Implementing Automatic Microservices Detection in Business Processes Using Association Rules

Abstract

Microservice-oriented architectures are increasingly becoming the preferred architectural style over monolithic systems, both in academic research and industrial applications. This shift is largely due to microservices' ability to deconstruct large, monolithic applications into smaller, independent, highly cohesive, and loosely connected services.However, the process of identifying appropriate microservices is a significant challenge, which, if not addressed adequately, could hinder the effectiveness and benefits of transitioning to this architectural style. In this paper, we introduce an innovative method based on association rules to automate the identification of microservices within a business process. This technique leverages association analysis to uncover latent correlations among the attributes of various activities. Activities sharing similar attributes are then grouped into the same microservice categories. To validate and demonstrate the practicality of our method, we conduct a case study focusing on a bicycle rental system.