DEA-C01 Data Store Management Practice Question
A company runs a MySQL-compatible Amazon Aurora database for its e-commerce platform. The database experiences high write latency during peak hours. The application performs frequent INSERT and UPDATE operations on a table with 50 million rows. The DB instance is db.r5.large with 500 GB of Provisioned IOPS storage. A recent performance analysis shows that the average queue depth is consistently above 32 and write latency exceeds 50 ms. The company needs to reduce write latency without changing the application code. What should a data engineer do?
⚠ Common exam trap
Watch out — candidates often confuse read scaling solutions (Auto Scaling, read replicas) with write performance improvements, or assume that Aurora Serverless v2 automatically solves all performance issues without considering that write latency is often tied to instance size and storage configuration.
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
✓
Resize the DB instance to a larger instance type such as db.r5.xlarge.
The high queue depth (consistently above 32) and write latency exceeding 50 ms indicate that the current db.r5.large instance is CPU or I/O constrained for the write workload. Resizing to a larger instance type such as db.r5.xlarge increases the available vCPUs, memory, and network bandwidth, which directly reduces queue depth and write latency by allowing more concurrent write operations to be processed. This solution does not require application code changes and addresses the root cause of insufficient compute capacity for the frequent INSERT and UPDATE operations on the 50-million-row table.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable Aurora Auto Scaling to automatically add reader instances.
Why it's wrong here
Auto Scaling adds read replicas, which does not reduce write latency on the primary instance.
- ✗
Convert the cluster to Aurora Serverless v2 to automatically scale compute capacity.
Why it's wrong here
Aurora Serverless v2 scales compute, but may introduce latency during scaling events and does not directly address the specific performance issue with Provisioned IOPS.
- ✓
Resize the DB instance to a larger instance type such as db.r5.xlarge.
Why this is correct
Increasing instance size provides more CPU and memory, reducing queue depth and write latency.
- ✗
Create a read replica and configure the application to offload read queries.
Why it's wrong here
Read replicas offload reads but do not affect write performance on the primary.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services 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 DEA-C01 exam.