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

type Rep CreateInferenceExperimentResponse Source # 
Instance details

Defined in Amazonka.SageMaker.CreateInferenceExperiment

type Rep CreateInferenceExperimentResponse = D1 ('MetaData "CreateInferenceExperimentResponse" "Amazonka.SageMaker.CreateInferenceExperiment" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "CreateInferenceExperimentResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int) :*: S1 ('MetaSel ('Just "inferenceExperimentArn") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Text)))

Response Lenses