Automated Cloud Migration Pipelines: Trends, Tools, and Best Practices – A Survey

Abstract

The rapid advancement of cloud computing has necessitated efficient and reliable cloud migration strategies, as organizations increasingly transition their data to the cloud. This survey examines the evolving landscape of automated cloud migration, highlighting its benefits, risks, strategies, tools, and emerging trends. This survey examines the evolving landscape of automated cloud migration, highlighting its benefits, risks, strategies, tools, and emerging trends. It discusses migration approaches, rehosting, refactoring, re-platforming, repurchasing, and retaining and explores trends in automated migration, including AI-driven workload assessment, risk optimization, multi-cloud and hybrid adoption, and DevSecOps integration. Essential tools such as Azure Data Migration, AWS Cloud Data Migration, Docker, and Kubernetes are reviewed, along with best practices including CI/CD integration, Infrastructure as Code, agile development, cost modeling, and AI-driven adaptive control to ensure robust, scalable, and efficient migration pipelines. The survey identifies key challenges, including data security and privacy risks, regulatory compliance, operational disruptions, migration costs, complexity of legacy applications, and vendor lock-in. To address these, future research directions are proposed, such as AI-driven security and compliance frameworks, automated cost optimization models, intelligent workload assessment, adaptive multi-cloud strategies, and self-healing migration pipelines. By consolidating current strategies, tools, challenges, and research opportunities, this survey provides a comprehensive reference for organizations planning cloud adoption and establishes a foundation for future innovations in secure, efficient, and cost-effective cloud migration solutions.