Reducing RDS MySQL High CPU for Write-Heavy Workloads
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 of the DB instance is very high. The high CPU utilization is slowing down the application. The data engineer must reduce the CPU utilization of the DB Instance. Which actions should the data engineer take to meet this requirement? (Choose two.)
Community Votes
76% of anonymous learners picked answer AD. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The question tests diagnosing and resolving database performance bottlenecks, with the common trap being the selection of caching (E) which primarily benefits read-heavy workloads.
This page explains how to reduce high CPU utilization on an Amazon RDS for MySQL instance with a write-heavy workload, establishing that A and D are the correct actions.
Many candidates incorrectly choose E (Implement caching) because it is a common database optimization, but caching does not effectively reduce CPU load for write-dominant transactions.
Community Discussion (7 comments)
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Expert Analysis
Why the Answer Is Correct
To address high CPU utilization in a write-heavy RDS MySQL environment, you must first identify the root cause and then scale resources. Option A is correct because AWS documentation explicitly recommends using Performance Insights to identify queries causing high load before optimizing them; this is the standard diagnostic step. Option D is correct because if the workload exceeds the current instance's compute capacity, upgrading to a larger instance size provides the necessary CPU power to handle the increased write volume.Why the Other Options Are Wrong
Option B is incorrect because modifying schema without data indicates speculative changes that may not address the specific query causing the spike. Option C is invalid as rebooting does not solve persistent performance issues and causes downtime. Option E is incorrect because caching (like ElastiCache) reduces read latency and load, but since the workload is mostly writes, caching has minimal impact on the CPU utilization driven by write operations.Community Comment Notes
Community consensus strongly supports AD, with users noting that caching does not solve write-heavy issues. One user referenced the official AWS knowledge center article on high CPU, confirming that diagnosis via Performance Insights is the recommended first step. Another commenter emphasized that options improving read performance should be eliminated given the write-dominant nature of the workload.Official Reference
Exam Strategy
Always align your solution with the specific workload characteristics described (e.g., write-heavy vs. read-heavy). For performance issues, prioritize diagnosis (Performance Insights) and scaling (instance upgrade) over speculative schema changes or irrelevant optimizations like caching.
Frequently Asked Questions
Why is caching not effective for write-heavy RDS workloads?
Caching stores frequently accessed data to reduce database reads. Since write-heavy workloads generate most traffic through insert/update operations, caching cannot significantly offload the CPU burden from these transactional processes.
Is upgrading the instance always the best first step?
No. You should always diagnose first using Performance Insights (Option A) to ensure the issue isn't just inefficient queries. Upgrading (Option D) is the corrective action if the workload legitimately exceeds the current instance's capacity after optimization.
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