Google PCA Manage implementation of cloud architecture Practice Question
A company is deploying a microservices application on Google Kubernetes Engine (GKE). They want to ensure that the cluster can automatically scale based on custom metrics, such as the number of pending requests per pod. Which two steps should they take? (Choose TWO)
⚠ Common exam trap
A common mix-up: candidates confuse the Metrics Server (which exposes resource metrics) with the need for a custom metrics adapter; candidates often think the Metrics Server alone handles custom metrics, but it only serves CPU/memory, not application-level custom metrics like pending requests.
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
✓
Deploy the Metrics Server in the cluster to expose custom metrics via the Custom Metrics API.
The Metrics Server is required to expose custom metrics via the Custom Metrics API in GKE. Without it, the HorizontalPodAutoscaler (HPA) cannot retrieve the custom metrics needed for scaling decisions. Option B is correct because the application must expose custom metrics (e.g., pending requests) through an endpoint, and the HPA must be configured to reference that custom metric name to trigger scaling based on that specific value.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Deploy the Metrics Server in the cluster to expose custom metrics via the Custom Metrics API.
Why this is correct
The Metrics Server provides the Custom Metrics API, enabling HPA to use custom metrics.
- ✓
Modify the application to expose custom metrics via an endpoint and configure the HPA to reference the custom metric.
Why this is correct
The application must expose the metric, and the HPA must be configured to use it.
- ✗
Enable the Cloud Monitoring API and create a custom dashboard to track pending requests.
Why it's wrong here
Cloud Monitoring API is for monitoring, not for custom metrics scaling.
- ✗
Configure a HorizontalPodAutoscaler (HPA) with the target average CPU utilization set to 80%.
Why it's wrong here
CPU utilization is a resource metric, not a custom metric.
- ✗
Enable GKE Autopilot mode to automatically manage scaling based on custom metrics.
Why it's wrong here
Autopilot does not support custom metrics scaling.
Go deeper
Related to this question
Learn chapter
Introduction to Google Cloud Platform
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
Key term
Microservices
Microservices is an architectural style where a software application is built as a collection of small, independent services, each handling a specific business function and communicating over a network.
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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.