Supporting the decision of migrating to microservices through multi-layer fuzzy cognitive maps - Christoforou, Andreas; Garriga, Martin; Andreou, Andreas S.; Baresi, Luciano (My University, 2017)
Microservices architectures are gaining momentum for the development of applications as suites of small, autonomous, and conversational services, which are then easy to understand, deploy and scale. However, one of today’s problems is that microservices introduce new complexities to the system and, despite the hype, many factors should be considered when deciding to adopt a microservices architecture. This paper proposes the first Decision Support System (DSS) to migrate to microservices, by identifying the key concepts and drivers regarding through a literature review and feedback from a group of experts from industry and academia. Then, these concepts are organized as a Multi-Layer Fuzzy Cognitive Map (ML-FCM), a graph-based computational intelligence model that captures the behavior of a given problem in nodes that represent knowledge in the domain, and offers the means to study their influence and interrelation. Static and dynamic analysis over the resulting ML-FCM helped us identify the prevailing drivers towards the migration to a microservices architecture.
Keywords: Microservices architectures; Monolith migration; Multi-layer fuzzy cognitive maps