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Class: Aws::SageMaker::Types::MonitoringClusterConfig

Inherits:
Struct
  • Object
show all
Defined in:
(unknown)

Overview

Note:

When passing MonitoringClusterConfig as input to an Aws::Client method, you can use a vanilla Hash:

{
  instance_count: 1, # required
  instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge
  volume_size_in_gb: 1, # required
  volume_kms_key_id: "KmsKeyId",
}

Configuration for the cluster used to run model monitoring jobs.

Returned by:

See Also:

Instance Attribute Summary collapse

Instance Attribute Details

#instance_count ⇒ Integer

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.

Returns:

  • (Integer) —

    The number of ML compute instances to use in the model monitoring job.

#instance_type ⇒ String

The ML compute instance type for the processing job.

Possible values:

  • ml.t3.medium
  • ml.t3.large
  • ml.t3.xlarge
  • ml.t3.2xlarge
  • ml.m4.xlarge
  • ml.m4.2xlarge
  • ml.m4.4xlarge
  • ml.m4.10xlarge
  • ml.m4.16xlarge
  • ml.c4.xlarge
  • ml.c4.2xlarge
  • ml.c4.4xlarge
  • ml.c4.8xlarge
  • ml.p2.xlarge
  • ml.p2.8xlarge
  • ml.p2.16xlarge
  • ml.p3.2xlarge
  • ml.p3.8xlarge
  • ml.p3.16xlarge
  • ml.c5.xlarge
  • ml.c5.2xlarge
  • ml.c5.4xlarge
  • ml.c5.9xlarge
  • ml.c5.18xlarge
  • ml.m5.large
  • ml.m5.xlarge
  • ml.m5.2xlarge
  • ml.m5.4xlarge
  • ml.m5.12xlarge
  • ml.m5.24xlarge
  • ml.r5.large
  • ml.r5.xlarge
  • ml.r5.2xlarge
  • ml.r5.4xlarge
  • ml.r5.8xlarge
  • ml.r5.12xlarge
  • ml.r5.16xlarge
  • ml.r5.24xlarge

Returns:

  • (String) —

    The ML compute instance type for the processing job.

#volume_kms_key_id ⇒ String

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.

Returns:

  • (String) —

    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.

#volume_size_in_gb ⇒ Integer

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

Returns:

  • (Integer) —

    The size of the ML storage volume, in gigabytes, that you want to provision.