Increasing software deployment speed in agile environments through automated configuration management
1 Independent Researcher, Sheffield, UK.
2 The Vanguard Group, Charlotte, North Carolina, USA.
3 Independent Researcher, United Kingdom.
4 Etihuku Pty Ltd, Midrand, Gauteng, South Africa.
Review
International Journal of Engineering Research Updates, 2024, 07(02), 028–035.
Article DOI: 10.53430/ijeru.2024.7.2.0047
Publication history:
Received on 02 October 2024; revised on 09 November 2024; accepted on 12 November 2024
Abstract:
In today's fast-paced software development landscape, the ability to deploy applications rapidly while maintaining high quality is crucial for Agile teams. This paper explores the impact of Automated Configuration Management (ACM) on enhancing software deployment speed within Agile environments. By examining the complexities of modern software systems and the challenges associated with manual configuration processes, the study underscores the necessity of automation to streamline workflows and reduce errors. Key ACM tools such as Ansible, Puppet, and Chef are discussed and their role in facilitating efficient configuration management. The integration of ACM with Continuous Integration (CI) and Continuous Deployment (CD) practices is highlighted as a pivotal strategy for achieving faster deployment cycles and improved software reliability. Additionally, the paper emphasizes the importance of fostering a DevOps culture, where collaboration between development and operations teams enhances the overall efficiency of the software delivery pipeline. Ultimately, the findings present a roadmap for Agile teams seeking to implement automated solutions, offering practical recommendations to optimize their deployment processes and adapt to the evolving demands of the market.
Keywords:
Automated Configuration Management; Agile Development; Software Deployment; Continuous Integration; Continuous Deployment; DevOps Collaboration
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0