Next-Generation Firewall
Forecasting and Anomaly Detection
Table of Contents
Forecasting and Anomaly Detection
Learn how to generate alerts and incidents by forecasting and anomaly
detection.
| Where Can I Use This? | What Do I Need? |
|---|---|
| One of these: |
Normally, AIOps for NGFW detects issues by applying fixed rules to the
metrics in your deployment. For example, if Management Plane CPU Usage exceeds 85%, the
metric enters a Critical state.
However, to alert you to events that fixed rules might miss, AIOps for NGFW can use machine learning to understand your deployment and offer you additional
alerts and incidents tailored to your usage trends.
- Forecast-Based Alerts help you anticipate issues by projecting how a device metric may change and alerting you accordingly.
- Anomaly-Based Alerts establish a baseline behavior for a device metric and alert you when that metric crosses the Anomaly Sensitivity Settings that you specify.
The benefits of forecasting and anomaly detection are as follows:
- Proactive Management: By predicting potential issues and identifying anomalies early, administrators can take proactive measures to prevent problems, reducing downtime and improving overall network performance.
- Enhanced Security: Detecting unusual patterns and behaviors can help identify security threats and vulnerabilities, allowing for timely intervention and mitigation.
- Optimized Resources: Forecasting helps in better resource planning and allocation, ensuring that the network infrastructure is adequately prepared to handle future demands.
Navigate to .
AIOps for NGFW generates alerts and incidents that dynamically adjust
based on the metric’s historical value and your usage trends. Deviations from the
normality band can indicate potential issues. You can adjust this setting to control the
sensitivity level of the anomaly detection algorithm.
