Beyond Lift-and-Shift: Research in Intelligent Cloud-Native Transformation

Cloud migration transcends basic server relocation through intelligent automation that fundamentally restructures enterprise systems. Organizations harness artificial intelligence to decode legacy applications, extracting embedded business logic while mapping complex interdependencies. Banking giants modernize mainframe infrastructures using AI tools that parse COBOL, document forgotten functionality, and delineate microservice boundaries. Healthcare networks tackle patient management platforms where machine learning accelerates system comprehension while preserving regulatory compliance. Pattern recognition converts legacy architectures into cloud-native designs, systematically converting monoliths into distributed components. Retail enterprises modernize inventory systems by replacing batch workflows with serverless functions that react instantly to stock changes. Security integration permeates migration workflows via DevSecOps, embedding threat detection and automated remediation throughout transformation processes. Financial institutions implement zero-trust models during cloud transitions, maintaining microsecond latency for billions in daily trades. Advanced encryption lets medical providers run analytics on patient data that stays protected throughout processing. Modern monitoring platforms track performance across distributed architectures, spotting anomalies and forecasting capacity requirements before users experience issues. Entertainment platforms serving millions showcase how proactive monitoring prevents service disruptions during peak demand. These technological convergences create predictable transformation pathways that improve scalability, minimize operational complexity, and strengthen security postures. The synthesis of AI-driven evaluation, pattern-based conversion, integrated protection, and comprehensive visibility establishes new standards for enterprise modernization.