Real-time time series prediction for anomaly detection

A method for operating a real-time time series prediction model includes obtaining a first sequence corresponding to a target time series; obtaining a second sequence corresponding to a peer time series of the target time series; determining whether a predetermined number of time steps have elapsed since a last retraining of the real-time time series prediction model; and if the predetermined number of time steps have elapsed since the last retraining of the time series prediction model, retraining the real-time time series prediction model using a first portion of the first and second sequences; and applying a remaining portion of the first and second sequences to the real-time time series prediction model to predict a next value of the target time series.