A Digital Twin Framework for Enterprise IT Operations: Bridging Application Development, Infrastructure Management, Product Migration, and Operational Support
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V6I1P125Keywords:
Digital Twin, Enterprise IT Operations, Devops, Application Development, Infrastructure Management, Product Migration, Operational Support, IT Service Management (ITSM), Aiops, Observability, Predictive Analytics, Cloud Computing, Digital Transformation, Enterprise Architecture, Intelligent OperationsAbstract
Enterprise IT environments have become increasingly complex due to the rapid growth of cloud computing, microservices architectures, DevOps practices, hybrid infrastructures, and continuous product evolution. Traditional management approaches often operate in silos, creating challenges in application development, infrastructure management, product migration, and operational support. This paper proposes a comprehensive Digital Twin Framework for Enterprise IT Operations that establishes a dynamic virtual representation of enterprise technology ecosystems. The framework integrates real-time operational data, application lifecycle information, infrastructure telemetry, migration intelligence, and support analytics into a unified digital environment. By leveraging technologies such as artificial intelligence, machine learning, observability platforms, predictive analytics, and automation, the proposed framework enables continuous monitoring, simulation, impact analysis, capacity planning, risk assessment, and proactive decision-making across the IT lifecycle. The framework bridges the gap between development and operations by providing end-to-end visibility of applications, infrastructure resources, business services, and migration dependencies. Furthermore, it supports scenario-based testing, root-cause analysis, performance optimization, and predictive maintenance, reducing operational risks and improving service reliability. A conceptual architecture is presented to demonstrate how digital twin capabilities can enhance collaboration among development, infrastructure, migration, and support teams while increasing organizational agility and operational resilience. The study contributes a unified approach to enterprise IT management and highlights the potential of digital twins as a strategic enabler for intelligent, data-driven IT operations.
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References
[1] Aheleroff, S., Xu, X., Lu, Y., Aristizabal, M., Velásquez, J. P., Joa, B., & Valencia, Y. (2021). Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model. Advanced Engineering Informatics, 47. https://doi.org/10.1016/j.aei.2020.101225
[2] Broo, D. G., Bravo-Haro, M., & Schooling, J. (2022). Design and Implementation of a Smart Infrastructure Digital Twin. Automation in Construction, 136. https://doi.org/10.1016/j.autcon.2022.104171
[3] Cheng, J., Zhang, H., Tao, F., & Juang, C. F. (2020). DT-II: Digital Twin Enhanced Industrial Internet Reference Framework Towards Smart Manufacturing. Robotics and Computer-Integrated Manufacturing, 62. https://doi.org/10.1016/j.rcim.2019.101881
[4] Edrisi, F., Perez-Palacin, D., Caporuscio, M., et al. (2024). Developing and Evolving a Digital Twin of the Organization. IEEE Access. https://ieeexplore.ieee.org/document/10478895
[5] El Mokhtari, K., Panushev, I., & McArthur, J. J. (2022). Development of a Cognitive Digital Twin for Building Management and Operations. Frontiers in Built Environment, 8. https://doi.org/10.3389/fbuil.2022.856873
[6] Empl, P., Koch, D., Dietz, M., & Pernul, G. (2024). Digital Twins in Security Operations: State of the Art and Future Perspectives. ACM Computing Surveys. https://doi.org/10.1145/3746279
[7] Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 8, 108952–108971. https://doi.org/10.1109/ACCESS.2020.2998358
[8] Grieves, M., & Vickers, J. (2017). Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. In Transdisciplinary Perspectives on Complex Systems. Springer.
[9] Ivanov, D. (2024). Conceptualisation of a 7-Element Digital Twin Framework in Supply Chain and Operations Management. International Journal of Production Research. https://doi.org/10.1080/00207543.2023.2217291
[10] Kim, G., Humble, J., Debois, P., & Willis, J. (2016). The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations. IT Revolution Press.
[11] Lu, Q., Xie, X., Parlikad, A. K., & Schooling, J. M. (2020). Digital Twin-Enabled Anomaly Detection for Built Asset Monitoring in Operation and Maintenance. Automation in Construction, 118. https://doi.org/10.1016/j.autcon.2020.103277
[12] Lu, Q., Xie, X., Parlikad, A. K., & Schooling, J. M. (2022). Moving from Building Information Models to Digital Twins for Operation and Maintenance. Smart Infrastructure and Construction, 174(2), 46–55.
[13] Meierhofer, J., Schweiger, L., Lu, J., Züst, S., West, S., & Stoll, O. (2021). Digital Twin-Enabled Decision Support Services in Industrial Ecosystems. Applied Sciences, 11(23), 11418. https://doi.org/10.3390/app112311418
[14] Moyne, J., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., & Barton, K. (2020). A Requirements Driven Digital Twin Framework: Specification and Opportunities. IEEE Access, 8, 107781–107801.
[15] Pang, T. Y., Pelaez Restrepo, J. D., Cheng, C. T., Yasin, A., Lim, H., & Miletic, M. (2021). Developing a Digital Twin and Digital Thread Framework for an Industry 4.0 Shipyard. Applied Sciences, 11(3), 1097. https://doi.org/10.3390/app11031097
[16] Rahmani, R., Jesus, C., & Lopes, S. I. (2024). Implementations of Digital Transformation and Digital Twins: Exploring the Factory of the Future. Processes, 12(4), 787. https://doi.org/10.3390/pr12040787
[17] Rosen, K. M., & Pattipati, K. R. (2023). Operating Digital Twins Within an Enterprise Process. In The Digital Twin. Springer.
[18] Santos, R., Piqueiro, H., Dias, R., & Rocha, C. D. (2024). Transitioning Trends into Action: A Simulation-Based Digital Twin Architecture for Enhanced Strategic and Operational Decision-Making. Computers & Industrial Engineering, 194.
[19] Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019). Digital Twin in Industry: State-of-the-Art. IEEE Transactions on Industrial Informatics, 15(4), 2405–2415. https://doi.org/10.1109/TII.2018.2873186
[20] West, S., Stoll, O., Meierhofer, J., & Züst, S. (2021). Digital Twin Providing New Opportunities for Value Co-Creation Through Supporting Decision-Making. Applied Sciences, 11(9), 3750. https://doi.org/10.3390/app11093750
[21] Werbińska-Wojciechowska, S., Giel, R., & Winiarska, K. (2024). Digital Twin Approach for Operation and Maintenance of Transportation SystemSystematic Review. Sensors, 24(18), 6069. https://doi.org/10.3390/s24186069
[22] Yan, M. R., Hong, L. Y., & Warren, K. (2022). Integrated Knowledge Visualization and the Enterprise Digital Twin System for Supporting Strategic Management Decision. Management Decision, 60(4), 1095–1116.
[23] Yu, G., Wang, Y., Mao, Z., Hu, M., Sugumaran, V., & Zhou, H. (2021). A Digital Twin-Based Decision Analysis Framework for Operation and Maintenance of Tunnels. Tunnelling and Underground Space Technology, 112. https://doi.org/10.1016/j.tust.2021.103998
[24] Zhao, J., Feng, H., Chen, Q., & De Soto, B. G. (2022). Developing a Conceptual Framework for the Application of Digital Twin Technologies to Revamp Building Operation and Maintenance Processes. Journal of Building Engineering, 49. https://doi.org/10.1016/j.jobe.2022.104028.
