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AI Techniques in the Microservices Life-Cycle: a Systematic Mapping Study
Journal article   Open access   Peer reviewed

AI Techniques in the Microservices Life-Cycle: a Systematic Mapping Study

S Moreschini, S Pour, I Lanese, D Balouek, J Bogner, Xiaozhou Li, F Pecorelli, J Soldani, E Truyen and D Taibi
Computing, Vol.107(4), pp.1-50
107
2025
Handle:
https://hdl.handle.net/10863/52243

Abstract

Artificial Intelligence (AI) Microservices Machine Learning
The use of AI in microservices (MSs) is an emerging field as indicated by a substantial number of surveys. However these surveys focus on a specific problem using specific AI techniques, therefore not fully capturing the growth of research and the rise and disappearance of trends. In our systematic mapping study, we take an exhaustive approach to reveal all possible connections between the use of AI techniques for improving any quality attribute (QA) of MSs during the DevOps phases. Our results include 16 research themes that connect to the intersection of particular QAs, AI domains and DevOps phases. Moreover by mapping identified future research challenges and relevant industry domains, we can show that many studies aim to deliver prototypes to be automated at a later stage, aiming at providing exploitable products in a number of key industry domains.
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s00607-025-01432-z1.53 MBDownloadView
Open Access
url
https://doi.org/10.1007/s00607-025-01432-zView

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