Adaptive Cloud-Native Migration Framework for Secure Enterprise Financial Systems Using OpenShift and Distributed Microservices

Enterprise financial organizations are rapidly modernizing legacy application ecosystems to improve scalability, deployment efficiency, operational resilience, and security compliance. However, migration from traditional Platform-as-a-Service (PaaS) environments to containerized cloud-native infrastructures introduces substantial challenges involving service orchestration, dependency management, runtime stability, and secure workload transformation. This research proposes an adaptive cloud-native migration framework for secure enterprise financial systems using OpenShift Container Platform (OCP), distributed microservices, and automated deployment orchestration. The framework integrates containerized service transformation, Kubernetes-based workload scheduling, secure API communication, and infrastructure-aware deployment automation to support large-scale enterprise modernization. The proposed architecture incorporates Kafka-based asynchronous messaging, Vault-driven secret management, Docker image optimization, and CI/CD pipeline automation for improving migration reliability and deployment consistency across distributed environments. Mathematical workload-balancing models and distributed performance analysis are utilized to evaluate scalability, recovery efficiency, deployment latency, and infrastructure utilization under enterprise-scale financial workloads. The study aims to establish a scalable and secure migration strategy capable of improving operational continuity, deployment flexibility, and infrastructure resilience in modern financial cloud ecosystems.