hardMultiple Choice
CV0-004 Practice Question: Deploying a microservices architecture that must…
A company is deploying a microservices architecture that must scale dynamically based on traffic. Which technology should be used?
⚠ Common exam trap
Many exam-takers confuse load balancing (distributing existing capacity) with autoscaling (adding capacity on demand) — candidates who pick the load balancer option mistake traffic distribution for elastic scaling.
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
✓
Kubernetes with Horizontal Pod Autoscaler
Kubernetes with Horizontal Pod Autoscaler (HPA) is purpose-built for microservices that must scale dynamically: HPA watches metrics (CPU, memory, or custom metrics via the metrics API) and automatically adjusts the number of pod replicas in a Deployment, ReplicaSet, or StatefulSet. This delivers elastic, policy-driven scaling without human intervention, which is exactly what a traffic-driven microservices architecture requires.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Manually add more virtual machines during peak hours
Why it's wrong here
Manual VM addition is reactive and human-triggered, so it cannot scale dynamically with traffic in real time. It is tempting because adding VMs does increase capacity, and it would suit predictable, scheduled peaks, but microservices demand automated horizontal scaling driven by live metrics.
- ✗
Deploy a monolithic application on a single large instance
Why it's wrong here
A monolithic application on one large instance contradicts the microservices architecture and offers no per-service dynamic scaling. It is tempting as a simple deployment model, and would be correct for a small application with steady load, but it cannot scale individual services independently as traffic changes.
- ✓
Kubernetes with Horizontal Pod Autoscaler
Why this is correct
The Horizontal Pod Autoscaler adjusts replica counts from observed metrics such as CPU or request rate, letting microservices scale elastically with traffic. Kubernetes supplies the orchestration and scheduling layer, satisfying the dynamic-scaling requirement without manual intervention.
- ✗
Use a single large instance with a load balancer
Why it's wrong here
A single large instance with a load balancer scales vertically and distributes traffic, but cannot scale individual microservices dynamically per demand. It is tempting because load balancers front microservices, yet horizontal pod autoscaling, not one fixed instance, satisfies the dynamic scaling requirement.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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