OpsNow FinOps Plus offers two detection modes in its Cost Anomalies feature:
AI-based detection and Manual rule-based detection.
Each method differs in detection logic, setup complexity, and flexibility:
✅ AI-based Detection
- Automatically analyzes the last 14 days of usage trends to generate predicted spend, and detects anomalies by comparing them with actual costs.
- Alerts are triggered when the actual cost significantly deviates from the forecast, and users receive visual reports via email.
- Detection sensitivity can be adjusted (High / Middle / Low).
- Requires at least 7 days of usage data before activating automatic analysis, which then runs daily.
⚙️ Manual Detection
- Allows users to define custom rules based on:
- Budget thresholds
- Percentage deviations
- Specific time range comparisons (e.g., last 3 days vs previous 3 days)
- Enables fine-grained control over which anomalies to detect and under what conditions.
💡 Comparison Summary
| Category |
AI-Based Detection |
Manual Detection |
| Method |
Based on prediction model |
Based on user-defined rules |
| Setup |
Simple (few clicks) |
Detailed configuration required |
| Flexibility |
Good for general anomaly tracking |
Ideal for edge cases or special scenarios |
| Activation |
Requires 7-day learning |
Immediate availability |
| Sensitivity |
Adjustable (High / Middle / Low) |
Fully configurable thresholds |
📌 You can use both methods in parallel to achieve automated efficiency and manual precision in anomaly detection.
