Uses of Class
com.amazonaws.services.sagemaker.model.GetScalingConfigurationRecommendationResult

Packages that use GetScalingConfigurationRecommendationResult

Package	Description
com.amazonaws.services.sagemaker	Provides APIs for creating and managing SageMaker resources.
com.amazonaws.services.sagemaker.model

Uses of GetScalingConfigurationRecommendationResult in com.amazonaws.services.sagemaker

Methods in com.amazonaws.services.sagemaker that return GetScalingConfigurationRecommendationResult

Modifier and Type	Method and Description
GetScalingConfigurationRecommendationResult	AbstractAmazonSageMaker.getScalingConfigurationRecommendation(GetScalingConfigurationRecommendationRequest request)
GetScalingConfigurationRecommendationResult	AmazonSageMakerClient.getScalingConfigurationRecommendation(GetScalingConfigurationRecommendationRequest request) Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.
GetScalingConfigurationRecommendationResult	AmazonSageMaker.getScalingConfigurationRecommendation(GetScalingConfigurationRecommendationRequest getScalingConfigurationRecommendationRequest) Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.

Methods in com.amazonaws.services.sagemaker that return types with arguments of type GetScalingConfigurationRecommendationResult

Modifier and Type	Method and Description
Future<GetScalingConfigurationRecommendationResult>	AbstractAmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsyncClient.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest getScalingConfigurationRecommendationRequest) Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.
Future<GetScalingConfigurationRecommendationResult>	AbstractAmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsyncClient.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest getScalingConfigurationRecommendationRequest, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler) Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.

Method parameters in com.amazonaws.services.sagemaker with type arguments of type GetScalingConfigurationRecommendationResult

Modifier and Type	Method and Description
Future<GetScalingConfigurationRecommendationResult>	AbstractAmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsyncClient.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest request, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler)
Future<GetScalingConfigurationRecommendationResult>	AmazonSageMakerAsync.getScalingConfigurationRecommendationAsync(GetScalingConfigurationRecommendationRequest getScalingConfigurationRecommendationRequest, AsyncHandler<GetScalingConfigurationRecommendationRequest,GetScalingConfigurationRecommendationResult> asyncHandler) Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.

Uses of GetScalingConfigurationRecommendationResult in com.amazonaws.services.sagemaker.model

Methods in com.amazonaws.services.sagemaker.model that return GetScalingConfigurationRecommendationResult

Modifier and Type	Method and Description
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.clone()
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withDynamicScalingConfiguration(DynamicScalingConfiguration dynamicScalingConfiguration) An object with the recommended values for you to specify when creating an autoscaling policy.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withEndpointName(String endpointName) The name of an endpoint benchmarked during a previously completed Inference Recommender job.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withInferenceRecommendationsJobName(String inferenceRecommendationsJobName) The name of a previously completed Inference Recommender job.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withMetric(ScalingPolicyMetric metric) An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withRecommendationId(String recommendationId) The recommendation ID of a previously completed inference recommendation.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withScalingPolicyObjective(ScalingPolicyObjective scalingPolicyObjective) An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
GetScalingConfigurationRecommendationResult	GetScalingConfigurationRecommendationResult.withTargetCpuUtilizationPerCore(Integer targetCpuUtilizationPerCore) The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request.