A company uses Amazon RDS for MySQL as the database for a critical application. The database workload is mostly writes, with a small number of reads. A data engineer notices that the CPU utilization…

Amazon RDS Performance Insights helps identify the top SQL queries, wait events, and hosts contributing to high CPU utilization, allowing targeted optimization efforts to address the root cause of performance issues. By pinpointing inefficient queries, the data engineer can then optimize them to reduce CPU load.

Modifying the database schema to include additional tables and indexes could potentially make the problem worse if not carefully planned or if inefficiently designed, as adding indexes consumes resources and tables increase complexity.

Rebooting an RDS DB instance weekly provides only temporary relief and does not address the underlying cause of high CPU utilization, which will likely return as the workload continues.

Upgrading to a larger instance size, such as one with more vCPUs, provides additional processing capacity for the database, which can directly alleviate high CPU utilization caused by heavy workloads that exceed the current instance's capabilities. This provides immediate relief for CPU-bound instances.

Implementing caching primarily reduces read query load, but the problem states the workload is 'mostly writes,' so caching would not significantly address the high CPU utilization caused by write operations.