Explanation:
The correct answer is B: Implement an Amazon ElastiCache for Redis cluster to cache frequently accessed data from the RDS database, reducing direct database load. During high-traffic events like a flash sale, caching frequently accessed data helps minimize the load on the RDS DB instance. By storing data in an in-memory cache, frequent read operations can bypass the database, thereby improving application performance and reducing CPU utilization on the database server. Options A, C, and D provide potential improvements but do not address the root cause of high read traffic on the RDS instance as effectively as using ElastiCache for Redis.
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An e-commerce company operates an application on AWS, utilizing Amazon API Gateway to invoke AWS Lambda functions. The application's data is managed in an Amazon RDS for PostgreSQL database instance. During a recent flash sale event, the application experienced degraded performance due to a surge in API calls. Upon reviewing Amazon CloudWatch metrics, a solutions architect identified a sharp rise in Lambda invocations, database connections, and high CPU utilization on the DB instance. What measures should the solutions architect propose to enhance the application's performance under such high-traffic conditions?
A
Increase the memory allocation for the Lambda function and ensure the function closes database connections immediately after data retrieval.
B
Implement an Amazon ElastiCache for Redis cluster to cache frequently accessed data from the RDS database, reducing direct database load.
C
Establish an RDS proxy through the Lambda console and reconfigure the Lambda function to utilize this proxy endpoint for database connections.
D
Adjust the Lambda function to establish database connections outside of the function handler and verify the existence of an active connection before creating a new one.
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