Semantic Dependency in Microservice Architecture
Microservices have been a key architectural approach for over a decade, transforming system design by promoting decentralization and allowing development teams to work independently on specific microservices. While loosely coupled microservices are ideal, dependencies between them are inevitable. Often, these dependencies go unnoticed by development teams. Although syntactic dependencies can be identified, tracking semantic dependencies — when multiple microservices share similar logic — poses a greater challenge. As systems evolve, changes made to one microservice can trigger ripple effects, jeopardizing system consistency and requiring updates to dependent services, which increases maintenance and operational complexity. Effectively tracking different types of dependencies across microservices is essential for anticipating the impact of such changes. This paper introduces the Semantic Dependency Matrix as an instrument to address these challenges from a semantic perspective. We propose an automated approach to extract and represent these dependencies and demonstrate its effectiveness through a case study. This paper takes a step further by demonstrating the significance of semantic dependencies, even in cases where there are no direct dependencies between microservices. It shows that these hidden dependencies can exist independently of endpoint or data dependencies, revealing critical connections that might otherwise be overlooked.
Sun 27 AprDisplayed time zone: Eastern Time (US & Canada) change
14:00 - 15:30 | Session 3: Micro-services and Configurable SystemsICSR at 204 Chair(s): Tommi Mikkonen University of Jyväskylä | ||
14:00 30mPaper | MONO2REST: Identification and exposition of micro-services: a reusable RESTification approach ICSR Matthéo Lecrivain Nantes Université, Hanifa Barry Université de Montréal, Dalila Tamzalit Nantes Université, Houari Sahraoui DIRO, Université de Montréal Pre-print | ||
14:30 30mPaper | Semantic Dependency in Microservice Architecture ICSR Amr Elsayed The University of Arizona, Kari E Cordes University of Arizona, Austin Medina University of Arizona, Tomas Cerny University of Arizona DOI Pre-print | ||
15:00 30mPaper | Unveiling the Impact of Sampling on Feature Selection for Performance Prediction in Configurable Systems ICSR João Marcello Bessa Rodrigues Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Millena Cavalcanti Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Mathieu Acher Univ Rennes, Inria, CNRS, IRISA, Markus Endler Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Juliana Alves Pereira PUC-Rio File Attached |