You manage an Azure Machine learning workspace. The workspace includes an Azure Machine Learning kubernetes compute target configured as an Azure…

When submitting a command job to an Azure Kubernetes Service (AKS) compute target using the Azure ML Python SDK v2, the instancetype parameter is used to specify the virtual machine (VM) size for the job. If the AKS cluster is configured with multiple node pools, each with a different VM size, specifying the instancetype directs the Azure ML scheduler to run the job on a node within the corresponding node pool. This allows for the selection of different compute node types for different workloads as required by the question.

A. compute: This parameter specifies the name of the compute target (e.g., the AKS cluster 'AKS1') where the job will run, not the specific type of node within that cluster.

B. environment: This parameter defines the software environment, including the Docker image and package dependencies for the job, not the underlying hardware infrastructure.

D. limits: This parameter is used to set resource constraints (like CPU or memory limits) for the container running the job, but it does not select the underlying VM node type.

1. Microsoft Official Documentation - azure.ai.ml.command function: The signature for the command function clearly lists instancetype as a parameter. The description states it is "The instance type of the compute target."

Source: Microsoft

Azure Machine Learning SDK documentation

"azure.ai.ml package - command function".

2. Microsoft Official Documentation - Train models with Azure Machine Learning CLI and Python SDK (v2): In the "Configure the job" section for a command job

the documentation shows an example of setting the instancetype within the job definition to specify the VM size for the run.

Source: Microsoft

Azure Machine Learning documentation

"Train models (create jobs)".

3. Microsoft Official Documentation - Attach and manage Kubernetes clusters: This document explains how instancetype is used with Kubernetes compute. It states

"When you submit a job to a Kubernetes compute target

you can use the instancetype parameter to specify the VM size for the job to run on. If the AKS cluster has a node pool with the specified VM size

the job will be scheduled to a node in that node pool."

Source: Microsoft

Azure Machine Learning documentation

"Configure and attach Kubernetes clusters in Azure Machine Learning"

Section: "Use instance type for job targeting".