Q46 — AWS DVA-C02 Ch.1

Question 46 of 100 | ← Chapter 1

A company is building a stock trading application. The application requires sub-millisecond latency for processing trade requests. The company uses Amazon DynamoDB to store all trade data required for processing each trade request. A development team conducted load testing and found data retrieval times exceeded expectations. The team needs a solution that reduces data retrieval time with minimal engineering effort. Which solution meets these requirements?

• A. Add a Local Secondary Index (LSI) to the trade data.
• B. Store trade data in Amazon S3 and use S3 Transfer Acceleration.
• C. Add exponential backoff retries to DynamoDB queries.
• D. Use DynamoDB Accelerator (DAX) to cache trade data. ✓

Correct Answer: D. Use DynamoDB Accelerator (DAX) to cache trade data.

Explanation

Option D recommends using DynamoDB Accelerator (DAX) to cache trade data. DAX is a fully managed, in-memory caching service that delivers high performance and ultra-low-latency data retrieval. By caching trade data in DAX, the application can meet sub-millisecond latency requirements for trade request processing without requiring extensive modifications to application code. Other options have limitations: Option A—adding a Local Secondary Index (LSI) may improve performance somewhat, but likely insufficient for sub-millisecond latency. Option B—storing trade data in Amazon S3, while viable for storage, is less effective than DAX for achieving ultra-low-latency retrieval. Option C—adding exponential backoff retries handles query failures but does not directly reduce data retrieval latency. 【Lantern Certification provided by: swufelp1999】