A company hosts a production MySQL database on an Amazon Aurora single-node DB cluster. The database is queried heavily for reporting purposes. The DB cluster is experiencing periods of performance…

Question

Options

• ACreate an Aurora Replica node. Create an Auto Scaling policy to scale replicas based on CPU
• BCreate a second Aurora MySQL single-node DB cluster in a second Availability Zone. Ensure that
• CCreate an AWS Lambda function that caches reporting requests. Ensure that all reporting
• DCreate a multi-node Amazon ElastiCache cluster. Ensure that all reporting requests use the

• A
  75% (49)
• B
  6% (4)
• C
  3% (2)
• D
  15% (10)

Explanation

Explanation

Option A is correct because creating an Aurora Replica offloads read-heavy reporting queries from the primary (write) node, directly addressing both the high CPU utilization and maximum connections errors. Aurora Auto Scaling automatically adds or removes replicas based on CPU load, ensuring the cluster can handle variable reporting demand without degrading production write performance.

Option B is wrong because simply creating a second single-node cluster in another AZ does not automatically distribute query load - it would require manual failover logic and doesn't natively balance reads between nodes like Aurora Replicas do.

Option C is wrong because a Lambda function adds architectural complexity and is not designed to serve as a database caching layer; it introduces latency and doesn't natively solve connection limits or CPU pressure at the database level.

Option D is wrong because while ElastiCache can cache read queries, it requires significant application-layer changes to implement properly, and the question is asking for a database stability solution - Aurora Replicas are the more direct and AWS-native answer.

Memory Tip: Think "Read Replicas = Read Relief." Whenever you see reporting queries causing CPU spikes on a primary Aurora node, your first instinct should be Aurora Replica + Auto Scaling - separate the readers from the writers!

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