10. AWS Cost Anomaly Detection
AWS Cost Anomaly Detection uses Machine Learning (ML) to continuously monitor your AWS cost and usage data and detect unusual spending patterns.
⚙️ How It Works
| Feature | Description |
|---|---|
| ML-Based Detection | Learns your historical spending patterns automatically. |
| No Manual Thresholds | You don’t need to define any static limits — ML determines what’s “abnormal.” |
| Continuous Monitoring | Detects both one-time spikes and ongoing cost increases. |
| Scope of Monitoring | Works across AWS services, member accounts, cost allocation tags, and cost categories. |
📊 Notifications & Reporting
| Method | Description |
|---|---|
| Anomaly Detection Reports | Provides insights with root cause analysis of cost anomalies. |
| Alerting Options | You can get individual alerts or daily/weekly summaries. |
| Delivery Method | Notifications are sent via Amazon SNS (Simple Notification Service). |
🧠 Key Benefit
Automatically detect and analyze unusual spending using ML — no configuration, no manual thresholds, just insights.
✅ Summary
- ML-powered, automated cost anomaly detection
- Learns your spending patterns
- Detects spikes or abnormal trends
- Alerts via SNS (individual or summary)
- Helps you act quickly to control unexpected costs
📍Exam Tip: Remember — this service is proactive, machine-learning-based, and requires no manual setup of thresholds.