Question 1,493 of 1,616
Development with AWS ServicesmediumMultiple ChoiceObjective-mapped

Enabling Auto Scaling with CPU Triggers to Reduce Latency

This DVA-C02 practice question tests your understanding of development with aws services. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 runs a Node.js application on AWS Elastic Beanstalk. The application experiences high latency during peak hours. The developer suspects that the environment's EC2 instances are under-provisioned. Which configuration change would MOST effectively address the latency issue with minimal cost increase?

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 Auto Scaling and configure scaling triggers based on CPU utilization.

Enabling Auto Scaling with CPU utilization triggers dynamically adds EC2 instances during peak hours, distributing the load and reducing latency without over-provisioning during off-peak times. This matches the symptom of under-provisioned instances and minimizes cost by scaling only when needed, unlike static solutions that waste resources.

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.

  • Place the environment behind an Application Load Balancer.

    Why it's wrong here

    A load balancer distributes traffic but does not add more instances.

  • Enable Auto Scaling and configure scaling triggers based on CPU utilization.

    Why this is correct

    Auto Scaling adds instances during high CPU usage and removes them when idle, optimizing cost and performance.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Change the instance type to a larger size in the environment configuration.

    Why it's wrong here

    Larger instances may be more expensive and not as cost-effective as scaling out.

  • Decrease the minimum number of instances in the Auto Scaling group.

    Why it's wrong here

    Decreasing instances reduces capacity, worsening latency.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse adding a load balancer (Option A) with solving capacity issues, but a load balancer only distributes traffic and does not increase compute resources, so latency remains if instances are saturated.

Detailed technical explanation

How to think about this question

Elastic Beanstalk manages an Auto Scaling group behind the scenes; configuring a scaling policy based on CPU utilization (e.g., add one instance when CPU > 70% for 5 minutes) ensures the application can handle bursts without manual intervention. Under the hood, Auto Scaling uses CloudWatch alarms to trigger scale-out events, and the cooldown period prevents thrashing, but developers must set appropriate thresholds to avoid scaling too aggressively or too slowly.

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

A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

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.

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FAQ

Questions learners often ask

What does this DVA-C02 question test?

Development with AWS Services — This question tests Development with AWS Services — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Enable Auto Scaling and configure scaling triggers based on CPU utilization. — Enabling Auto Scaling with CPU utilization triggers dynamically adds EC2 instances during peak hours, distributing the load and reducing latency without over-provisioning during off-peak times. This matches the symptom of under-provisioned instances and minimizes cost by scaling only when needed, unlike static solutions that waste resources.

What should I do if I get this DVA-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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Last reviewed: Jul 4, 2026

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This DVA-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 DVA-C02 exam.