Microservices smell detection through dynamic analysis

Abstract

The past few years saw the rise of microservices studies and best practices, along with wide industrial adoption of this architectural style. We now witness the birth of another challenging topic: microservices quality. Like other kinds of architectures, also microservices suffer from erosion and technical debt, whose symptoms can be the appearance of microservices smells, which impact negatively on the system’s quality, by hindering, for example, its maintainability. In this paper we propose a tool called Aroma, to reconstruct microservices architectures and detect microservices smells, based on the dynamic analysis of microservices execution traces. We describe the main features of the tool, the strategies adopted for microservice smells detection and the first preliminary experimentation.