Answer-first summary for fast verification
Answer: Create a dedicated node pool with compute-optimized machine-type nodes for the image rendering microservice, and use general-purpose machine-type nodes for the remaining microservices.
Option B is the correct choice because it ensures the image rendering microservice has access to the necessary CPU resources by utilizing compute-optimized nodes, without impacting the performance of other microservices running on general-purpose nodes. Option A is incorrect as higher pod priority doesn't optimize resource usage but affects scheduling during contention. Option C is incorrect because general-purpose nodes may not meet the high CPU demands of the image rendering service. Option D is insufficient as it doesn't guarantee efficient resource usage across the entire cluster. For more details, refer to [Google Kubernetes Engine documentation on node pools](https://cloud.google.com/kubernetes-engine/docs/concepts/node-pools) and [Kubernetes documentation on scheduling](https://kubernetes.io/docs/concepts/scheduling-eviction/taint-and-toleration/).
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You've developed a complex microservices-based application on Kubernetes Engine. Among these, one microservice dedicated to rendering images demands significant CPU time and an average amount of memory. Your cluster currently uses n2-type nodes, which are well-suited for the other microservices. What strategy would you employ to optimize resource usage across your cluster?
A
Allocate a higher pod priority to the image rendering microservice's pods compared to others, to influence scheduling during resource contention.
B
Create a dedicated node pool with compute-optimized machine-type nodes for the image rendering microservice, and use general-purpose machine-type nodes for the remaining microservices.
C
Assign the image rendering microservice to the general-purpose machine-type node pool, and set up a separate node pool with compute-optimized machine-type nodes for the other microservices.
D
Specify the CPU and memory requirements in the resource requests section of the image rendering microservice's deployment, leaving other microservices' resource requests at default settings.