Aspectos de Arquitectura y diseño en aplicaciones distribuidas (Web, Móviles, IoT, etc) con foco en Microservicios

Permanent URI for this collection

https://repositorio.uai.edu.ar/handle/123456789/4685

Browse

Browsing Aspectos de Arquitectura y diseño en aplicaciones distribuidas (Web, Móviles, IoT, etc) con foco en Microservicios by Author "Fernández, Alejandro"
  • Item
    Behavior-Driven Microservice Architecture: un marco metodológico para la identificación iterativa de microservicios en proyectos ágiles greenfield
    (Universidad Abierta Interamericana. Facultad de Tecnología Informática, 2025) Battaglia, Nicolás ; Rossi, Gustavo Hector ; Fernández, Alejandro ; Narváez Flores, José Daniel
    La adopción de arquitecturas basadas en microservicios plantea desafíos significativos en la fase de diseño, particularmente en contextos greenfield donde las decisiones iniciales condicionan la mantenibilidad futura. Aunque existen aportes relevantes desde Domain-Driven Design (DDD) y Behavior-Driven Development (BDD), persiste una brecha metodológica: los enfoques actuales suelen ser teóricos, carecen de mecanismos explícitos de trazabilidad entre requisitos funcionales y decisiones arquitectónicas, o se enfocan en escenarios de reingeniería brownfield. Este trabajo introduce Behavior-Driven Microservice Architecture (BDMA), un marco metodológico sistemático, iterativo y reproducible que guía la identificación, diseño y evolución de microservicios en proyectos ágiles greenfield. BDMA integra principios de DDD, técnicas de BDD y prácticas de arquitectura evolutiva para trans-formar escenarios funcionales en bounded contexts, contratos de servicio y registros de decisiones arquitectónicas. Como aporte principal, BDMA ofrece un enfoque práctico que asegura alineación entre requisitos y arquitectura, fomenta la colaboración interdisciplinaria y habilita trazabilidad completa desde los escenarios BDD hasta la implementación, demostrada mediante una Architectural Kata ilustrativa.
  • Item
    Designing Microservices Using AI: A Systematic Literature Review
    (MDPI, 2025-3-19) Narváez Flores, José Daniel ; Battaglia, Nicolás ; Fernández, Alejandro ; Rossi, Gustavo Hector
    Microservices architecture has emerged as a dominant approach for developing scalable and modular software systems, driven by the need for agility and independent deployability. However, designing these architectures poses significant challenges, particularly in service decomposition, inter-service communication, and maintaining data consistency. To address these issues, artificial intelligence (AI) techniques, such as machine learning (ML) and natural language processing (NLP), have been applied with increasing frequency to automate and enhance the design process. This systematic literature review examines the application of AI in microservices design, focusing on AI-driven tools and methods for improving service decomposition, decision-making, and architectural validation. This review analyzes research studies published between 2018 and 2024 that specifically focus on the application of AI techniques in microservices design, identifying key AI methods used, challenges encountered in integrating AI into microservices, and the emerging trends in this research area. The findings reveal that AI has effectively been used to optimize performance, automate design tasks, and mitigate some of the complexities inherent in microservices architectures. However, gaps remain in areas such as distributed transactions and security. The study concludes that while AI offers promising solutions, further empirical research is needed to refine AI’s role in microservices design and address the remaining challenges.