Advanced Detectors

Lab Objective

Build a multi-condition detector that alerts only when:

• A metric is historically anomalous
• AND above a static operational threshold
• For a sustained duration
• With a customized, actionable alert message

The intent of this lab is to use a real-world example to gain hands-on experience with the SignalFlow behind detectors and alerts. You will move beyond the wizard interface to understand how metric streams are evaluated, how threshold functions generate anomaly conditions, and how detection logic is composed programmatically.

You will examine the out-of-the-box functions used by the wizard, understand how they translate to SignalFlow, and introduce additional SignalFlow methods and functions to construct a detector with greater precision and control.

Scenario

Alert when:

• CPU utilization is anomalous based on history
• AND above 90%
• For 15 minutes sustained

This pattern reduces noise by combining statistical deviation with an operational guardrail and reinforces how threshold generation and alert logic work together within SignalFlow.