Question 911 of 1,546
Cost and Performance OptimizationmediumMultiple ChoiceObjective-mapped

SOA-C02 Practice Question: AWS Cost Anomaly Detection for automated alerts…

This SOA-C02 practice question tests your understanding of cost and performance optimization. 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. A key principle to apply: cost Anomaly Detection. 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.

The finance team was surprised by a $12,000 spike in EC2 costs last month caused by a runaway Auto Scaling group. They want to receive an email alert within hours whenever any AWS service cost behaves unexpectedly, without manually setting fixed dollar thresholds for each service. Which AWS cost management feature provides this?

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

Enable Cost Anomaly Detection with an AWS services monitor and create an alert subscription to email the finance team when an anomaly is detected

Cost Anomaly Detection uses machine learning to model historical spending patterns for each AWS service and automatically detects unusual spikes without requiring manual thresholds. By creating an AWS services monitor and linking an alert subscription, the finance team receives email notifications within hours when any service deviates from its expected cost behavior, directly addressing the need for service-agnostic, threshold-free alerts.

Key principle: Cost Anomaly Detection

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Enable Cost Anomaly Detection with an AWS services monitor and create an alert subscription to email the finance team when an anomaly is detected

    Why this is correct

    Cost Anomaly Detection's ML model learns the historical spending pattern for each service. When EC2 (or any service) starts spending at an anomalous rate, the model detects it within hours. The alert subscription can notify via email or SNS with the anomaly amount, affected service, and percentage deviation. No manual threshold tuning is needed — the model self-calibrates.

    Related concept

    Cost Anomaly Detection

  • Create an AWS Budget with a monthly EC2 cost threshold of $10,000 and an alert at 80 percent of the threshold

    Why it's wrong here

    A fixed-threshold budget is easy to set up but requires knowing the expected spend in advance. It does not detect anomalous patterns — if normal spend is $9,000 and a runaway group adds $3,000 over the alert period, a $10,000 budget may not trigger if some costs shift to the next period. It also requires separate budgets per service.

  • Enable AWS Cost Explorer and review the daily cost breakdown each morning to spot unexpected charges

    Why it's wrong here

    Cost Explorer is a visualization and analysis tool — it requires manual review. The finance team would only discover the spike during their daily review, potentially hours or days after it began. Cost Anomaly Detection sends automatic proactive alerts without requiring manual log-in and review.

  • Configure CloudWatch Billing alarms with a static threshold for each AWS service individually

    Why it's wrong here

    CloudWatch Billing alarms use fixed dollar thresholds per account or service. Setting appropriate static thresholds for every service requires knowing the expected spend and updating thresholds as workloads grow. They do not use ML to distinguish normal growth from anomalous spikes.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse AWS Budgets or CloudWatch Billing alarms with anomaly detection, but those tools require manual static thresholds and do not automatically adapt to changing spending patterns across multiple services.

Detailed technical explanation

How to think about this question

Cost Anomaly Detection leverages a proprietary machine learning model that analyzes up to 12 months of historical cost and usage data to establish a baseline for each service, then evaluates new usage against that baseline using a statistical anomaly score. The alert subscription integrates with Amazon SNS to deliver notifications via email, SMS, or other endpoints, and the detection granularity is at the service level, meaning a spike in any monitored service triggers an alert without per-service threshold configuration. In practice, this feature can detect anomalies caused by misconfigured resources, such as a runaway Auto Scaling group, within 24 hours of the cost incurrence.

KKey Concepts to Remember

  • Cost Anomaly Detection
  • Anomaly Monitor
  • Alert Subscription
  • ML-based Threshold

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

Cost Anomaly Detection

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 SOA-C02 question test?

Cost and Performance Optimization — This question tests Cost and Performance Optimization — Cost Anomaly Detection.

What is the correct answer to this question?

The correct answer is: Enable Cost Anomaly Detection with an AWS services monitor and create an alert subscription to email the finance team when an anomaly is detected — Cost Anomaly Detection uses machine learning to model historical spending patterns for each AWS service and automatically detects unusual spikes without requiring manual thresholds. By creating an AWS services monitor and linking an alert subscription, the finance team receives email notifications within hours when any service deviates from its expected cost behavior, directly addressing the need for service-agnostic, threshold-free alerts.

What should I do if I get this SOA-C02 question wrong?

Review cost Anomaly Detection, then practise related SOA-C02 questions on the same topic to reinforce the concept.

What is the key concept behind this question?

Cost Anomaly Detection

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Last reviewed: Jun 11, 2026

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This SOA-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 SOA-C02 exam.