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Optimizing service performancemediumMultiple ChoiceObjective-mapped

PCDOE Optimizing service performance Practice Question

Your team has deployed a microservices application on Google Kubernetes Engine (GKE). You notice that one service has high latency during peak hours. The service is CPU-bound and uses a HorizontalPodAutoscaler (HPA) based on CPU utilization. What is the most likely cause of the latency?

⚠ Common exam trap

Google Cloud often tests the misconception that HPA scaling is instantaneous or that CPU-bound latency is caused by external factors like load balancers or node preemption, when the real issue is the HPA threshold configuration and its delayed reaction to sustained high utilization.

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

The HPA's target CPU utilization is set too high, causing the autoscaler to react slowly.

When the HPA's target CPU utilization is set too high, the autoscaler waits until the average CPU utilization exceeds that threshold before scaling up. During peak hours, the service becomes CPU-bound and latency increases as pods are overwhelmed, but the HPA reacts slowly because it only triggers when the high threshold is breached, causing a delay in adding new pods to handle the load.

Answer analysis

Option-by-option breakdown

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

  • The GKE cluster uses preemptible nodes that are frequently reclaimed.

    Why it's wrong here

    Preemptible nodes cause pod evictions, not gradual latency increase.

  • The HPA's target CPU utilization is set too high, causing the autoscaler to react slowly.

    Why this is correct

    A high target CPU threshold delays scaling, leading to latency.

  • The service uses a global external HTTP(S) load balancer with session affinity.

    Why it's wrong here

    Session affinity does not cause latency; it routes requests to the same backend.

  • The application does not implement request autoscaling at the application layer.

    Why it's wrong here

    Request autoscaling is not a built-in GKE concept.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This PCDOE 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 PCDOE exam.