Requirements for Anomaly Detection Techniques for Microservices

Abstract

Version configurations of third-party software are essential to ensure a reliable and executable microservice architecture. Although these minor version configurations seem straightforward as the functionality does not need to be adapted, unexpected behaviour emerges due to the complex infrastructure and many dependencies. Anomaly detection techniques determine these unexpected behaviour changes during runtime. However, the requirements anomaly detection algorithms need to fulfil are unexplored. Thus, this case study collects experiences from practitioners and monitoring datasets from a well-known benchmark system (Train Ticket) to identify five requirements - namely: (1) early detectability, (2) reliability, (3) risk analysis, (4) adaptability, and (5) root causes analysis. In this work, we additionally evaluate three anomaly detection techniques on their practical applicability with the help of these identified requirements and extracted monitoring data.