An online bookstore uses Amazon Aurora MySQL as its backend database. After the online bookstore added a popular book to the online catalog, customers began reporting intermittent timeouts on the chec

Question

Options

• ATurn on Performance Insights for the Aurora MySQL database. Configure and turn on Amazon
• BCreate a CPU usage alarm. Select the CPU utilization metric for the DB instance. Create an
• CUse the Amazon RDS query editor to get the process ID of the query that is causing the database
• DUse the SELECT INTO OUTFILE S3 statement to query data from the database. Save the data

• A
  72% (18)
• B
  8% (2)
• C
  16% (4)
• D
  4% (1)

Explanation

Performance Insights is the purpose-built AWS tool for automatically detecting and diagnosing database performance issues - it visualizes database load, surfaces top SQL queries, and shows wait events like locking/row-level contention in a continuous, automated way, directly solving the checkout timeout problem.

Option B is wrong because a CPU utilization alarm only tells you the CPU is high - it cannot identify why (e.g., lock contention vs. a bad query), and lock waits don't necessarily spike CPU at all, making it the wrong metric for this scenario.

Option C is wrong because manually querying the RDS process list via the query editor is a reactive, one-time action - it does not automatically detect or diagnose issues, which is a key requirement.

Option D is wrong because SELECT INTO OUTFILE S3 is a data export command, not a monitoring or diagnostics tool - it has no relevance to detecting performance bottlenecks.

Memory tip: Think of Performance Insights as a "performance X-ray" - whenever an exam question asks for automatic detection + diagnosis of database slowdowns (locks, waits, slow queries), Performance Insights is almost always the answer. If the question says "manually investigate," think RDS process list or CloudWatch Logs instead.

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