Answer-first summary for fast verification
Answer: Serverless compute
Serverless compute is the optimal choice for Automated ML training jobs requiring automatic scaling to a multi-node cluster. It abstracts infrastructure management and automatically scales compute resources based on job demand, making it ideal for handling larger datasets without manual intervention. Compute instance (A) is a single-node development environment that doesn't support multi-node clusters or automatic scaling. Endpoints (B) are for deploying and serving models, not training. Kubernetes cluster (C) can scale but requires manual configuration and management, unlike serverless which provides automatic scaling out-of-the-box.
Author: LeetQuiz Editorial Team
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You are designing a training job in an Azure Machine Learning workspace using Automated ML.
The compute resource must be able to scale up to a multi-node cluster to handle larger datasets.
Which Azure Machine Learning compute target should you use?
A
Compute instance
B
Endpoints
C
Kubernetes cluster
D
Serverless compute