- A
AWS Compute Optimizer
Correct. AWS Compute Optimizer uses machine learning to analyze historical utilization metrics and provides actionable rightsizing recommendations for EC2 instances, Auto Scaling groups, and EBS volumes, exactly matching the company's need for automated optimization.
- B
AWS Trusted Advisor
Why wrong: Incorrect. AWS Trusted Advisor inspects your AWS environment and makes recommendations in categories like cost optimization, performance, security, and fault tolerance. However, its cost optimization recommendations are generally higher-level (e.g., underutilized instances, reserved instance opportunities) and do not provide the same granular, per-instance rightsizing recommendations that AWS Compute Optimizer offers.
- C
AWS Cost Explorer
Why wrong: Incorrect. AWS Cost Explorer provides graphs and reports for analyzing your AWS costs and usage over time. It does not generate rightsizing recommendations based on resource utilization. It is a cost analysis tool, not a resource optimization tool.
- D
AWS Systems Manager
Why wrong: Incorrect. AWS Systems Manager provides a unified interface to manage operational tasks on AWS resources, including patching, automation, and inventory collection. While it can gather utilization data, it does not provide built-in rightsizing recommendations like AWS Compute Optimizer.
Quick Answer
The answer is AWS Compute Optimizer. This service is the correct choice because it uses machine learning to analyze historical utilization data—such as CPU, memory, and network I/O—across your EC2 instances, then automatically generates rightsizing recommendations to flag over-provisioned or under-provisioned resources, optimizing both cost and performance without manual monthly reviews. On the AWS Certified Cloud Practitioner CLF-C02 exam, this scenario tests your understanding of native AWS services that leverage historical metrics for automation, often appearing as a distractor against third-party tools or manual services like AWS Trusted Advisor (which gives general best-practice checks but not ML-driven rightsizing). A common trap is confusing Compute Optimizer with AWS Cost Explorer, but remember: Cost Explorer shows past spending, while Compute Optimizer predicts future sizing needs. Memory tip: “Compute Optimizer computes the right size.”
CLF-C02 Cloud Technology and Services Practice Question
This CLF-C02 practice question tests your understanding of cloud technology and services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 hundreds of Amazon EC2 instances for its application. The operations team manually reviews instance utilization metrics once a month to identify instances that are over-provisioned (e.g., using only 10% of CPU) or under-provisioned. They want to automate this analysis and receive rightsizing recommendations to optimize costs and performance. The solution must be natively provided by AWS and must use historical utilization data to generate recommendations. Which AWS service should the company use?
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
AWS Compute Optimizer
AWS Compute Optimizer is the correct choice because it is a native AWS service that uses machine learning to analyze historical utilization metrics (such as CPU, memory, and network) across EC2 instances and automatically generates rightsizing recommendations. It specifically identifies over-provisioned and under-provisioned instances to optimize both cost and performance, meeting the requirement for automated analysis based on historical data.
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.
- ✓
AWS Compute Optimizer
Why this is correct
Correct. AWS Compute Optimizer uses machine learning to analyze historical utilization metrics and provides actionable rightsizing recommendations for EC2 instances, Auto Scaling groups, and EBS volumes, exactly matching the company's need for automated optimization.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Trusted Advisor
Why it's wrong here
Incorrect. AWS Trusted Advisor inspects your AWS environment and makes recommendations in categories like cost optimization, performance, security, and fault tolerance. However, its cost optimization recommendations are generally higher-level (e.g., underutilized instances, reserved instance opportunities) and do not provide the same granular, per-instance rightsizing recommendations that AWS Compute Optimizer offers.
- ✗
AWS Cost Explorer
Why it's wrong here
Incorrect. AWS Cost Explorer provides graphs and reports for analyzing your AWS costs and usage over time. It does not generate rightsizing recommendations based on resource utilization. It is a cost analysis tool, not a resource optimization tool.
- ✗
AWS Systems Manager
Why it's wrong here
Incorrect. AWS Systems Manager provides a unified interface to manage operational tasks on AWS resources, including patching, automation, and inventory collection. While it can gather utilization data, it does not provide built-in rightsizing recommendations like AWS Compute Optimizer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Trusted Advisor's cost optimization checks with detailed rightsizing recommendations, but Trusted Advisor does not analyze historical utilization data or provide instance-specific rightsizing suggestions like Compute Optimizer does.
Detailed technical explanation
How to think about this question
AWS Compute Optimizer ingests CloudWatch metrics (e.g., CPUUtilization, NetworkIn, NetworkOut, and memory utilization if the CloudWatch agent is installed) over a lookback period of up to 14 days, then applies machine learning models to compare observed utilization against instance family specifications. It generates recommendations with estimated cost savings and performance risk scores, and can also analyze Auto Scaling groups and Amazon EBS volumes. A subtle behavior is that Compute Optimizer requires at least 30 hours of historical data to generate recommendations, and it excludes instances with less than 24 hours of continuous utilization.
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
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FAQ
Questions learners often ask
What does this CLF-C02 question test?
Cloud Technology and Services — This question tests Cloud Technology and Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Compute Optimizer — AWS Compute Optimizer is the correct choice because it is a native AWS service that uses machine learning to analyze historical utilization metrics (such as CPU, memory, and network) across EC2 instances and automatically generates rightsizing recommendations. It specifically identifies over-provisioned and under-provisioned instances to optimize both cost and performance, meeting the requirement for automated analysis based on historical data.
What should I do if I get this CLF-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: Jun 11, 2026
This CLF-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 CLF-C02 exam.
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