DBS-C01 Workload-Specific Database Design Practice Question
A financial services company runs an Amazon Aurora MySQL database. The application performs complex joins and aggregations on large tables, causing high CPU utilization on the writer instance. The team wants to reduce load without changing the application code. Which solution would best address this issue?
⚠ Common exam trap
A common mix-up: candidates confuse scaling compute capacity (Aurora Serverless v2) with offloading read traffic, but only read replicas directly reduce CPU load on the writer by moving read-heavy operations to separate instances.
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
✓
Create one or more Aurora Replicas and route read traffic to them.
Creating one or more Aurora Replicas and routing read traffic to them offloads the complex joins and aggregations from the writer instance, reducing CPU utilization without requiring application code changes. Aurora Replicas share the same underlying storage volume as the writer, so they serve read queries with minimal replication lag while the writer focuses on write operations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create one or more Aurora Replicas and route read traffic to them.
Why this is correct
Read replicas offload SELECT queries from the writer.
- ✗
Switch to asynchronous replication to reduce load on the primary.
Why it's wrong here
Aurora replication is already asynchronous; this does not help.
- ✗
Enable Aurora Auto Scaling to increase storage capacity.
Why it's wrong here
Auto Scaling is for storage, not compute; does not reduce CPU.
- ✗
Migrate to Aurora Serverless v2 for automatic scaling.
Why it's wrong here
Serverless may not handle complex joins efficiently; scaling latency may be an issue.
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