Structural Coupling for Microservices

TL;DR

This paper introduces a new method to measure and visualize the coupling between microservices in cloud-native applications, providing quantitative tools to improve system design and evolution monitoring.

Contribution

It extends traditional structural coupling concepts to microservices, offering validated metrics and an automatic approach for their computation and visualization.

Findings

Metrics effectively quantify microservice coupling.

Case study demonstrates practical applicability.

Visual tools aid in system evolution monitoring.

Abstract

Cloud-native Applications are 'distributed, elastic and horizontal-scalable systems composed of (micro)services which isolate states in a minimum of stateful components'. Hence, an important property is to ensure a low coupling and a high cohesion among the (micro)services composing the cloud-native application. Loosely coupled and highly cohesive services allow development teams to work in parallel, reducing the communication overhead between teams. However, despite both practitioners and researchers agree on the importance of this general property, there are no validated metrics to effectively measure or test the actual coupling level between services. In this work, we propose ways to compute and visualize the coupling between microservices, by extending and adapting the concepts behind the computation of the traditional structural coupling. We validate these measures with a case study involving 17 open-source projects and we provide an automatic approach to measure them. The results of this study highlight how these metrics provide to practitioners a quantitative and visual view of services compositions, which can be useful to conceive advanced systems to monitor the evolution of the service.