CLF-C02 Billing, Pricing, and Support Practice Question
A company runs a mix of Amazon EC2 instances across multiple AWS Regions to support its e-commerce platform. The finance team wants to reduce compute costs by right-sizing resources. They need a managed tool that analyzes historical CPU and memory utilization over 30 days, uses machine learning to identify over-provisioned and under-provisioned instances, and provides actionable recommendations to adjust instance sizes. Which AWS tool should the finance team use?
⚠ Common exam trap
A common mix-up: candidates confuse AWS Cost Explorer's cost-based rightsizing recommendations (which are purely financial) with Compute Optimizer's utilization-based ML recommendations, leading them to select Cost Explorer despite the question explicitly requiring CPU and memory analysis.
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 managed service that uses machine learning to analyze historical utilization metrics (CPU, memory, etc.) over up to 93 days, identifies over-provisioned and under-provisioned EC2 instances, and generates actionable rightsizing recommendations. The question specifically requires a tool that analyzes 30 days of historical CPU and memory data with ML-driven insights, which aligns exactly with Compute Optimizer's core functionality.
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 Trusted Advisor
Why it's wrong here
AWS Trusted Advisor provides cost optimization checks that include identifying idle instances and instances with low utilization, but it does not use machine learning to provide detailed right-sizing recommendations based on 30-day utilization patterns. Its recommendations are based on simple thresholds (e.g., CPU utilization less than 10% for 14 days) rather than comprehensive ML analysis.
When this WOULD be correct
A company wants a single dashboard to check for unused resources, idle instances, and other cost-saving opportunities based on AWS best practices, without needing ML-based right-sizing. Trusted Advisor would be the correct tool for that scenario.
- ✗
AWS Cost Explorer
Why it's wrong here
AWS Cost Explorer is a tool for visualizing, understanding, and managing AWS costs and usage over time. It provides cost and usage graphs, forecasting, and resource-level granularity, but it does not generate right-sizing recommendations for EC2 instances. It is primarily a cost analysis tool, not an optimization recommendation engine.
When this WOULD be correct
A finance team wants to visualize and analyze their AWS spending over time, identify cost trends, and break down costs by service or linked account to understand where money is being spent.
- ✓
AWS Compute Optimizer
Why this is correct
AWS Compute Optimizer is a service that uses machine learning to analyze historical utilization metrics (CPU, memory, network throughput) for EC2 instances and other resources. It identifies over- and under-provisioned instances and provides specific recommendations to change instance types or sizes to reduce costs or improve performance. This directly matches the finance team's requirement for ML-based right-sizing based on 30-day utilization data.
- ✗
AWS Budgets
Why it's wrong here
AWS Budgets is a service that allows you to set custom spending thresholds and receive alerts when costs or usage exceed (or are forecast to exceed) the budgeted amount. It does not analyze instance utilization or provide recommendations for resizing instances. Its purpose is cost tracking and alerting, not optimization.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The CLF-C02 exam frequently reuses these exact scenarios with slightly different constraints.
✓AWS Compute OptimizerCorrect answer▾
Why this is correct
AWS Compute Optimizer is a service that uses machine learning to analyze historical utilization metrics (CPU, memory, network throughput) for EC2 instances and other resources. It identifies over- and under-provisioned instances and provides specific recommendations to change instance types or sizes to reduce costs or improve performance. This directly matches the finance team's requirement for ML-based right-sizing based on 30-day utilization data.
✗AWS Trusted AdvisorWrong answer — click to see why▾
Why this is wrong here
AWS Trusted Advisor provides general best-practice checks for cost optimization, but it does not use machine learning to analyze historical CPU and memory utilization over 30 days to right-size instances. It offers static recommendations based on rules, not ML-driven analysis.
★ When this WOULD be the correct answer
A company wants a single dashboard to check for unused resources, idle instances, and other cost-saving opportunities based on AWS best practices, without needing ML-based right-sizing. Trusted Advisor would be the correct tool for that scenario.
Why candidates choose this
Candidates may confuse Trusted Advisor's cost optimization checks with the more advanced, ML-based right-sizing capabilities of Compute Optimizer, assuming any cost recommendation tool can do the job.
✗AWS Cost ExplorerWrong answer — click to see why▾
Why this is wrong here
AWS Cost Explorer provides cost and usage data but does not analyze historical CPU/memory utilization or use machine learning to right-size instances; it lacks the specific resource utilization analysis needed.
★ When this WOULD be the correct answer
A finance team wants to visualize and analyze their AWS spending over time, identify cost trends, and break down costs by service or linked account to understand where money is being spent.
Why candidates choose this
Candidates may confuse cost analysis tools with resource optimization tools, assuming Cost Explorer's cost data can directly inform right-sizing decisions without needing utilization metrics.
Analysis generated from the official CLF-C02blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.