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CV0-004 Practice Question: A cloud architect is designing a multi-tier web…
A cloud architect is designing a multi-tier web application that must handle sudden traffic spikes. The application layer is stateless, and the database layer is read-heavy with occasional writes. Which design best meets the requirement for elasticity and cost efficiency?
⚠ Common exam trap
CompTIA often tests the misconception that auto-scaling applies equally to all tiers, but the trap here is that databases are stateful and require careful replication strategies (like read replicas) rather than simple instance scaling, and candidates may confuse load balancers with database replication mechanisms.
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
✓
Use auto-scaling for the application tier and read replicas for the database
Auto-scaling the stateless application tier dynamically adds or removes instances based on CPU or request metrics, directly handling traffic spikes without over-provisioning. For the read-heavy database tier, read replicas offload SELECT queries from the primary database, improving read throughput and cost efficiency by scaling horizontally only when needed, while the primary handles occasional writes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use auto-scaling for the application tier and read replicas for the database
Why this is correct
Auto-scaling matches capacity to demand for the stateless application tier, satisfying elasticity without over-provisioning. Read replicas offload read-heavy traffic from the primary database, improving throughput while writes remain on the primary. Together they deliver horizontal scaling and cost efficiency, since resources track actual load rather than peak estimates.
- ✗
Implement auto-scaling for the database tier and use a larger application instance
Why it's wrong here
Auto-scaling the database tier does not relieve a read-heavy load, since writes cannot be spread across replicas, and a fixed larger application instance cannot flex with spikes. It is tempting because auto-scaling is the elasticity mechanism, and would be right when the stateless application tier, not the database, must absorb variable demand.
- ✗
Use a load balancer to distribute traffic to multiple database instances
Why it's wrong here
A load balancer spreads connections across identical database nodes; it cannot serve read-heavy traffic from replicas or absorb write spikes, and the database remains the bottleneck. It is tempting because load balancing is the standard elasticity pattern for stateless tiers, and would be right for scaling the stateless application layer.
- ✗
Deploy large application and database instances to handle peak load
Why it's wrong here
Fixed large instances provide capacity for a known peak, not elasticity; during sudden spikes they still saturate, and outside peaks you pay for idle capacity. It is tempting because vertical scaling is quick and needs no architectural change, and would suit a steady, predictable workload rather than spiky, cost-sensitive traffic.
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