DVA-C02 Troubleshooting and Optimization Practice Question
A developer is using Amazon DynamoDB for a new application. The developer wants to reduce read latency. Which design pattern should the developer use?
⚠ Common exam trap
Many exam-takers confuse increasing provisioned capacity (Option B) with reducing latency, when in fact it only increases throughput, while DAX (Option D) directly addresses latency by caching reads in memory.
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
✓
Use DynamoDB Accelerator (DAX) as a cache for frequently read items.
DynamoDB Accelerator (DAX) is an in-memory cache designed specifically for DynamoDB, providing microsecond read latency for frequently accessed items. By caching read-heavy workloads, DAX offloads requests from the DynamoDB table, reducing read latency without requiring application-level caching logic. This directly addresses the developer's goal of reducing read latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a global secondary index (GSI) for the table.
Why it's wrong here
While a Global Secondary Index (GSI) allows for querying data using attributes other than the primary key, it does not inherently reduce the read latency for existing query patterns on the base table. GSIs are primarily designed to enable diverse access patterns and support different query needs, introducing eventual consistency and additional write costs, rather than speeding up direct primary key lookups.
- ✗
Increase the provisioned read capacity units (RCUs) for the table.
Why it's wrong here
Increasing provisioned Read Capacity Units (RCUs) primarily prevents throttling and ensures that DynamoDB can sustain a higher volume of read requests per second, thereby improving throughput. However, RCUs do not reduce the intrinsic latency of individual read operations from the underlying storage layer; they manage the capacity for concurrent requests, not the speed of a single request.
- ✗
Use DynamoDB Global Tables to replicate data to multiple regions.
Why it's wrong here
DynamoDB Global Tables provide multi-region, active-active replication, enhancing application availability and disaster recovery by allowing users to read and write from the closest region. While this can reduce latency for geographically dispersed users accessing their nearest replica, it does not improve the read latency for an application operating within a single, specific AWS region.
- ✓
Use DynamoDB Accelerator (DAX) as a cache for frequently read items.
Why this is correct
DynamoDB Accelerator (DAX) is a fully managed, in-memory cache specifically designed to sit in front of DynamoDB tables, providing microsecond read latency for frequently accessed items. By caching read-heavy workloads, DAX significantly reduces the response time for repeated requests, offloading the DynamoDB table and improving application performance for read-intensive operations.
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