DVA-C02 Troubleshooting and Optimization Practice Question
A developer is using Amazon DynamoDB as the database for a web application. The application experiences occasional spikes in traffic, and some write requests fail with a ProvisionedThroughputExceededException. What is the MOST cost-effective way to handle these spikes without manual intervention?
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
✓
Enable DynamoDB auto scaling for the table.
DynamoDB auto scaling automatically adjusts the provisioned read and write capacity based on actual traffic patterns, handling spikes without manual intervention and only paying for the capacity needed at peak times. Option A (on-demand mode) avoids capacity management but can be more expensive for predictable workloads or sustained traffic. Option C (increasing to peak) leads to over-provisioning and higher cost during low traffic. Option D (DAX) is a caching layer for reads, not writes, and does not address write throughput limitations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to on-demand mode for the table.
Why it's wrong here
On-demand capacity mode does eliminate throttling by billing per request regardless of volume, but it is priced roughly five to seven times higher per request than provisioned capacity, so for a workload with a generally predictable baseline and only occasional spikes it is not the most cost-effective remedy compared with scaling provisioned capacity dynamically.
- ✓
Enable DynamoDB auto scaling for the table.
Why this is correct
DynamoDB auto scaling continuously monitors consumed capacity through CloudWatch alarms and automatically raises or lowers the table's provisioned read and write capacity units within configured min/max bounds and a target utilization percentage, absorbing traffic spikes without manual intervention while keeping baseline costs lower than a flat over-provisioned or fully on-demand configuration.
- ✗
Increase the provisioned write capacity to the peak expected value.
Why it's wrong here
Manually raising provisioned write capacity to match the peak expected value guarantees enough throughput during spikes, but it forces the table to pay for that peak-level capacity around the clock even during long idle periods between spikes, making it the least cost-efficient of the available remedies.
- ✗
Use DynamoDB Accelerator (DAX) to cache writes.
Why it's wrong here
DynamoDB Accelerator (DAX) is an in-memory caching layer that reduces read latency by caching GetItem and Query results; it has no effect on write throughput or on ProvisionedThroughputExceededException errors triggered by write operations, since DAX does not cache, buffer, or absorb PutItem or UpdateItem capacity consumption.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 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 DVA-C02 exam.