A UE5 DEVELOPMENT ADOPTION FRAMEWORK FOR MULTIPLAYER DEVELOPMENT: REPLICATION, SERVICES, OBSERVABILITY, AND LIVEOPS

<ns0:p>This paper proposes a practical, UE5-centered adoption framework that translates modern software development methodologies from Web/App, enterprise/heavy systems, AI systems, and contemporary game development into measurable production practices for multiplayer Unreal Engine 5 (UE5) teams. While Agile, MVP, DevOps, microservices, data-driven development, and architectural patterns are widely discussed, UE5 multiplayer imposes hard constraints that are often absent from generic methodology guidance: replication cost and relevance/dormancy management, server-authoritative state, dedicated server build and deployment operations, online session flows, and continuous delivery/LiveOps expectations. To address this “methodology translation” gap, we define a software-focused research design that operationalizes methodology adoption through implementable UE5 artifacts: a suite of test projects, multiplayer archetypes, and an instrumentation plugin stack for deterministic scenario execution, controlled network stress injection, replication observability, and standardized telemetry outputs. We present pilot-format result templates and case-study tables that connect methodology choices to objective UE5 indicators, including replication budget per client, temporal consistency of server simulation steps (server tick rate stability), session join reliability, build-to-playable time, crash-free server hours, and change lead time. A Lyra-style GameFeature plugin slice is introduced to demonstrate clean architectural boundaries and auditable iteration throughput via feature lifecycle telemetry tied to CI build identifiers. The paper synthesizes these results into a staged adoption map that prioritizes replication-first KISS discipline, multiplayer MVP defined as an operations-capable vertical slice, minimal services before microservice decomposition, data-driven tuning with safe rollbacks, and modular feature slices for scalable iteration. This framework is intended as a practical guide for UE5 multiplayer teams and as a foundation for larger empirical evaluations.Recieved2026-02-09Accepted 2026-03-16</ns0:p>