- A
Deploy a Regional GKE cluster with node auto-provisioning and a fixed number of replicas per service.
Why wrong: Fixed replicas cannot adapt to traffic spikes; node auto-provisioning alone is insufficient.
- B
Use a Regional GKE cluster with preemptible VMs and static pod counts.
Why wrong: Preemptible VMs can be terminated at any time, risking availability; static pod counts don't scale.
- C
Deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment.
Regional for high availability, cluster autoscaler for node scaling, HPA for pod scaling based on load.
- D
Use a single-zone GKE cluster with a large fixed node pool to handle peak load.
Why wrong: Single-zone lacks availability across zones and fixed nodes waste resources.
Quick Answer
The correct choice is to deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment. A Regional cluster distributes control plane and nodes across multiple zones, providing high availability against zone failures, while the cluster autoscaler dynamically adds or removes nodes to handle unpredictable traffic spikes without over-provisioning. The Horizontal Pod Autoscaler (HPA) then scales individual pod replicas based on CPU, memory, or custom metrics, ensuring each service scales independently and cost-effectively. On the Google Professional Cloud Developer exam, this scenario tests your ability to combine infrastructure-level and application-level scaling for stateless workloads—a common trap is choosing a zonal cluster with only HPA, which lacks multi-zone resilience. Remember the layered approach: Regional for HA, cluster autoscaler for node capacity, HPA for pod replicas. A useful memory tip is “RCH” — Regional, Cluster autoscaler, HPA — think “Rich Capacity Horizontally” to recall the three-tier scaling design.
PCD Practice Question: Designing highly scalable, available, and reliable cloud-native applications
This PCD practice question tests your understanding of designing highly scalable, available, and reliable cloud-native applications. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is deploying a microservices-based application on Google Kubernetes Engine (GKE). The application consists of several stateless services that experience unpredictable traffic spikes. The team wants to ensure high availability and scalability while minimizing costs. Which design should they implement?
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 a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment.
Option C is correct because a Regional GKE cluster provides multi-zone high availability, cluster autoscaling dynamically adjusts node pool size to handle unpredictable traffic spikes, and Horizontal Pod Autoscaler (HPA) scales individual pod replicas based on CPU/memory or custom metrics. This combination ensures both scalability and cost efficiency by only provisioning resources when needed.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 a Regional GKE cluster with node auto-provisioning and a fixed number of replicas per service.
Why it's wrong here
Fixed replicas cannot adapt to traffic spikes; node auto-provisioning alone is insufficient.
- ✗
Use a Regional GKE cluster with preemptible VMs and static pod counts.
Why it's wrong here
Preemptible VMs can be terminated at any time, risking availability; static pod counts don't scale.
- ✓
Deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment.
Why this is correct
Regional for high availability, cluster autoscaler for node scaling, HPA for pod scaling based on load.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a single-zone GKE cluster with a large fixed node pool to handle peak load.
Why it's wrong here
Single-zone lacks availability across zones and fixed nodes waste resources.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between scaling pods (HPA) and scaling nodes (cluster autoscaler), and the trap here is that candidates may think preemptible VMs or fixed replicas are sufficient for high availability and cost optimization, ignoring the need for dynamic scaling and multi-zone redundancy.
Detailed technical explanation
How to think about this question
Cluster autoscaling works by monitoring pending pods and adjusting node pool size via the Cluster Autoscaler, which integrates with Google Compute Engine's managed instance groups. HPA uses the Kubernetes Metrics Server to collect resource utilization and adjusts the `replicas` field in the deployment spec, with a default cooldown period of 3 minutes to avoid thrashing. In real-world scenarios, combining HPA with cluster autoscaling allows the cluster to scale from 3 to 100+ nodes during a flash sale while keeping costs low during idle periods.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this PCD question test?
Designing highly scalable, available, and reliable cloud-native applications — This question tests Designing highly scalable, available, and reliable cloud-native applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy a Regional GKE cluster with cluster autoscaling and Horizontal Pod Autoscaler for each deployment. — Option C is correct because a Regional GKE cluster provides multi-zone high availability, cluster autoscaling dynamically adjusts node pool size to handle unpredictable traffic spikes, and Horizontal Pod Autoscaler (HPA) scales individual pod replicas based on CPU/memory or custom metrics. This combination ensures both scalability and cost efficiency by only provisioning resources when needed.
What should I do if I get this PCD question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways this is tested on PCD
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is designing a cloud-native application on Google Kubernetes Engine. They want to ensure high availability and scalability for their microservices. Which two best practices should they follow?
medium- A.Use a single cluster per region.
- B.Use a single replica for each service to reduce cost.
- ✓ C.Use horizontal pod autoscaling based on custom metrics.
- D.Use stateful sets for all services.
- ✓ E.Deploy services across multiple zones.
Why C: Horizontal Pod Autoscaling (HPA) based on custom metrics allows the application to automatically scale the number of pod replicas in response to application-specific signals (e.g., requests per second, queue depth) rather than just CPU/memory. This ensures that each microservice can handle varying load efficiently, maintaining high availability and scalability without over-provisioning.
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Last reviewed: Jun 11, 2026
This PCD 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 PCD exam.
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