CV0-004 Operations and Support Practice Question
A cloud operations team is configuring cost anomaly detection for a multi-account AWS organization. They want to be notified proactively when spending deviates from expected patterns and to attribute the deviation to the right team. Which TWO actions should they take? (Choose two.)
⚠ Common exam trap
The trap here is assuming AWS Budgets provides anomaly detection, when Budgets only compares actual spend to a static threshold and cannot learn expected patterns or attribute deviations by tag.
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
✓
Create a cost allocation report and apply a consistent tag taxonomy across all accounts
Cost Anomaly Detection with per-account monitors and alert subscriptions provides proactive, machine-learning-based notification of abnormal spend, while a consistent cost allocation tag taxonomy enables attribution of those anomalies to the correct team. Trusted Advisor, Budgets thresholds, and in-instance agents do not provide the combination of learned baselines and team-level attribution required here.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy a third-party agent on every EC2 instance to report hourly spend to a central dashboard
Why it's wrong here
Billing data is aggregated by AWS at the account and service level, not per instance in real time, so an in-instance agent cannot produce accurate cost figures. This approach adds operational overhead and still cannot attribute shared or serverless costs. It also bypasses the native Cost Anomaly Detection capability the team is trying to use.
- ✓
Create a cost allocation report and apply a consistent tag taxonomy across all accounts
Why this is correct
Consistent cost allocation tags across accounts let Cost Explorer and Cost Anomaly Detection group and filter spend by team, application, or environment. Without a shared tag taxonomy, anomalies cannot be reliably attributed to an owner. Tagging plus per-account monitors together provide both detection and attribution, which is exactly what the scenario requires.
- ✗
Set a hard AWS Budgets limit that automatically terminates EC2 instances when exceeded
Why it's wrong here
AWS Budgets can alert on thresholds, but it does not terminate instances automatically; that would require a separate automation such as an EventBridge rule invoking Lambda. Budgets also compare against a fixed threshold rather than learning expected spend patterns. This does not deliver machine-learning anomaly detection or team attribution.
- ✗
Enable AWS Trusted Advisor cost optimization checks and rely on their weekly emails
Why it's wrong here
Trusted Advisor cost checks identify idle resources and savings opportunities, not statistical anomalies relative to a spending baseline. Its reports are periodic and broad, so they will not flag a sudden unexpected spike in near real time. It also provides no per-account attribution mechanism tied to anomaly detection.
- ✓
Enable AWS Cost Anomaly Detection with a monitor scoped to each linked account and configure an alert subscription
Why this is correct
Cost Anomaly Detection uses machine learning to learn each account's spending patterns and emits alerts when actual spend deviates from the forecast. Scoping monitors per linked account isolates anomalies to the responsible account, and an alert subscription delivers notifications through email or Amazon SNS so the team is informed proactively. This directly addresses early detection of abnormal spend.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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