SAP-C02 Question 642
Single answerYour company is running an e-commerce platform and uses Amazon DynamoDB as the primary database for its product catalog. Recently, the business team noticed degraded application performance during peak shopping hours. After investigation, you determined that the performance issues are related to throttling in DynamoDB due to high read traffic. What is the most cost-effective solution to resolve this issue?
- A
Enable DynamoDB Auto Scaling to automatically adjust the read capacity units based on traffic patterns.
- B
Use DynamoDB Accelerator (DAX) to cache frequently accessed items and reduce read traffic to the table.
- C
Increase the provisioned read capacity units of the DynamoDB table to handle peak traffic.
- D
Migrate the product catalog to Amazon RDS for better performance under high read workloads.
Show answer and explanation
Correct answer: B
Explanation
The most cost-effective solution to resolve throttling caused by high read traffic in DynamoDB is to use DynamoDB Accelerator (DAX). DAX is an in-memory caching service that improves performance by caching frequently accessed data, reducing the need for read operations directly on DynamoDB. This approach minimizes throttling and is more cost-effective than simply increasing provisioned capacity or migrating to a different database service.
- A. Incorrect.
While enabling Auto Scaling can help adjust read capacity dynamically, it may not address issues during sudden spikes in traffic and could lead to unnecessary costs during non-peak hours.
- B. Correct.
Using DynamoDB Accelerator (DAX) is a cost-effective solution as it provides a caching layer for DynamoDB, reducing the number of read requests to the table and alleviating throttling issues.
- C. Incorrect.
Increasing the provisioned read capacity units can handle the traffic but is less cost-effective compared to leveraging a caching solution like DAX.
- D. Incorrect.
Migrating to Amazon RDS is not necessary in this case, as DynamoDB with DAX can effectively handle high read workloads while maintaining cost efficiency.