An application is experiencing performance issues based on increased demand. This increased demand is on read-only historical records pulled from an Amazon RDS-hosted database with custom views and qu

Question

Options

• ADeploy Amazon DynamoDB, move all the data, and point to DynamoDB.
• BDeploy Amazon ElastiCache (Redis OSS) and cache the data for the application.
• CDeploy Memcached on Amazon EC2 and cache the data for the application.
• DDeploy Amazon DynamoDB Accelerator (DAX) on Amazon RDS to improve cache performance.

• A
  8% (4)
• B
  67% (34)
• C
  4% (2)
• D
  22% (11)

Explanation

ElastiCache (Redis OSS) is the right fit here because it's a fully managed AWS caching service that sits in front of RDS, serving repeated read requests from memory instead of hitting the database - no schema changes required, and AWS handles patching, replication, and failover.

A is wrong because migrating to DynamoDB requires moving all data and rewriting queries/views to fit a NoSQL model - that's a major structural change, the opposite of what the question demands.

C is wrong because self-managed Memcached on EC2 maximizes management overhead: you own the OS, patching, scaling, and availability - exactly what the question tells you to minimize.

D is wrong because DAX (DynamoDB Accelerator) is an in-memory cache for DynamoDB, not RDS. You cannot deploy DAX on top of RDS - it's a DynamoDB-specific service.

Memory tip: When you see "RDS + read performance + minimize management," think ElastiCache as the managed caching layer. A quick rule: DAX = DynamoDB only, ElastiCache = everything else (RDS, app-level caching). If the question adds "self-managed," that's a trap pointing you toward EC2-based solutions, which always carry higher overhead.

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