Systems and methods of anomaly detection in large scale production environments using time-series modeling

Abstract

Systems and methods of anomaly detection using a generalized time-series forecasting model are disclosed. A time-series dataset is received and a forecast is generated for the time-series dataset utilizing a trained generalized time-series forecasting model configured to utilize a fixed set of characteristic features. A first anomaly determination for the time-series dataset is generated based on a comparison of the forecast for the time-series dataset to the time-series dataset. In response to the first anomaly determination identifying an anomaly, an anomaly identification notification is transmitted to an additional system associated with the anomaly identification.