A DynamoDB table stores device status items. The partition key is deviceId, and the partition distribution is healthy (no single partition dominates). However, during peak periods the application experiences high read latency because many clients repeatedly request the latest status for the same devices. Which action best improves read latency without changing the DynamoDB partitioning model?

Change the partition key to a random value for each request to eliminate hot partitions.

The scenario states partition distribution is already healthy, so randomizing the partition key does not target the actual problem (repeat reads of the same items). It also breaks the access pattern because the application can no longer reliably request items by deviceId, and it can reduce usability and query correctness.

Increase write capacity only, because writes generally determine read latency in DynamoDB.

Write capacity does not directly address read latency for repeatedly accessed items. Read latency is primarily influenced by read capacity, item size, network latency, and whether reads are being accelerated via caching (such as DAX). Increasing writes may increase overall workload contention without fixing the repeated-read issue.

Create an additional Global Secondary Index (GSI) and read exclusively from the index to accelerate reads.

A GSI can support alternate query patterns or access paths, but it does not provide caching for repeated point reads. Creating a GSI changes how items are accessed and billed; it is not as direct as using DAX to reduce latency for repeated reads of the same keys.

What does this SAA-C03 question test?

Static NAT maps one inside address to one outside address.

What is the correct answer to this question?

The correct answer is: Add Amazon DAX as a caching layer in front of DynamoDB and route repeated read operations through DAX. — Because the partitioning model is already healthy, the latency issue is driven by repeated reads for the same items. Amazon DAX is specifically designed to cache DynamoDB read results in memory, which dramatically reduces latency for hot read patterns without requiring a change to partition keys or the data model. Routing those repeated “latest status” reads through DAX improves read latency while preserving the existing partitioning strategy. Why others are wrong: Randomizing the partition key attacks the wrong symptom and undermines the ability to access items by deviceId. Increasing write capacity does not address read-path latency caused by repeated reads. Adding a GSI may improve certain query patterns, but it does not inherently reduce latency for repeated point reads the way an in-memory caching layer does.

What should I do if I get this SAA-C03 question wrong?

Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.