Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure
What is the purpose of a Pod Disruption Budget (PDB) in GKE?
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
✓
To ensure a minimum number of pods are always available during voluntary disruptions
A PDB limits the number of pods of a replicated application that can be down simultaneously from voluntary disruptions (e.g., node upgrades, cluster autoscaler evictions).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
To automatically scale pods based on CPU usage
Why it's wrong here
That's the Horizontal Pod Autoscaler (HPA).
- ✗
To distribute pods across different zones
Why it's wrong here
That is achieved via pod topology spread constraints or node affinity.
- ✓
To ensure a minimum number of pods are always available during voluntary disruptions
Why this is correct
PDBs define the minimum available pods, ensuring high availability.
- ✗
To prevent any pod from being terminated
Why it's wrong here
PDBs allow some disruption, not none.
Go deeper
Related to this question
Learn chapter
IAM Policies, Service Accounts, and Auditing
Key term
Pod
A pod is the smallest deployable unit in Kubernetes, containing one or more containers that share storage, network, and a specification for how to run.
Key term
Autoscaler
An Autoscaler is a cloud service that automatically increases or decreases the number of virtual machines (instances) or resources based on real-time demand, so your application always has enough capacity without wasting money on idle servers.
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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.