pulumi-aws-native-kotlin/com.pulumi.awsnative.sagemaker.kotlin.inputs/ModelQualityJobDefinitionClusterConfigArgs

ModelQualityJobDefinitionClusterConfigArgs

data class ModelQualityJobDefinitionClusterConfigArgs(val instanceCount: Output<Int>, val instanceType: Output<String>, val volumeKmsKeyId: Output<String>? = null, val volumeSizeInGb: Output<Int>) : ConvertibleToJava<ModelQualityJobDefinitionClusterConfigArgs>

Configuration for the cluster used to run model monitoring jobs.

Constructors

fun ModelQualityJobDefinitionClusterConfigArgs(instanceCount: Output<Int>, instanceType: Output<String>, volumeKmsKeyId: Output<String>? = null, volumeSizeInGb: Output<Int>)

Functions

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open override fun toJava(): ModelQualityJobDefinitionClusterConfigArgs

Properties

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val instanceCount: Output<Int>

The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.

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val instanceType: Output<String>

The ML compute instance type for the processing job.

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val volumeKmsKeyId: Output<String>? = null

The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.

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val volumeSizeInGb: Output<Int>

The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.