Improvement in Efficiency and Reduction in Deployment Time Verifying Crucial Features of DevOps Using AWS and Azure

-, Sameera Bano (2024) Improvement in Efficiency and Reduction in Deployment Time Verifying Crucial Features of DevOps Using AWS and Azure. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research focuses on identifying cost-efficient solutions and deployment time in DevOps environments involving AWS and Azure cloud platforms. The research compares the two frameworks by using an assessment of key deployment statistics, resource consumption, and machine learning. It targets at measuring deployment time, the cost of deployment, and the testing of critical DevOps attributes in regard to automated rollbacks as well as pipeline evaluation. Examining the quantitative data and applying data-driven models, it becomes possible to conclude that AWS is superior at the deployment of applications if they are highly parallelized, whereas the resource management capabilities of Azure and its compatibility with Microsoft environments are noteworthy. The research also presents a new concept of integrating machine learning models with DevOps processes and pipelines for smart automation. The research offers organizations recommendations for choosing cloud platforms based on coverage of organizational DevOps needs while offering analytical data regarding deployment speed, resource control, and cost factors of cloud DevOps.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Gupta, Shaguna UNSPECIFIED
Uncontrolled Keywords:	Cloud Computing; DevOps; AWS; Azure; Machine Learning; Deployment Optimization
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	14 Jul 2025 13:33
Last Modified:	14 Jul 2025 13:33
URI:	https://norma.ncirl.ie/id/eprint/8074

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