Question

Your team runs intermittent training jobs on an Azure Machine Learning workspace. Costs are high because a dedicated compute cluster stays allocated even when no jobs are queued. You must minimize cost while ensuring capacity is available automatically when jobs are submitted. Which compute cluster configuration should you apply?

Accepted Answer

Set the minimum node count to 0 and configure a suitable maximum node count with an idle-seconds-before-scaledown value.

Answer

Provision a compute instance instead of a compute cluster and leave it running for the team.

Answer

Set both the minimum and maximum node count to the same fixed value so capacity is always reserved.

Answer

Attach a self-managed Azure Kubernetes Service cluster and run all training jobs on it continuously.