Designing Microservices Using AI: A Systematic Literature Review

cic.institucionOrigenLaboratorio de Investigación y Formación en Informática Avanzada (LIFIA)
cic.isFulltextSI
cic.isPeerReviewedSI
cic.lugarDesarrolloLaboratorio de Investigación y Formación en Informática Avanzada (LIFIA)
cic.parentTypeArtículo
cic.versionPublicada
dc.date.accessioned2025-03-26T12:50:20Z
dc.date.available2025-03-26T12:50:20Z
dc.identifier.urihttps://digital.cic.gba.gob.ar/handle/11746/12452
dc.titleDesigning Microservices Using AI: A Systematic Literature Reviewen
dc.typeRevisión
dcterms.abstractMicroservices 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.en
dcterms.creator.authorNarváez, Daniel
dcterms.creator.authorBattaglia, Nicolas
dcterms.creator.authorFernández, Alejandro
dcterms.creator.authorRossi, Gustavo Héctor
dcterms.identifier.otherDOI: 10.3390/software4010006
dcterms.identifier.otherISSN: 2674-113X
dcterms.identifier.urlhttps://www.mdpi.com/2674-113X/4/1/6
dcterms.isPartOf.issuevol. 4, no. 1
dcterms.isPartOf.seriesSoftware
dcterms.issued2025
dcterms.languageInglés
dcterms.licenseAttribution 4.0 International (BY 4.0)
dcterms.subjectmicroservices designen
dcterms.subjectartificial intelligenceen
dcterms.subjectservice decompositionen
dcterms.subjectmachine learningen
dcterms.subjectnatural language processingen
dcterms.subjectAI in software architectureen
dcterms.subjectmicroservices performance optimizationen
dcterms.subjectAI-driven decision-makingen
dcterms.subjectdistributed systemsen
dcterms.subjectgenerative AIen
dcterms.subject.materiaCiencias de la Computación e Información

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