On measuring coupling between microservices
Chenxing Zhong, He Zhang, Chao Li, Huang Huang, Daniel Feitosa
Abstract
In software quality management , the selection strategy for proper metrics varies depending on the application scenarios and measurement objectives. MicroService Architecture (MSA), despite being commonly employed nowadays, still cannot be reliably measured and compared if the microservices in a system are independent. Software managers and architects need to understand whether their microservices are “decoupled enough”, if not, which ones are over-coupled, and by how much. In this paper, we contribute a novel set of metrics – Microservice Coupling Index (MCI) – derived from the relative measurement theory. Instead of measuring coupling evidence with simple counts, we measure how dependent and coupled the microservices are relative to the possible couplings between them. We measured the MCI metrics for 15 open source projects that involve 113 distinct microservices. Empirical investigation confirmed that MCIs differ quite significantly from existing coupling measures and that they are more discriminative than existing ones for separating high and low degrees of microservice couplings and thus more useful in comparing design alternatives. A series of experimental studies were conducted, showing that the larger the MCIs, the less likely the bugs and changes can be localized and separated, and the less likely that the individual microservices in a system can be independently developed and evolved.