MDDOAI: A Model-Driven DevOps Approach to CI/CD Automation

Proceedings of the IEEE 66th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2025) 2025
Uldis Karlovs-Karlovskis, Oksana Ņikiforova, Oscar Pastor Lopez, Kristijans Vēveris

Since its emergence in 2009, DevOps has significantly transformed software engineering by streamlining integration and delivery workflows. While prior research has extensively examined DevOps practices and their evolution, limited attention has been given to automated generation of Continuous Integration and Continuous Delivery (CI/CD) pipelines directly from high-level software architecture models. Addressing this gap, Model-Driven DevOps with AI (MDDOAI) introduces a model-to-code solution that bridges the abstraction gap between design and deployment. It leverages Atlas Transformation Language (ATL) for model-to-model transformation and Acceleo for code generation, enabling the automated synthesis of deployable CI/CD pipeline configurations. The resulting prototype demonstrates the feasibility of scalable, model-driven automation in DevOps, offering a structured foundation for future extensible and maintainable pipeline engineering.

Atslēgas vārdi
Model-driven, DevOps, CI/CD, pipelines, metamodel, architecture
DOI
10.1109/ITMS67030.2025.11236630
Hipersaite
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11236630

Karlovs-Karlovskis, U., Ņikiforova, O., Pastor Lopez, O., Vēveris, K. MDDOAI: A Model-Driven DevOps Approach to CI/CD Automation. No: Proceedings of the IEEE 66th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2025), Latvija, Rìga, 9.-10. oktobris, 2025. https://ieeexplore.ieee.org/: IEEE Xplore, 2025, 1.-9.lpp. Pieejams: doi:10.1109/ITMS67030.2025.11236630

Publikācijas valoda
English (en)