Harnessing Artificial Intelligence in Continuous Integration and Continuous Delivery: A Comprehensive Survey
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Review Papers | Software Engineering | United States of America | Volume 14 Issue 4, April 2025 | Popularity: 5.7 / 10


     

Harnessing Artificial Intelligence in Continuous Integration and Continuous Delivery: A Comprehensive Survey

Vipin Mathew


Abstract: DevOps reshapes software delivery by integrating development and operations to drive speed, collaboration, and reliability. This survey explores the growing role of Artificial Intelligence (AI) and Machine Learning Operations (MLOps) in enhancing Continuous Integration and Continuous Deployment (CI/CD) pipelines. It reviews how AI-driven approaches, alongside cloud platforms like AWS, Azure, and Google Cloud, automate model deployment, experimentation, and monitoring. While modern CI/CD tools such as Jenkins, CircleCI, and Flux CD streamline processes, challenges remain in orchestrating diverse systems, ensuring data privacy, and maintaining model robustness. Future research must focus on standardizing MLOps practices and advancing automated monitoring to fully realize AI?s potential. By addressing these challenges, organizations can achieve more resilient, efficient, and intelligent software delivery.


Keywords: Development Operations, Continuous Integration and Continuous Deployment (CI/CD), Artificial Intelligence, Cloud infrastructure


Edition: Volume 14 Issue 4, April 2025


Pages: 2429 - 2434


DOI: https://www.doi.org/10.21275/SR25427081451


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Vipin Mathew, "Harnessing Artificial Intelligence in Continuous Integration and Continuous Delivery: A Comprehensive Survey", International Journal of Science and Research (IJSR), Volume 14 Issue 4, April 2025, pp. 2429-2434, https://www.ijsr.net/getabstract.php?paperid=SR25427081451, DOI: https://www.doi.org/10.21275/SR25427081451

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