You have several hundred microservice applications running in a Google Kubernetes Engine (GKE) cluster. Each microservice is a deployment with resource limits configured for each container in the depl

Question

Options

• AConfigure a Vertical Pod Autoscaler for each microservice.
• BModify the cluster's node pool machine type and choose a machine type with more memory and
• CConfigure a Horizontal Pod Autoscaler for each microservice.
• DConfigure GKE cluster autoscaling.

• A
  78% (40)
• B
  6% (3)
• C
  12% (6)
• D
  4% (2)

Explanation

Right-Sizing Resources: VPA is designed to automatically adjust the resource requests and limits (CPU and memory) for pods based on their actual usage. This ensures that pods have enough resources to run efficiently without being over-provisioned, which can lead to wasted resources and higher costs. Automated Optimization: VPA continuously monitors the resource usage of your pods and recommends optimal settings. You can choose to apply these recommendations automatically or manually, giving you flexibility and control over the process. Microservice-Specific Tuning: By configuring a VPA for each microservice, you can fine-tune the resource allocation for each individual service based on its specific needs and usage patterns. This is more efficient than making blanket changes to the entire cluster or node pool.

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