Batch endpoints run on compute clusters and support both Azure Machine Learning compute clusters (AmlCompute) and Kubernetes clusters. Clusters are a shared resource, therefore, one cluster can host one or many batch deployments (along with other workloads, if desired).
Create a compute named batch-cluster, as shown in the following code. You can adjust as needed and reference your compute using azureml:<your-compute-name>.
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-model-deployments?view=azureml-api-2&tabs=python
D is correct. Only clusters
Batch endpoints run on compute clusters and support both Azure Machine Learning compute clusters (AmlCompute) and Kubernetes clusters. Clusters are a shared resource, therefore, one cluster can host one or many batch deployments (along with other workloads, if desired).
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