sagemaker_get_scaling_configuration_recommendation: Starts an Amazon SageMaker Inference Recommender autoscaling...

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job

Description

Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.

See https://www.paws-r-sdk.com/docs/sagemaker_get_scaling_configuration_recommendation/ for full documentation.

Usage

sagemaker_get_scaling_configuration_recommendation(
  InferenceRecommendationsJobName,
  RecommendationId = NULL,
  EndpointName = NULL,
  TargetCpuUtilizationPerCore = NULL,
  ScalingPolicyObjective = NULL
)

Arguments

InferenceRecommendationsJobName	[required] The name of a previously completed Inference Recommender job.
RecommendationId	The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field. Specify either this field or the EndpointName field.
EndpointName	The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field. Specify either this field or the RecommendationId field.
TargetCpuUtilizationPerCore	The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
ScalingPolicyObjective	An object where you specify the anticipated traffic pattern for an endpoint.

paws.machine.learning documentation built on Sept. 12, 2023, 1:14 a.m.