Google PCA Practice Question: Analyze and optimize technical and business processes
An organization runs a Kubernetes cluster on GKE with cluster autoscaling enabled. They notice that pods are frequently in 'Pending' state due to insufficient CPU, but the cluster autoscaler does not add nodes quickly enough. What is the most likely cause?
⚠ Common exam trap
Google Cloud often tests the distinction between pod-level scaling (HPA) and node-level scaling (cluster autoscaler), and the trap here is that candidates confuse a restrictive PDB with a node pool limit, or assume the expander strategy directly causes scaling delays.
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 node pool has reached the maximum node count limit.
The cluster autoscaler cannot add new nodes if the node pool has already reached its maximum node count limit. This limit is configured at the node pool level in GKE, and once reached, the autoscaler will not scale up further, leaving pods in 'Pending' state due to insufficient CPU resources.
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 cluster autoscaler is using the 'least-waste' expander.
Why it's wrong here
That expander is fine.
- ✗
The horizontal pod autoscaler (HPA) is misconfigured.
Why it's wrong here
HPA scales pods, not nodes.
- ✗
The pod disruption budget (PDB) is too restrictive.
Why it's wrong here
PDB prevents voluntary disruptions, not scaling.
- ✓
The node pool has reached the maximum node count limit.
Why this is correct
Cluster autoscaler cannot exceed max node limit.
Go deeper
Related to this question
Learn chapter
Google Cloud Resource Hierarchy and Organization
Key term
Kubernetes cluster
A set of machines, called nodes, that work together to run and manage containerized applications using Kubernetes orchestration software.
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
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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.