AI-900 · Question #330
AI-900 Question #330: Real Exam Question with Answer & Explanation
The correct answer is D: compute instance. To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure M
Question
Which type of compute resource should you use to attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning?
Options
- Acompute cluster
- Bserverless compute
- Cinference cluster
- Dcompute instance
Explanation
To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure Machine Learning. You can achieve this using the Azure CLI v2, Python SDK v2, or Machine Learning Studio UI. 1. Kubernetes Compute Target: Azure Machine Learning treats your AKS cluster as a compute target, allowing you to specify it as the location for running your training jobs or deploying models. 2. Attached Compute: This refers to the ability to connect existing compute resources, like your AKS cluster, to your Azure Machine Learning workspace. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace
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