International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Survey of Predict DevOps Readiness based on Machine Learning

Zahraa Nuri HasanStudent, Department of Software, College of Computer & Math., University of Mosul, IraqIbrahim Ahmed SalehProfessor, Department of Software, College of Computer & Math., University of Mosul, Iraq

Vol 9 No 5 (2025): Volume 9, Issue 5, May 2025 | Pages: 98-103

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 19-05-2025

doi Logo doi.org/10.47001/IRJIET/2025.905013

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Abstract

In the Software Development Life Cycle (SDLC), Development and Operations (DevOps) has given software more reliability, and enable to scalable within a little period. Software development is became is more effective in world today in become a core competency for every business also the machine learning is as obtained   interest. As companies increasingly use DevOps practices to enhance efficiency, quality, and timely software delivery, predicting DevOps readiness becomes increasingly vital and important to ensure successful software implementation. the contribution of this paper  presents a critical framework for machine learning and its use in predicting DevOps readiness in organizations through team collaboration and workflow monitoring using machine learning models and algorithms that are used for optimization, accuracy, and effective delivery of good results.

Keywords

DevOps, Machine learning, CI, CD, Pipeline, Ensemble learning, Automation


Citation of this Article

Zahraa Nuri Hasan, & Ibrahim Ahmed Saleh. (2025). Survey of Predict DevOps Readiness based on Machine Learning. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(5), 98-103. Article DOI https://doi.org/10.47001/IRJIET/2025.905013

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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