Synergizing AWS DevOps and AI for Predictive Scaling in Legacy IT Transformations: Enhancing Efficiency and Innovation in Traditional Environments

In today's rapidly evolving digital landscape, organizations are increasingly recognizing the need to adopt DevOps practices to stay competitive and deliver value to customers more efficiently. However, transforming traditional IT environments poses significant challenges due to legacy systems, siloed teams, and entrenched processes. This paper explores how Amazon Web Services (AWS) DevOps tools and practices can be leveraged to facilitate this transformation, with a particular focus on integrating artificial intelligence (AI) and machine learning (ML) to enhance the DevOps lifecycle. We propose a comprehensive architecture for implementing AWS DevOps in traditional IT environments, illustrating the use of key AWS services such as CodeCommit, CodeBuild, CodePipeline, and ECS. Additionally, we demonstrate how AI and ML can be utilized for predictive scaling, automated code reviews, and intelligent monitoring, thereby increasing efficiency and fostering innovation. Through real - world examples and detailed implementation strategies, this paper aims to provide actionable insights for organizations seeking to modernize their IT infrastructure and operations.