Quick Answer
The answer is the AverageActiveConnections metric. Aurora Auto Scaling for readers uses this metric to monitor the average number of active connections per reader instance, and when it exceeds a defined threshold, the service automatically adds new read replicas to distribute the load. This is the correct trigger because scaling is driven by connection pressure on existing readers, not by CPU utilization or latency, which are symptoms rather than direct scaling signals. On the AWS Certified Database Specialty DBS-C01 exam, this question tests your understanding that Aurora Auto Scaling is connection-based, not performance-based—a common trap is confusing ReadLatency or CPU metrics as triggers. Remember the memory tip: “Connections count, not CPU clout” to recall that AverageActiveConnections is the key metric for scaling out readers.
This DBS-C01 practice question tests your understanding of monitoring and troubleshooting. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company has an Amazon Aurora MySQL DB cluster with one writer and two readers. The application is reporting increased read latency. The DB cluster is using Aurora Auto Scaling for readers. Which metric should be used to trigger scaling out readers?
ReadLatency
Why wrong: ReadLatency is a symptom of load, not a direct metric for scaling decisions.
ReaderNodeCPU
Why wrong: ReaderNodeCPU is not a standard CloudWatch metric for Aurora auto scaling.
CPUUtilization
Why wrong: CPUUtilization is not the default metric for reader auto scaling; it is based on connections.
AverageActiveConnections
Aurora Auto Scaling uses the number of active connections to the reader to add or remove readers.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AverageActiveConnections
Aurora Auto Scaling for readers uses the 'AverageActiveConnections' metric to determine when to add readers. Option B is correct. Option A is incorrect because the auto scaling is based on connections, not CPU. Option C is incorrect because ReaderNodeCPU is not a predefined metric for auto scaling. Option D is incorrect because ReadLatency is an effect, not a scaling trigger.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
ReadLatency
Why it's wrong here
ReadLatency is a symptom of load, not a direct metric for scaling decisions.
ReaderNodeCPU
Why it's wrong here
ReaderNodeCPU is not a standard CloudWatch metric for Aurora auto scaling.
CPUUtilization
Why it's wrong here
CPUUtilization is not the default metric for reader auto scaling; it is based on connections.
AverageActiveConnections
Why this is correct
Aurora Auto Scaling uses the number of active connections to the reader to add or remove readers.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which DBS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Monitoring and Troubleshooting — This question tests Monitoring and Troubleshooting — Read the scenario before looking for a memorised answer..
The correct answer is: AverageActiveConnections — Aurora Auto Scaling for readers uses the 'AverageActiveConnections' metric to determine when to add readers. Option B is correct. Option A is incorrect because the auto scaling is based on connections, not CPU. Option C is incorrect because ReaderNodeCPU is not a predefined metric for auto scaling. Option D is incorrect because ReadLatency is an effect, not a scaling trigger.
Identify which DBS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
This DBS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DBS-C01 exam.
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