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scaling_configuration_recommendations

Creates, updates, deletes, gets or lists a scaling_configuration_recommendations resource.

Overview​

Namescaling_configuration_recommendations
TypeResource
Idaws.sagemaker.scaling_configuration_recommendations

Fields​

The following fields are returned by SELECT queries:

NameDatatypeDescription
dynamic_scaling_configurationobjectAn object with the recommended values for you to specify when creating an autoscaling policy.
endpoint_namestringThe name of an endpoint benchmarked during a previously completed Inference Recommender job. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
inference_recommendations_job_namestringThe name of a previously completed Inference Recommender job. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,63}</code>)
metricobjectAn object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
recommendation_idstringThe recommendation ID of a previously completed inference recommendation.
scaling_policy_objectiveobjectAn object representing the anticipated traffic pattern for an endpoint that you specified in the request.
target_cpu_utilization_per_coreintegerThe percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.

Methods​

The following methods are available for this resource:

NameAccessible byRequired ParamsOptional ParamsDescription
get_scaling_configuration_recommendationselectregionStarts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.

Parameters​

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

NameDatatypeDescription
regionstringAWS region (default: us-east-1)

SELECT examples​

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

SELECT
dynamic_scaling_configuration,
endpoint_name,
inference_recommendations_job_name,
metric,
recommendation_id,
scaling_policy_objective,
target_cpu_utilization_per_core
FROM aws.sagemaker.scaling_configuration_recommendations
WHERE region = '{{ region }}' -- required
;