Anomaly Detection and Forecasting That Learns From Every Write in InfluxDB (opens in new tab)

For many operational time series workloads, machine learning can’t operate in the historical way, where data is compiled once and models are trained offline. Sensor readings, infrastructure metrics, application telemetry, energy data, industrial measurements, and financial ticks all share a basic property: the next datapoint is more useful when the system can respond to it immediately (or at least close to immediately). When a model learns in the same flow that ingests data and reacts to inco...