Overview of Key Performance Indicator Anomaly Detection

With the rapid development of the Internet, web services have penetrated into all areas of society, and ensuring the stability of web services has become more and more important. Generally, operations judge whether a web service is stable by monitoring various key performance indicators (KPI). If a KPI is abnormal, it often means that there is a problem with the related application, and KPI anomaly detection plays an important role in it. KPI is time serial which is different from static data. In this article, we show the investigation and summary of KPI anomaly detection. The KPI anomaly detection methods can be classified into three types: distance-based methods, density-based methods, and deep learning-based methods. We conclude the advantages and disadvantages of them. Finally, we give the possible future research directions.