Vehicle-to-everything represent a major step in the evolution of Intelligent Transportation Systems (ITS), by allowing vehicles and the infrastructure to share information seamlessly. The new sensors introduced by the next generation of vehicles, that can be autonomous or partially assisted, generate huge volumes of data that, in some scenarios, may not be handled by the available resource-constrained devices. Therefore, edge and fog concepts have been applied to vehicular networks under Vehicle Edge Computing (VEC), to perform computational offloading, content caching, data management, flexible network management, security, and others. Technologies like virtualization and containerization are the cornerstones when addressing service deployment on edge and cloud environments. This work assesses different schemes of VEC service deployments to understand their use with the deterministic and reliable nature of some critical VEC services, such as an open-source implementation of the ETSI C-ITS protocol suite. Service prioritization and preemption are explored in order to achieve an upper-bound latency in native and containerized services deployment. The results show that the preemption leads to a slight increase in the average and median processing delay, but it also results in positive effects for real-time services; the prioritization of services is able to provide lower upper-bound latency, providing a performance without guarantees but with an expected delay.