Architectural Refactoring Strategies for Legacy Trade Systems in Cloud-Native Ecosystems

Abstract

Legacy trade systems continue to underpin critical financial operations, yet their monolithic architectures, rigid deployment models, and accumulated technical debt significantly constrain scalability, resilience, and adaptability in cloud-native environments. Direct migration approaches such as lift-and-shift or full system rewrites often fail to address these structural limitations and introduce unacceptable operational and regulatory risks. This paper examines architectural refactoring as a strategic pathway for modernizing legacy trade systems within cloud-native ecosystems. It proposes a layered refactoring framework encompassing structural decomposition, data decoupling, communication transformation, and infrastructure modernization, while preserving deterministic latency, transactional integrity, and regulatory compliance. The study further analyzes domain-specific refactoring patterns and governance considerations essential for trade systems, highlighting trade-offs between cloud elasticity and execution predictability. By framing refactoring as an incremental, risk-aware transformation rather than a purely technical exercise, this work contributes a structured approach to achieving sustainable modernization of trade platforms without disrupting mission-critical operations.