In the fifth generation (5G) mobile networks, the number of user plane functions has increased, and, in contrast to previous generations. They can be deployed in a decentralized way and auto-scaled independently from their control plane functions. Moreover, the performance of the user plane functions can be boosted with the adoption of advanced acceleration techniques such as Vector Packet Processing (VPP). However, the increased number of user plane functions has also made load balancing a necessity, something we find has so far received little attention. Moreover, the introduction of VPP poses a challenge to the design of the auto-scaling of user-plane functions. In this paper, we address these two challenges by proposing a novel performance indicator for making better auto-scaling decisions, and by proposing three new dynamic load-balancing algorithms for the user plane of a VPP-based, softwarized 5G network. The novel performance indicator is estimated based on the VPP vector rate, and is used as a threshold for the auto-scaling process. The dynamic load-balancing algorithms take into account the number of bearers allocated for each user plane function and their VPP vector rate. We validated and evaluated our proposed solution in a 5G testbed. Our experiment results show that the scaling helps to reduce the packet latency for the user plane traffic, and our proposed load-balancing algorithms seem to give a better distribution of traffic load as compared to traditional static algorithms.