Application of FinOps-Based Cloud Cost Risk Analysis on Microsoft Azure Services

Dzihni Safwa Alifah (Universitas Amikom Purwokerto)
Mahadika Rastia Wardana (Universitas Amikom Purwokerto)
Yulia Cahyani (Universitas Amikom Purwokerto)
Ilham Albana (Universitas Amikom Purwokerto)

Economic, Management, Business and Accountancy International Journal (EMBAIJ)
Vol. 2 No. 2 (2025): Economic, Management, Business and Accountancy International Journal

The increasing adoption of cloud computing simplifies IT infrastructure management but also introduces challenges related to unpredictable cost fluctuations. This study applies a descriptive quantitative approach using the Z-Score method to detect cloud cost anomalies as an initial step in FinOps practices. Microsoft Azure service cost data from the 2023–2024 period were analyzed through data cleansing, statistical calculations, and cost trend visualization. Using a Z-Score threshold of ≥ 1.7, the results indicate that one month was identified as High Risk with a Z-Score value of 2.275, representing a significant cost spike. These findings demonstrate that the Z-Score method is capable of detecting cost deviations quickly and efficiently without requiring complex analytical models, making it effective as an early warning system prior to the adoption of more advanced analytics techniques.