Your GKE cluster currently runs on standard e2-medium nodes. Your data science team wants to deploy a new workload to the cluster that requires high-memory machines. You do not want to disrupt the existing workloads.

How should you accommodate this new workload?

Answer options:

Edit the existing node pool and change the machine type to high-memory.

Create a new node pool in the existing cluster using high-memory machine types.

Create a completely new GKE cluster for the data science team.

Use kubectl to manually allocate more memory to the specific pods.

How to approach this question

Understand that GKE clusters can have multiple groups of different machine types.

Full Answer

B.Create a new node pool in the existing cluster using high-memory machine types.✓ Correct

Create a new node pool in the existing cluster using high-memory machine types.

A node pool is a group of nodes within a cluster that all have the same configuration (machine type, disk size, etc.). A single GKE cluster can have multiple node pools. If you need different hardware (like high-memory machines or GPUs) for specific workloads, the best practice is to add a new node pool to the existing cluster and use node selectors/taints to schedule the specific pods onto those nodes.

Common mistakes

Trying to edit the machine type of an existing node pool. Node pool machine types are immutable after creation.

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