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Answer: Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling.
The correct answer is C: Configure a HorizontalPodAutoscaler (HPA) for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling. This solution allows the system to automatically adjust the number of pods based on their resource usage, helping ensure efficient resource utilization. HPA helps in scaling the pods up or down based on demand, while node auto scaling adjusts the number of nodes in the cluster to meet the current load. This approach maintains availability while optimizing cost. Options A, B, and D either do not address both costs and availability effectively or are not suitable for all types of workloads in the given cluster.
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Your company relies on Google Kubernetes Engine (GKE) for managing its various workloads, which include batch, stateful, and stateless services. Currently, all these workloads run on a single large GKE cluster that comprises a node pool of 200 nodes. Due to financial constraints, your company is seeking ways to reduce the operational costs associated with this GKE cluster but aims to ensure that the availability of these services is not compromised. What should you do?
A
Create a second GKE cluster for the batch workloads only. Allocate the 200 original nodes across both clusters.
B
Configure CPU and memory limits on the namespaces in the cluster. Configure all Pods to have a CPU and memory limits.
C
Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling.
D
Change the node pool to use preemptible VMs.
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