TY - JOUR
T1 - AI Techniques in the Microservices Life-Cycle
T2 - a Systematic Mapping Study
AU - Moreschini, Sergio
AU - Pour, Shahrzad
AU - Lanese, Ivan
AU - Balouek, Daniel
AU - Bogner, Justus
AU - Li, Xiaozhou
AU - Pecorelli, Fabiano
AU - Soldani, Jacopo
AU - Truyen, Eddy
AU - Taibi, Davide
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/4
Y1 - 2025/4
N2 - 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.
AB - 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.
KW - AI
KW - Machine learning
KW - Microservices
UR - http://www.scopus.com/inward/record.url?scp=105001598708&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=105001598708&partnerID=8YFLogxK
U2 - 10.1007/s00607-025-01432-z
DO - 10.1007/s00607-025-01432-z
M3 - Article
AN - SCOPUS:105001598708
SN - 0010-485X
VL - 107
JO - Computing
JF - Computing
IS - 4
M1 - 100
ER -