AI-Based Cloud Cost Anomaly Detection and Alerting System
Eclerx Cloud ComputingProject Objectives:
Develop an AI-driven cloud cost anomaly detection system that monitors billing patterns, detects unusual spending spikes, and generates automated alerts to prevent unexpected financial overruns in cloud environments.
Project Tasks:
Collect historical cloud billing and usage data.
Store billing data in structured database.
Preprocess time-series cost datasets.
Implement anomaly detection algorithms (Isolation Forest / ARIMA).
Identify abnormal cost spikes.
Visualize spending trends on dashboard.
Configure automated alert notifications.
Simulate unexpected traffic surge.
Compare anomaly detection accuracy.
Analyze false positives and negatives.
Integrate system with cloud billing API.
Generate monthly cost anomaly reports.
Evaluate model performance metrics.
Document AI workflow and cost monitoring architecture.
