pulumi-aws-kotlin/com.pulumi.aws.sagemaker.kotlin.inputs/DataQualityJobDefinitionJobResourcesClusterConfigArgs

DataQualityJobDefinitionJobResourcesClusterConfigArgs

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

Constructors

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

Functions

toJava

open override fun toJava(): DataQualityJobDefinitionJobResourcesClusterConfigArgs

Properties

instanceCount

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.

instanceType

val instanceType: Output<String>

The ML compute instance type for the processing job.

volumeKmsKeyId

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.

volumeSizeInGb

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.