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You are managing a suite of microservices deployed on a Kubernetes Engine cluster. Each microservice has distinct resource requirements. One specific microservice, responsible for rendering images, demands a considerable amount of CPU time but relatively little memory. The remaining microservices are configured to perform optimally on n2-standard machine types. Your objective is to fine-tune your cluster configuration to ensure that all microservices utilize resources in the most efficient manner possible. How should you achieve this?
Explanation:
Option B is the correct answer. The microservice responsible for image rendering requires a large amount of CPU time compared to the memory it requires. Therefore, it is best to create a node pool with compute-optimized machine type nodes specifically for the image rendering microservice to ensure it gets the necessary CPU resources. Using the existing node pool with general-purpose machine type nodes for the other microservices ensures that the resources are used efficiently for their specific workloads. This approach separates the workloads based on their resource requirements, leading to optimal resource utilization within the Kubernetes Engine cluster.