DOP-C02 Monitoring and Logging Practice Question
A company runs a critical e-commerce application on AWS. The architecture includes an Application Load Balancer (ALB) in front of an Auto Scaling group of EC2 instances running a web server, and an Amazon RDS MySQL Multi-AZ database. The DevOps team has implemented CloudWatch dashboards to monitor key metrics. Recently, customers have reported that the website becomes unresponsive for a few minutes during peak traffic hours. The team reviews the CloudWatch metrics and observes that during the incidents, the ALB's 'TargetResponseTime' metric spikes, and the RDS 'ReadLatency' and 'WriteLatency' metrics also spike. However, the EC2 CPU utilization and memory usage remain normal. The ALB health check shows 'Healthy' for all targets. The team needs to identify the root cause. Which course of action should the team take?
⚠ Common exam trap
The trap is chasing the loudest symptom — the ALB TargetResponseTime spike — and adding application-tier capacity, when the correlated RDS latency metrics reveal the database as the true bottleneck.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable Performance Insights on the RDS instance to analyze database performance and identify slow queries.
The symptoms — spiking ALB TargetResponseTime alongside spiking RDS ReadLatency and WriteLatency, with normal EC2 CPU/memory and healthy targets — point to a database bottleneck, most likely slow or inefficient queries. Performance Insights is the AWS-native tool for identifying top SQL statements, wait events, and database load contributors, so it directly addresses the root cause. Adding instances or listeners would not help because the bottleneck is downstream at the database, not at the application tier.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the ALB to add a second listener and distribute traffic across multiple target groups.
Why it's wrong here
This option misidentifies the bottleneck as the application layer. Adding a second listener and distributing traffic across multiple target groups changes how ALB routes to EC2 instances, but it does nothing to reduce the database load that is causing the latency. In fact, routing more concurrent requests to the same RDS instance can increase database contention and make the problem worse.
- ✗
Review the ALB access logs to identify if there are any unusual request patterns causing the latency.
Why it's wrong here
ALB access logs record HTTP request metadata such as timestamps, client IPs, request URIs, and the time taken for each request, but they do not expose database query execution plans, wait events, or RDS metrics like CPU and storage latency. While they can confirm that certain endpoints are slow, they cannot reveal whether the slowness stems from a bad SQL query, lock contention, or an undersized database instance. The latency is a symptom, and these logs only show the symptom's surface details.
- ✓
Enable Performance Insights on the RDS instance to analyze database performance and identify slow queries.
Why this is correct
Performance Insights for Amazon RDS is the direct diagnostic tool for database performance. It visualizes database load by wait states, SQL statements, and hosts, allowing you to quickly identify slow queries, lock waits, or I/O bottlenecks that are driving the ALB backend latency. This matches the scenario where application instances are healthy but the database is the constraint, making it the correct next step for root-cause analysis.
- ✗
Increase the desired capacity of the Auto Scaling group to add more EC2 instances to handle the load.
Why it's wrong here
Increasing the Auto Scaling group's desired capacity adds more EC2 instances to handle incoming requests, but the observed latency originates at the RDS layer. Replicating the application tier would increase the number of connections and queries hitting the same database, potentially overwhelming it further and exhausting its connection pool. Since the application servers are not saturated, horizontal scale-out does not address the actual performance bottleneck.
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Same concept, more angles
1 more way this is tested on DOP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A DevOps team is troubleshooting a performance issue where an Amazon RDS for PostgreSQL instance's CPU utilization spikes every hour. The team suspects a specific query from an application. Which combination of tools can identify the problematic query?
hard- A.CloudWatch Logs Insights and CloudWatch metrics.
- ✓ B.Amazon RDS Performance Insights and Enhanced Monitoring.
- C.VPC Flow Logs and Lambda.
- D.CloudTrail and CloudWatch alarms.
Why B: Amazon RDS Performance Insights is purpose-built to visualize database load (DBLoad) broken down by SQL statement, wait event, and user, so it can pinpoint the exact query causing hourly CPU spikes. Enhanced Monitoring provides OS-level metrics (per-process CPU, memory, disk I/O) at up to 1-second granularity, letting the team correlate the spike with the specific PostgreSQL backend process. Together they identify both the offending SQL and the resource it consumes.
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This DOP-C02 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 DOP-C02 exam.