Question 1,241 of 1,663
DBS-C01 Monitoring and Troubleshooting Practice Question
A company is troubleshooting an Amazon DynamoDB table that is experiencing high latency. The table uses on-demand capacity. Which TWO steps should be taken to diagnose the issue?
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
✓
Examine CloudWatch metrics for throttling and latency patterns
CloudWatch metrics for DynamoDB can show throttling events, latency patterns, and consumed throughput, which help diagnose high latency issues. Option C is correct because DynamoDB Accelerator (DAX) provides an in-memory cache that can significantly reduce read latency for frequently accessed items. Option A is incorrect because the table uses on-demand capacity, so adjusting provisioned capacity is not applicable. Option D is incorrect because disabling TTL does not directly reduce write overhead or latency. Option E is incorrect because DynamoDB handles partitions automatically and manual splitting is not supported.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the provisioned read capacity
Why it's wrong here
Increasing provisioned read capacity is not applicable for an on-demand table, and since the table uses on-demand, throttling is not caused by insufficient capacity.
- ✓
Examine CloudWatch metrics for throttling and latency patterns
Why this is correct
CloudWatch metrics provide insights into throttling, latency, and consumed capacity, which are essential for diagnosing performance issues.
- ✓
Consider using DynamoDB Accelerator (DAX) for caching
Why this is correct
DynamoDB Accelerator (DAX) is an in-memory cache that can reduce read latency, especially for frequently accessed items.
- ✗
Disable TTL to reduce write overhead
Why it's wrong here
Disabling TTL is unrelated to latency; TTL is for automatic item expiration and does not affect write overhead.
- ✗
Split the table into multiple partitions manually
Why it's wrong here
DynamoDB automatically manages partitions; manual splitting is neither supported nor necessary for performance troubleshooting.
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Last reviewed: Jun 20, 2026
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