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Microsoft

DP-100 · Question #367

You manage an Azure Machine Learning workspace. The workspace includes an Azure Machine Learning Kubernetes compute target configured as an Azure Kubernetes Service (AKS) cluster named AKS1. AKS1 is…

The correct answer is D. instance_type. The instance_type parameter is used to specify the type of compute node when running a command job on an Azure ML Kubernetes compute target (AKS). In Azure ML, when an AKS cluster has multiple node pools with different hardware configurations (e.g., CPU vs. GPU nodes), the…

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Question

You manage an Azure Machine Learning workspace. The workspace includes an Azure Machine Learning Kubernetes compute target configured as an Azure Kubernetes Service (AKS) cluster named AKS1. AKS1 is configured to enable the targeting of different nodes to train workloads. You must run a command job on AKS1 by using the Azure ML Python SDK v2. The command job must select different types of compute nodes. The compute node types must be specified by using a command parameter. You need to configure the command parameter. Which parameter should you use?

Options

  • Aenvironment
  • Bcompute
  • Climits
  • Dinstance_type

How the community answered

(54 responses)
  • A
    6% (3)
  • B
    13% (7)
  • C
    2% (1)
  • D
    80% (43)

Explanation

The instance_type parameter is used to specify the type of compute node when running a command job on an Azure ML Kubernetes compute target (AKS). In Azure ML, when an AKS cluster has multiple node pools with different hardware configurations (e.g., CPU vs. GPU nodes), the instance_type parameter maps to a custom resource defined on the Kubernetes cluster that selects the appropriate node type. The compute parameter identifies which compute target to use (i.e., AKS1), not the node type within it. The environment parameter specifies the software environment, and limits defines resource constraints - neither selects a node type.

Topics

#Azure Machine Learning#Kubernetes Compute#Job Configuration#instance_type

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