- A
AWS Cost Anomaly Detection
This service uses machine learning to continuously monitor cost and usage patterns, detect anomalies based on historical baselines, and send alerts. It matches the requirement for automatic, threshold-free anomaly detection.
- B
AWS Budgets
Why wrong: AWS Budgets allows you to set fixed cost, usage, or reservation utilization budgets and receive alerts when actual or forecasted spending exceeds those budget amounts. However, it does not automatically detect anomalies based on historical patterns—the budget thresholds are manually defined.
- C
AWS Cost Explorer
Why wrong: AWS Cost Explorer is a tool for visualizing, understanding, and managing AWS costs and usage over time. It can generate forecasts but does not proactively detect anomalies or send alerts when unexpected spending occurs.
- D
AWS Trusted Advisor
Why wrong: AWS Trusted Advisor inspects your AWS environment and provides best practice recommendations in categories including cost optimization, performance, security, and fault tolerance. It does not monitor cost patterns or detect anomalies.
Quick Answer
The answer is AWS Cost Anomaly Detection. This managed service is the correct choice because it leverages machine learning to continuously analyze your historical cost and usage patterns, automatically establishing a baseline for normal spending without requiring you to manually define thresholds for each service. When an unexpected cost spike occurs—whether from resource misuse, billing errors, or unauthorized activity—the service detects the deviation and sends an alert, making it ideal for proactive financial governance. On the AWS Certified Cloud Practitioner CLF-C02 exam, this question tests your understanding of the AWS Cost Management suite and the distinction between automated ML-driven tools and manual alerting services like AWS Budgets, which require you to set fixed thresholds. A common trap is confusing Cost Anomaly Detection with AWS Budgets; remember that Budgets need your predefined limits, while Anomaly Detection learns patterns on its own. Memory tip: think “ML learns, Budgets burn” to recall that machine learning handles the detection automatically.
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 uses a variety of AWS services and wants to automatically detect unexpected cost spikes that might indicate resource misuse, billing errors, or unauthorized activity. The company needs a managed service that uses machine learning to analyze spending patterns and provide alerts when costs deviate from expected trends. The finance team does not want to manually define thresholds for every service. Which AWS service should the finance team 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 uses machine learning to continuously monitor your cost and usage patterns, automatically detecting anomalous spending without requiring manual threshold definitions. It analyzes historical data to establish a baseline and alerts you when costs deviate from expected trends, making it ideal for identifying unexpected spikes from resource misuse, billing errors, or unauthorized activity.
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 Cost Anomaly Detection
Why this is correct
This service uses machine learning to continuously monitor cost and usage patterns, detect anomalies based on historical baselines, and send alerts. It matches the requirement for automatic, threshold-free anomaly detection.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Budgets
Why it's wrong here
AWS Budgets allows you to set fixed cost, usage, or reservation utilization budgets and receive alerts when actual or forecasted spending exceeds those budget amounts. However, it does not automatically detect anomalies based on historical patterns—the budget thresholds are manually defined.
- ✗
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 can generate forecasts but does not proactively detect anomalies or send alerts when unexpected spending occurs.
- ✗
AWS Trusted Advisor
Why it's wrong here
AWS Trusted Advisor inspects your AWS environment and provides best practice recommendations in categories including cost optimization, performance, security, and fault tolerance. It does not monitor cost patterns or detect anomalies.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Budgets (which requires manual thresholds) with a proactive ML-based anomaly detection service, leading them to choose Budgets because they think 'alerts' automatically imply anomaly detection.
Detailed technical explanation
How to think about this question
AWS Cost Anomaly Detection leverages a combination of statistical modeling and machine learning algorithms (e.g., seasonal decomposition and neural networks) to learn normal spending patterns across services, accounts, and cost allocation tags. It evaluates metrics such as mean absolute percentage error (MAPE) and uses a root cause analysis feature to identify the specific service, region, or tag driving the anomaly, which helps reduce investigation time. In a real-world scenario, if a developer accidentally launches a fleet of GPU instances in an unused region, Cost Anomaly Detection can flag the spike within hours, whereas manual thresholds might miss it if set too loosely.
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 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 uses machine learning to continuously monitor your cost and usage patterns, automatically detecting anomalous spending without requiring manual threshold definitions. It analyzes historical data to establish a baseline and alerts you when costs deviate from expected trends, making it ideal for identifying unexpected spikes from resource misuse, billing errors, or unauthorized activity.
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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