Performing Real-Time Anomaly Detection with InfluxDB 3: An In-Depth Guide

Real-time anomaly detection can be performed directly within InfluxDB 3 using Python plugins and the Processing Engine. Two complementary approaches are available: the MAD (Median Absolute Deviation) plugin for detecting immediate spikes and outliers, and the ADTK (Anomaly Detection Toolkit) plugin for identifying sustained instability and variance shifts. Both plugins run in-database without separate infrastructure, support configurable thresholds and windows, and integrate with notification systems like Slack. The MAD approach uses statistical methods for instant detection on every write, while ADTK employs scheduled checks to analyze historical windows for pattern changes. Together, they provide comprehensive monitoring for IoT sensors and industrial systems.