Which set of steps should the database specialist take to obtain this information?
Navigate to RDS Performance Insights. Select the database that is associated with the application. Update the counter metrics to show top_sql. Update the time range to when the load test occurred. Review the top SQL statements.
Navigate to RDS Performance Insights. Select the database that is associated with the application. Update the time range to when the load test occurred. Change the slice to SQL. Review the top SQL statements.
Navigate to Amazon CloudWatch. Select the metrics for the appropriate DB instance. Review the top SQL statements metric for the time range when the load test occurred. Create a CloudWatch dashboard to watch during future load tests.
Navigate to Amazon CloudWatch. Find the log group for the application’s database. Review the top-sql-statements log file for the time range when the load test occurred.
Explanations:
Although Performance Insights is a valid tool, selecting “top_sql” under counter metrics is not the right approach. The correct way to review the top SQL statements in Performance Insights is by using the “SQL” slice, not a counter metric.
This option correctly recommends using RDS Performance Insights, selecting the relevant database, setting the time range, and changing the slice to “SQL” to review the top SQL statements that consumed the most load during the test.
Amazon CloudWatch does not provide a “top SQL statements” metric. CloudWatch can track RDS performance metrics but does not directly show the SQL queries themselves. Performance Insights is the right tool for this task.
While CloudWatch logs may capture information from RDS, they do not specifically offer a “top-sql-statements” log file. Performance Insights is a better tool for identifying slow SQL queries.
From what I’ve heard, the answer is:
Navigate to RDS Performance Insights. Select the database that is associated with the application. Update the time range to when the load test occurred. Change the slice to SQL. Review the top SQL statements.