You manage an Azure Machine Learning workspace. You develop a machine learning model. You must deploy the model to use a low-priority VM with a pricing discount. You need to deploy the model. Which co

The correct answer is B. Azure Machine Learning compute clusters. Azure Machine Learning compute clusters (managed compute) natively support low-priority VMs, which use Azure's surplus capacity and offer discounts of up to 80% compared to dedicated VMs. Low-priority nodes may be preempted when Azure reclaims capacity, making them suitable for f

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Question

You manage an Azure Machine Learning workspace. You develop a machine learning model. You must deploy the model to use a low-priority VM with a pricing discount. You need to deploy the model. Which compute target should you use?

Options

AAzure Kubernetes Service (AKS)
BAzure Machine Learning compute clusters
CAzure Container Instances (ACI)
DLocal deployment

How the community answered

(36 responses)

B
94% (34)
C
3% (1)
D
3% (1)

Explanation

Azure Machine Learning compute clusters (managed compute) natively support low-priority VMs, which use Azure's surplus capacity and offer discounts of up to 80% compared to dedicated VMs. Low-priority nodes may be preempted when Azure reclaims capacity, making them suitable for fault-tolerant batch workloads. AKS clusters use standard or spot node pools but are provisioned separately and are not the primary choice for this scenario. Azure Container Instances (ACI) and local deployment do not support the low-priority VM billing model at all.

Topics

#Model deployment#Azure ML compute targets#Low-priority VMs#Cost optimization

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