FOCP practice question 4 of 10

What is the primary purpose of "Cloud Cost Anomaly Detection" in FinOps? (Select One)

Full set: 300 questions
Answer options
A: To identify unusual spikes or drops in cloud spending Correct answer
B: To enforce cloud security policies
C: To automatically scale cloud resources based on demand
D: To improve the performance of cloud resources
Correct Answer:
A. To identify unusual spikes or drops in cloud spending
Explanation

The primary purpose of Cloud Cost Anomaly Detection is to automatically monitor cloud expenditure data and identify spending patterns that deviate significantly from the established baseline or forecast. By flagging unusual spikes (potential waste, bugs, or attacks) or unexpected drops (potential service outages), these systems enable FinOps teams to investigate and remediate issues quickly, preventing significant budget overruns and ensuring operational stability. It is a proactive control for managing cloud costs in a dynamic environment.

Why Incorrect

B. Enforcing cloud security policies is the function of security tools like Cloud Security Posture Management (CSPM), not cost anomaly detection.
C. Automatically scaling resources based on demand is the purpose of autoscaling services, which react to performance metrics, not historical cost data.
D. Improving the performance of cloud resources is the goal of performance monitoring and optimization tools, not cost anomaly detection.

References

1. Storment, J.R., Fuller, M., & Quinn, C. (2023). Cloud FinOps: Collaborative, Real-Time Cloud Financial Management (2nd ed.). O'Reilly Media. Chapter 5, "Managing FinOps," Section "Anomaly Detection," p. 103, states, "Anomaly detection is the process of identifying unexpected events or items in a dataset... In FinOps, we are looking for unexpected changes in cost."

2. FinOps Foundation. (n.d.). Managing Anomalies. FinOps Framework Capabilities. Retrieved from https://www.finops.org/framework/capabilities/manage-anomalies/. The documentation defines this capability as "the detection, identification, and management of unexpected or unforecasted cloud cost events."

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