Organizational Cohesion in Microservice Architectures: A Multi-Project Empirical Study
For researchers and practitioners in software engineering, this work provides a quantitative method to assess socio-technical alignment in microservice development, though the findings are exploratory and based on a limited set of projects.
This paper introduces organizational cohesion in microservice architectures and proposes Pairwise Team Cohesion (PTC) to measure developer contribution balance within services. Analyzing seven open-source microservice systems, they find weak correlation between PTC and Average Organizational Coupling, indicating distinct organizational dynamics.
The widespread adoption of microservice architectures has introduced new challenges in aligning software modularity with the structure of development organizations. Although prior research has extensively examined technical properties such as service coupling and dependency structures, comparatively little attention has been paid to how contributor activity reflects or diverges from service boundaries. In this paper, we introduce the notion of organizational cohesion in microservice ecosystems and propose a quantitative approach to measure it. Building on the Sensitive Class Cohesion Metric (SCOM), we define Pairwise Team Cohesion (PTC), a metric that captures the balance and focus of developer contributions within individual microservices. We analyze the evolution of organizational cohesion using a longitudinal case study of the Spinnaker microservice platform and replicate the analysis across six additional open-source microservice systems. Our results reveal systematic differences between core and peripheral services and show that PTC and Average Organizational Coupling (AOC) exhibit only a weak correlation across projects. This finding shows that team cohesion and cross-service developer activity suggest distinct and weakly associated organizational dynamics. By extending the "high cohesion, low coupling" principle to the organizational level, our study provides a quantitative perspective for assessing the socio-technical structure of microservice development.