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Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure

A team is running a GKE cluster with a workload that has variable CPU and memory usage. They want to automatically adjust pod resource requests and limits based on historical usage to improve resource efficiency. Which feature should they use?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Vertical Pod Autoscaler (VPA)

Vertical Pod Autoscaler (VPA) automatically adjusts CPU and memory requests and limits of pods based on historical usage, making it ideal for right-sizing. Horizontal Pod Autoscaler (HPA) scales the number of pods based on metrics, but does not modify resource requests. Cluster Autoscaler adjusts the number of nodes. PodDisruptionBudget controls pod disruptions during maintenance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Vertical Pod Autoscaler (VPA)

    Why this is correct

    VPA adjusts CPU and memory requests/limits based on usage, improving resource efficiency.

  • PodDisruptionBudget (PDB)

    Why it's wrong here

    PDB ensures a minimum number of pods are available during voluntary disruptions, but does not adjust resource requests.

  • Horizontal Pod Autoscaler (HPA)

    Why it's wrong here

    HPA scales the number of pods, not the resource requests of individual pods.

  • Cluster Autoscaler

    Why it's wrong here

    Cluster Autoscaler adjusts the number of nodes in the cluster, not pod resources.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This PCA practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCA exam.