- A
AWS Budgets
Why wrong: AWS Budgets allows you to set cost or usage limits and receive alerts when you approach or exceed those limits, but it does not automatically detect anomalies based on historical spending patterns.
- B
AWS Cost Anomaly Detection
AWS Cost Anomaly Detection uses machine learning to analyze historical cost and usage data, detect unusual spending patterns, and provide root cause analysis with actionable alerts.
- C
AWS Cost Explorer
Why wrong: AWS Cost Explorer provides interactive charts and reports for exploring and analyzing your AWS costs and usage, but it does not proactively detect anomalies using machine learning.
- D
AWS Trusted Advisor
Why wrong: AWS Trusted Advisor inspects your AWS environment and provides recommendations in categories including cost optimization, but it does not offer automated anomaly detection for spending patterns.
Quick Answer
The answer is AWS Cost Anomaly Detection. This is the correct choice because it is a fully managed service that uses machine learning to continuously analyze your historical cost and usage patterns, automatically establish a baseline of normal spending, and then detect deviations from that baseline in real time, providing root cause analysis for each anomaly. On the AWS Certified Cloud Practitioner CLF-C02 exam, this question tests your understanding of the difference between proactive budget alerts and ML-driven anomaly detection; a common trap is confusing AWS Budgets, which only triggers alerts based on fixed thresholds you set, with Cost Anomaly Detection, which learns patterns without manual thresholds. To remember this, think of Budgets as a static speed limit sign, while Cost Anomaly Detection is like a smart traffic system that flags unusual driving behavior even if you haven’t exceeded the limit.
CLF-C02 Billing, Pricing, and Support Practice Question
This CLF-C02 practice question tests your understanding of billing, pricing, and support. 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 a variety of workloads on AWS and wants to be notified when their monthly spending behaves unusually compared to past patterns. They want a managed service that uses machine learning to detect cost anomalies and provides root cause analysis. Which AWS service or feature should they 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 Cost Anomaly Detection
AWS Cost Anomaly Detection is a managed service that leverages machine learning to continuously monitor your cost and usage patterns, detect anomalies, and provide root cause analysis. It automatically establishes a baseline from historical spending data and alerts you when actual spending deviates from expected patterns, making it the correct choice for this use case.
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 Budgets
Why it's wrong here
AWS Budgets allows you to set cost or usage limits and receive alerts when you approach or exceed those limits, but it does not automatically detect anomalies based on historical spending patterns.
- ✓
AWS Cost Anomaly Detection
Why this is correct
AWS Cost Anomaly Detection uses machine learning to analyze historical cost and usage data, detect unusual spending patterns, and provide root cause analysis with actionable alerts.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Cost Explorer
Why it's wrong here
AWS Cost Explorer provides interactive charts and reports for exploring and analyzing your AWS costs and usage, but it does not proactively detect anomalies using machine learning.
- ✗
AWS Trusted Advisor
Why it's wrong here
AWS Trusted Advisor inspects your AWS environment and provides recommendations in categories including cost optimization, but it does not offer automated anomaly detection for spending patterns.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Budgets (a simple threshold alerting tool) with AWS Cost Anomaly Detection (an ML-driven anomaly detection service), because both can send cost alerts, but only the latter provides automated root cause analysis and pattern-based detection.
Detailed technical explanation
How to think about this question
AWS Cost Anomaly Detection uses a combination of statistical modeling and machine learning algorithms to analyze historical cost and usage data across accounts, services, and tags, establishing a dynamic baseline that adapts to seasonal trends and growth. When an anomaly is detected, it provides a root cause analysis by evaluating the impacted services, regions, and usage types, and can automatically trigger alerts via Amazon SNS or AWS Chatbot. In a real-world scenario, this service can detect a sudden spike in EC2 costs due to a misconfigured auto-scaling group and pinpoint the specific instance type and region responsible.
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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Billing, Pricing, and Support — study guide chapter
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CLF-C02 practice test guide
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FAQ
Questions learners often ask
What does this CLF-C02 question test?
Billing, Pricing, and Support — This question tests Billing, Pricing, and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Cost Anomaly Detection — AWS Cost Anomaly Detection is a managed service that leverages machine learning to continuously monitor your cost and usage patterns, detect anomalies, and provide root cause analysis. It automatically establishes a baseline from historical spending data and alerts you when actual spending deviates from expected patterns, making it the correct choice for this use case.
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.
About these practice questions
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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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