Semantic Dependency in Microservice Architecture: A Framework for Definition and Detection

• URL: http://arxiv.org/abs/2501.11787v1
• Date: Mon, 20 Jan 2025 23:34:24 GMT
• Title: Semantic Dependency in Microservice Architecture: A Framework for Definition and Detection
• Authors: Amr S. Abdelfattah, Kari E Cordes, Austin Medina, Tomas Cerny,
• Abstract summary: This paper introduces the Semantic Dependency Matrix as an instrument to address these challenges. It shows that these hidden dependencies can exist independently of endpoint data dependencies, revealing critical connections that might otherwise be overlooked.
• Score: 0.0
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• Abstract: 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.

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