Abstract: The advent of Industry 4.0 is leading to a radical restructuring of industrial control architectures, transitioning from the rigid, hierarchical models defined by the ISA-95 pyramid toward agile, decentralized cloud–edge–terminal architectures. Leveraging high bandwidth and low latency, 5G technology is poised to function as the critical enabler of this evolution, facilitating the migration of industrial controllers, such as programmable logic controllers (PLCs), from the factory floor to cloud or edge servers to support large-scale, collaborative control via wireless networks. However, establishing direct controller-to-device (C2D) links over 5G for high-precision applications, such as motion control, faces two fundamental challenges. The first is protocol incompatibility: high-performance standards like Ethernet for Control Automation Technology (EtherCAT) operate at Layer 2 of the OSI model using custom Ethernet frames, rendering them strictly incompatible with standard, IP-based (Layer 3) 5G routing. The second, and more profound challenge, is a fundamental performance mismatch. While EtherCAT necessitates deterministic, microsecond-level synchronization via mechanisms such as distributed clocks (DCs), 5G networks remain subject to inherent latency jitter stemming from radio channel fluctuations, interference, and resource scheduling. This non-deterministic jitter compromises the sensitive timing of EtherCAT, potentially leading to synchronization loss, control-loop instability, and system failure. To overcome these limitations, this study proposes a comprehensive strategy for integrating 5G and EtherCAT within cloud-based motion control systems, offering a two-fold contribution: (1) to resolve protocol disparities, we design and implement an integration architecture based on the Virtual eXtensible Local Area Network (VxLAN). By employing network virtualization to construct a Layer 2 overlay atop the 5G IP underlay, this mechanism encapsulates entire EtherCAT frames within standard User Datagram Protocol (UDP) packets; this ensures transparent transmission across the infrastructure, effectively rendering the 5G network a virtual ethernet segment from the perspective of the control system; (2) Concurrently, to address the stability challenges posed by jitter, we introduce a novel quantitative performance evaluation framework. Recognizing that establishing connectivity is distinct from ensuring operational stability, this framework analyzes the impact of network jitter on EtherCAT’s periodic data exchange. Subsequently, we derive a mathematical constraint model that explicitly correlates the minimum stable control period with key network performance indicators. This model serves as a robust predictive tool, allowing engineers to assess the feasibility of motion-control applications before physical deployment. The efficacy of both the VxLAN-based integration architecture and the analytical model is validated through extensive experimentation on a physical testbed using a commercial 5G network. By benchmarking the system performance, we demonstrate the solution’s practical feasibility and confirm the accuracy of the constraint model's predictions. Finally, this research extends beyond a functional integration scheme to provide a theoretic methodology for assessing the viability of deterministic, real-time industrial applications over non-deterministic wireless channels. Leveraging the proposed 5G-based motion control performance analytical methodology, this work seeks to promote the future deployment of 5G and its evolutions such as 5G-Advanced and 6G, in the most demanding sectors of industrial automation.