A Phased Modernization Model for Migrating Legacy I-Series Applications to Cloud-Native Java Architectures

Abstract

Enterprise systems developed on the IBM i (iSeries) platform still have a role to play in supporting mission-critical business processes across industries, but their structural inflexibility makes transformation to a cloud-native solution a big challenge. This review synthesizes existing methods for migrating such systems to cloud-native Java applications using phased modernization models, which allow progressive and risk-managed evolution. Key methodologies such as service decomposition, data migration strategies, and operational practices in accordance with microservices and DevOps ecosystems are critically discussed. Although architectural refactoring and adoption of microservices enhance the modularity, scalability and efficiency of deployment, successful transformation depends on the integration of data transition strategies, governance frameworks, and organizational maturity. The literature suggests that hybrid decomposition and phased migration are among the most promising approaches to the challenge of managing the complexity of tightly coupled legacy systems. Persistent challenges include reduced interoperability, aging codebases, limited refactoring support, a shrinking skilled workforce, and the lack of standard evaluation metrics and long-term empirical evidence. Emerging trends, including AI-assisted code transformation and data-driven modernization, represent promising future research directions.