CLF-C02 Billing, Pricing, and Support Practice Question
A company runs a production web application on a fleet of Amazon EC2 instances. The operations team has observed that most instances have an average CPU utilization below 10% over the past month. They want to receive automated, ML-based recommendations for downsizing these instances to smaller instance types to reduce costs without compromising performance. The team also wants to see the estimated monthly savings for each recommendation. Which AWS service should the operations team use?
⚠ Common exam trap
It's easy for candidates to confuse AWS Trusted Advisor's cost optimization checks with the ML-driven rightsizing capabilities of AWS Compute Optimizer, but Trusted Advisor does not provide per-instance, ML-based recommendations with estimated savings.
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 service because it uses machine learning to analyze historical utilization metrics (such as CPU, memory, and network) of EC2 instances and provides actionable recommendations to downsize or rightsize instances. It specifically generates estimated monthly savings for each recommendation, directly addressing the need for automated, ML-based downsizing suggestions without compromising performance.
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 includes a cost-optimization check for underutilized EC2 instances, but that check relies on simple, rule-based thresholds—for example, average CPU utilization below a specific percentage over a set number of days—rather than machine learning. It flags broad categories of idle or low-utilization instances and does not provide instance-specific right-sizing recommendations or itemized savings estimates for downsizing choices.
When this WOULD be correct
A company wants a one-time assessment of their AWS account against best practices, including cost optimization, security, and fault tolerance, without needing ML-driven or historical utilization analysis.
- ✗
AWS Cost Explorer
Why it's wrong here
AWS Cost Explorer visualizes historical cost and usage data with powerful filtering and grouping, and it provides Reserved Instance and Savings Plans purchase recommendations based on aggregate spend patterns. However, it does not examine instance-level resource utilization such as CPU or memory, so it cannot recommend changing an existing On-Demand instance to a smaller size, and it offers no right-sizing analysis.
When this WOULD be correct
AWS Cost Explorer would be correct if the question asked for a service to visualize historical EC2 spending, identify cost trends, or create custom cost reports to manually analyze downsizing opportunities, without requiring ML-based recommendations.
- ✓
AWS Compute Optimizer
Why this is correct
AWS Compute Optimizer applies machine learning to analyze historical utilization metrics—CPU, memory, EBS I/O, and network—for each EC2 instance, then recommends the most cost-efficient instance type and size, including downsizing opportunities. It delivers per-instance findings with projected monthly savings and expected performance impact, making it the only option here that directly performs ML-based right-sizing for production workloads.
- ✗
AWS Budgets
Why it's wrong here
AWS Budgets is a cost governance tool that triggers alerts when actual or forecasted spend exceeds user-defined dollar or usage thresholds. It neither ingests per-instance utilization telemetry nor generates any instance-type or size recommendations, so it cannot identify or quantify downsizing opportunities for an EC2 fleet.
When this WOULD be correct
A company wants to set a monthly spending limit for its EC2 usage and receive notifications when costs approach or exceed that limit. AWS Budgets would be the correct service to create a cost budget with alerts.
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 applies machine learning to analyze historical utilization metrics—CPU, memory, EBS I/O, and network—for each EC2 instance, then recommends the most cost-efficient instance type and size, including downsizing opportunities. It delivers per-instance findings with projected monthly savings and expected performance impact, making it the only option here that directly performs ML-based right-sizing for production workloads.
✗AWS Trusted AdvisorWrong answer — click to see why▾
Why this is wrong here
AWS Trusted Advisor provides general best-practice checks, including cost optimization, but it does not offer ML-based recommendations for downsizing EC2 instances based on historical utilization patterns.
★ When this WOULD be the correct answer
A company wants a one-time assessment of their AWS account against best practices, including cost optimization, security, and fault tolerance, without needing ML-driven or historical utilization analysis.
Why candidates choose this
Candidates may confuse Trusted Advisor's cost optimization checks with Compute Optimizer's ML-based recommendations, assuming Trusted Advisor provides similar instance sizing advice.
✗AWS Cost ExplorerWrong answer — click to see why▾
Why this is wrong here
AWS Cost Explorer provides cost and usage data but does not generate ML-based recommendations for downsizing EC2 instances. It lacks the automated, performance-aware optimization logic needed for this scenario.
★ When this WOULD be the correct answer
AWS Cost Explorer would be correct if the question asked for a service to visualize historical EC2 spending, identify cost trends, or create custom cost reports to manually analyze downsizing opportunities, without requiring ML-based recommendations.
Why candidates choose this
Candidates may confuse Cost Explorer's cost analysis capabilities with optimization recommendations, assuming it can suggest instance downsizing because it shows cost data and usage patterns.
✗AWS BudgetsWrong answer — click to see why▾
Why this is wrong here
AWS Budgets allows you to set custom cost and usage budgets and receive alerts when you exceed thresholds, but it does not provide ML-based recommendations for downsizing EC2 instances or estimate savings from specific instance changes.
★ When this WOULD be the correct answer
A company wants to set a monthly spending limit for its EC2 usage and receive notifications when costs approach or exceed that limit. AWS Budgets would be the correct service to create a cost budget with alerts.
Why candidates choose this
Candidates may confuse Budgets with cost optimization tools, thinking that setting a budget will automatically provide recommendations to reduce costs, or they may associate 'savings' with budget alerts.
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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About these practice questions
This CLF-C02 question is part of Courseiva's 988-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on CLF-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 company runs 200 Amazon EC2 instances for its web application. The finance team wants to identify instances that are over-provisioned or underutilized to reduce costs. The team needs automated recommendations that consider the instance's CPU, memory, and network utilization patterns over the past 14 days. Which AWS service should the team use?
medium- ✓ A.AWS Compute Optimizer
- B.AWS Trusted Advisor
- C.AWS Cost Explorer
- D.AWS Budgets
Why A: AWS Compute Optimizer is the correct service because it uses machine learning to analyze historical utilization metrics (CPU, memory, network) over a specified lookback period (up to 93 days, but 14 days is supported) and generates actionable recommendations to right-size EC2 instances. It specifically identifies over-provisioned and underutilized instances, directly addressing the finance team's cost-reduction goal with automated, metric-driven insights.
JA
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.