Microservice extraction based on knowledge graph from monolithic applications

Context: Re-architecting monolithic systems with microservice architecture is a common trend. However, determining the "optimal" size of individual services during microservice extraction has been a challenge in software engineering. Common limitations of the literature include not being reasonable enough to be put into practical application; relying too much on human experience; neglection of the impact of hardware environment on the performance. Objective: To address these problems, this paper proposes a novel method based on knowledge-graph to support the extraction of microservices during the initial phases of re-architecting existing applications. Method: According to the microservice extraction method based on the AKF principle which is a widely practiced microservice design principle in the industry, four kinds of entities and four types of entity-entity relationships are designed and automatically extracted from specification and design artifacts of the monolithic application to build the knowledge graph. A constrained Louvain algorithm is proposed to identify microservice candidates. Results: Our approach is tested based on two open-source projects with the other three typical methods: the domain-driven design-based method, the similarity calculation-based method, and the graph clustering-based method. Conducted experiments show that our method performs well concerning all the evaluation metrics.