DEA-C01 Data Store Management Practice Question
A company uses Amazon DynamoDB to store session data for a web application. The application experiences sudden spikes in traffic, causing occasional throttling errors. The data engineer needs to handle these spikes without over-provisioning capacity. What is the MOST cost-effective solution?
⚠ Common exam trap
Watch out — candidates often confuse DynamoDB on-demand mode (option D) as the default solution for unpredictable traffic, but the exam tests cost optimization—on-demand is premium-priced per request, while Auto Scaling with provisioned capacity is more cost-effective for workloads with variable but not extreme traffic patterns.
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
✓
Configure DynamoDB Auto Scaling to automatically adjust provisioned capacity.
DynamoDB Auto Scaling (option C) is the most cost-effective solution because it automatically adjusts the provisioned read/write capacity based on actual traffic patterns, handling sudden spikes without manual intervention or over-provisioning. This avoids paying for unused capacity during low-traffic periods while still accommodating bursts within the configured limits.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set up a TTL (Time to Live) attribute to automatically delete old session data.
Why it's wrong here
TTL helps manage storage costs but does not affect capacity throttling.
- ✗
Enable DynamoDB Accelerator (DAX) to cache read requests.
Why it's wrong here
DAX reduces read latency but does not prevent throttling due to write capacity limits.
- ✓
Configure DynamoDB Auto Scaling to automatically adjust provisioned capacity.
Why this is correct
Auto Scaling dynamically adapts to traffic patterns, preventing throttling and reducing cost.
- ✗
Switch to DynamoDB on-demand mode.
Why it's wrong here
On-demand mode can handle spikes but is usually more expensive for workloads with predictable traffic patterns.
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