Microservice Decomposition using Many-Objective Optimization

Abstract

The literature on Microservices Architecture (MSA) presents numerous approaches for decomposing systems into microservices with the goal of improving quality attributes such as scalability, maintainability, and elasticity. Studies indicate that practitioners typically consider multiple objectives simultaneously when defining service boundaries, making microservice decomposition an inherently multi-objective optimization problem. Within this context, evolutionary algorithms are well suited to exploring trade-offs among competing objectives. This work utilizes the Event Storming graph as the primary input for extracting domain entities and identifying their relationships. By combining semantic analysis of entity names with the structural information embedded in the Event Storming graph, candidate microservice decompositions are generated and optimized using the NSGA-III algorithm. The proposed approach seeks to improve the efficiency and accuracy of deriving microservice boundaries from Event Storming models while providing software architects and decision-makers with a systematic framework for analysing and evaluating decomposition alternatives.