Which solution will meet these requirements?
Turn on Performance Insights for the Aurora MySQL database. Configure and turn on Amazon DevOps Guru for RDS.
Create a CPU usage alarm. Select the CPU utilization metric for the DB instance. Create an Amazon Simple Notification Service (Amazon SNS) topic to notify the database specialist when CPU utilization is over 75%.
Use the Amazon RDS query editor to get the process ID of the query that is causing the database to lock. Run a command to end the process.
Use the SELECT INTO OUTFILE S3 statement to query data from the database. Save the data directly to an Amazon S3 bucket. Use Amazon Athena to analyze the files for long-running queries.
Explanations:
Enabling Performance Insights for Aurora MySQL provides detailed database performance metrics, helping to detect and diagnose performance issues. Combining this with Amazon DevOps Guru for RDS allows for proactive monitoring and automated analysis of database performance, helping to identify and resolve bottlenecks.
A CPU usage alarm alerts on CPU utilization but does not specifically address locking contention or database performance issues. It only triggers based on CPU usage, which may not correlate directly with the locking problems affecting the checkout page.
While identifying and ending the locking query may provide a short-term fix, this solution is not automated and does not address the root cause of the locking contention. It is not scalable or effective in the long term for diagnosing or preventing performance issues.
UsingSELECT INTO OUTFILEto export data and then analyzing it with Athena does not provide a direct solution to diagnosing locking contention or resolving database performance issues. This process is more about data extraction and analysis, not about real-time performance monitoring and automatic resolution of bottlenecks.
I systematize that the answer is:
Turn on Performance Insights for the Aurora MySQL database. Configure and turn on Amazon DevOps Guru for RDS.