Mage for Anomaly detection with InfluxDB and Half-space Trees

InfluxDB 3.0 has improved write throughput and query performance, but its task engine was deprioritized in favor of interoperability with existing tools. Mage.ai is an open-source replacement for Airflow that can be used for anomaly detection and sending alerts to a Slack webhook. To run this tutorial, users need an InfluxDB v3 Cloud account, Docker, and an .env file with necessary configuration. The dataset includes machine data from three machines that can be loaded into InfluxDB using the Mage pipeline. The pipeline consists of four blocks: Load_influx_data, Transform_data, Detect_anomalies, and Check_anomalies. Half-space trees are used for anomaly detection in high-dimensional data, partitioning the feature space with hyperplanes to isolate anomalies. The tutorial showcases how to use Mage for anomaly detection and sending alerts using InfluxDB 3.0 and half-space trees.

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