The correct three actions are enabling Aurora Auto Scaling for the reader instances, adding more reader instances, and increasing the instance size of the existing reader instances. These choices directly address the core problem of high replica lag during a sales event by distributing the read workload and boosting the processing power of each reader. Replica lag in Aurora MySQL occurs when reader instances cannot keep up with the volume of write-ahead logs from the writer, often due to CPU saturation on the readers. By adding more readers and enabling Auto Scaling, you dynamically distribute the read queries, while larger instance sizes give each reader more CPU and memory to apply changes faster. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this scenario tests your understanding of Aurora’s read scaling architecture versus traditional MySQL replication. A common trap is to focus only on the writer or to suggest Multi-AZ failover, which does not reduce lag. Remember the three-legged stool: more readers, bigger readers, and automatic scaling.
SAP-C02 Continuous Improvement for Existing Solutions Practice Question
This SAP-C02 practice question tests your understanding of continuous improvement for existing solutions. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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.
An e-commerce company runs its application on Amazon EC2 instances behind an Application Load Balancer (ALB). The application uses an Amazon Aurora MySQL DB cluster with one writer and two reader instances. During a sales event, the database CPU utilization is high, and read replicas show high replica lag. The company needs to improve the read scalability and reduce replica lag. Which THREE actions should the company take? (Choose THREE.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add more reader instances to the cluster to distribute the read traffic.
Adding more reader instances (Option A) distributes the read workload across additional nodes, reducing the load on each reader and helping to lower replica lag. Aurora Auto Scaling (Option E) automatically adjusts the number of reader instances based on metrics like CPU utilization or replica lag, providing dynamic scaling during traffic spikes. Increasing the instance size of reader instances (Option D) provides more CPU and memory resources to each reader, enabling them to process more read queries and apply changes from the writer faster, which directly reduces replica lag.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Add more reader instances to the cluster to distribute the read traffic.
Why this is correct
More readers improve read scalability.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable Multi-AZ for the cluster to improve read availability.
Why it's wrong here
Multi-AZ does not improve read performance.
✗
Increase the instance size of the writer instance to improve write throughput.
Why it's wrong here
Writer size helps writes but not replica lag directly.
✓
Increase the instance size of the reader instances to larger instance types.
Why this is correct
Larger instances can handle more read load and reduce lag.
Related concept
Read the scenario before looking for a memorised answer.
✓
Enable Aurora Auto Scaling for the reader instances.
Why this is correct
Auto Scaling dynamically adjusts reader count based on load.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Multi-AZ with read scaling, but Multi-AZ in Aurora is for high availability only and does not distribute read traffic, while the real solutions involve adding more readers, scaling readers up, or using Auto Scaling to handle variable load.
Detailed technical explanation
How to think about this question
Aurora replicas share the same cluster volume as the writer, so replica lag is primarily due to the time it takes for the reader to apply redo log records from the writer, not data transfer. Larger reader instances have more vCPUs and memory, which accelerates the redo apply process. Aurora Auto Scaling uses CloudWatch metrics like 'AuroraReplicaLagMaximum' and 'CPUUtilization' to trigger scaling policies, adding or removing readers to maintain target lag thresholds.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Continuous Improvement for Existing Solutions — This question tests Continuous Improvement for Existing Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add more reader instances to the cluster to distribute the read traffic. — Adding more reader instances (Option A) distributes the read workload across additional nodes, reducing the load on each reader and helping to lower replica lag. Aurora Auto Scaling (Option E) automatically adjusts the number of reader instances based on metrics like CPU utilization or replica lag, providing dynamic scaling during traffic spikes. Increasing the instance size of reader instances (Option D) provides more CPU and memory resources to each reader, enabling them to process more read queries and apply changes from the writer faster, which directly reduces replica lag.
What should I do if I get this SAP-C02 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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