Reducing Deployment Time in Large-Scale Cloud Systems Through Automated DevOps Pipelines
Site Reliability Engineer Jacksonville, Florida, USA, Haina Vladyslav · The American Journal of Engineering And Technology · 2025
This article explores methods for reducing deployment time in large-scale cloud systems through the implementation of automated DevOps pipelines. The focus lies on integrating the principles of Continuous Integration (CI) and Continuous Delivery (CD), adopting Infrastructure as Code (IaC), leveraging containerization and orchestration tools, and incorporating AI-driven solutions to optimize deployment workflows. The theoretical foundations of DevOps and CI/CD are examined alongside empirical data derived from comparative analyses of manual and automated deployment processes. The study also offers practical recommendations for improving the efficiency of cloud infrastructure. Findings confirm that the holistic application of these methods leads to reduced deployment times, lower operational costs, and enhanced system resilience. The insights presented in this paper will be relevant to both researchers and practitioners working on distributed cloud system development, where automated DevOps pipelines serve as a critical tool for minimizing deployment time and streamlining CI/CD processes. The study's outcomes and methodologies hold potential value for academia as well as industry professionals seeking to enhance the scalability, efficiency, and resilience of modern IT infrastructures.