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

Authors

  • Nazarenko Volodymyr National University of Life and Environmental Sciences of Ukraine image/svg+xml

DOI:

https://doi.org/10.31548/itees.2026.01.009

Keywords:

Unreal Engine 5, multiplayer game development, replication graph, DevOps/LiveOps, microservices, MVP, data-driven development

Abstract

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.

Recieved 2026-02-09

Accepted 2026-03-16

Author Biography

  • Nazarenko Volodymyr, National University of Life and Environmental Sciences of Ukraine

    Ph.D., Computer Systems, Networks and Cybersecurity Department, Faculty of Information Technologies, National University of Life and Environmental Sciences of Ukraine.
    ORCID: https://orcid.org/0000-0002-7433-2484

References

1. Alonso, S., Kalinowski, M., Ferreira, B., Barbosa, S. D. J., & Lopes, H. (2021). A systematic mapping study on the use of software engineering practices to develop MVPs (Technical report/preprint PDF). https://www-di.inf.puc-rio.br/~kalinowski/publications/AlonsoKVFB21.pdf.

2. Chueca, J., Verón, J., Font, J., Pérez, F., & Cetina, C. (2024). The consolidation of game software engineering: A systematic literature review of software engineering for industry-scale computer games. Information and Software Technology, 169, 107330. https://doi.org/10.1016/j.infsof.2023.107330.

3. Di Francesco, P., Malavolta, I., & Lago, P. (2019). Architecting with microservices: A systematic mapping study. Journal of Systems and Software, 150, 77–97. https://www.sciencedirect.com/science/article/abs/pii/S0164121219300019.

4. Epic Games. Lyra sample game in Unreal Engine (UE5 documentation). Epic Developer Community. https://dev.epicgames.com/documentation/en-us/unreal-engine/lyra-sample-game-in-unreal-engine.

5. Epic Games. Online Subsystem EOS plugin in Unreal Engine. Epic Developer Community. https://dev.epicgames.com/documentation/en-us/unreal-engine/online-subsystem-eos-plugin-in-unreal-engine.

6. Epic Games. Replication Graph in Unreal Engine. Epic Developer Community. https://dev.epicgames.com/documentation/en-us/unreal-engine/replication-graph-in-unreal-engine.

7. Epic Games. Setting up dedicated servers in Unreal Engine. Epic Developer Community. https://dev.epicgames.com/documentation/en-us/unreal-engine/setting-up-dedicated-servers-in-unreal-engine.

8. Epic Games. Enable and configure Online Services EOS in Unreal Engine. Epic Developer Community. https://dev.epicgames.com/documentation/en-us/unreal-engine/enable-and-configure-online-services-eos-in-unreal-engine.

9. Epic Games. (2018). Replication graph overview and proper replication methods. Unreal Engine Tech Blog. https://www.unrealengine.com/en-US/tech-blog/replication-graph-overview-and-proper-replication-methods.

10. Kasenides, N., & Paspallis, N. (2022). Athlos: A framework for developing scalable MMOG backends on commodity clouds. Software, 1(1), 107–145. https://doi.org/10.3390/software1010006.

11. Mizutani, W. K., Daros, V. K., & Kon, F. (2021). Software architecture for digital game mechanics: A systematic literature review. Entertainment Computing, 38, 100421. https://doi.org/10.1016/j.entcom.2021.100421.

12. Unrealist.org. (2023). Lyra deep dive: Chapter 2 - Experiences. https://unrealist.org/lyra-part-2/.

13. Leite, L., Rocha, C., Kon, F., Milojicic, D., & Meirelles, P. (2019). A survey of DevOps concepts and challenges. ACM Computing Surveys, 52(6), Article 127, 1–35. https://doi.org/10.1145/3359981.

14. Auer, F., Ros, R., Kaltenbrunner, L., Runeson, P., & Felderer, M. (2021). Controlled experimentation in continuous experimentation: Knowledge and challenges. Information and Software Technology, 134, 106551. https://doi.org/10.1016/j.infsof.2021.106551.

15. Giaimo, F., Andrade, H., & Berger, C. (2020). Continuous experimentation and the cyber–physical systems challenge: An overview of the literature and the industrial perspective. Journal of Systems and Software, 170, 110781. https://doi.org/10.1016/j.jss.2020.110781.

16. Erthal, V. M., de Souza, B. P., dos Santos, P. S. M., & Travassos, G. H. (2023). Characterization of continuous experimentation in software engineering: Expressions, models, and strategies. Science of Computer Programming, 229, 102961. https://doi.org/10.1016/j.scico.2023.102961.

Downloads

Published

2026-04-22

Issue

Section

Computer Science