The stringent delay requirements of Sixth-Generation (6G) networks necessitate efficient resource orchestration between the cloud and Multi-Access Edge Computing (MEC). This paper addresses the challenge of dynamic service migration in a hybrid MEC-Cloud environment where a single edge node, capable of hosting only one service at a time, must arbitrate between numerous services. We propose a novel queuing theory-based analytical model where migration decisions are triggered by user arrivals and departures. A key feature of the system is the ability to split the user base of a service between the low-delay MEC node and the remote cloud when that service is actively hosted on the edge. We introduce a migration policy designed to minimize the total End-to-End delay experienced by all users by dynamically selecting the optimal service for edge placement. The model derives steady-state formulas for key performance metrics, including the average number of users on the MEC and cloud and the overall mean system delay.