In recent years Kubernetes has become the de facto standard in the realm of service orchestration. Despite its great benefits, there are still numerous challenges to make it compatible with decentralised cloud computing platforms. One of the challenges of mobile edge computing is that the location of the users is changing over time. This mobility will constantly alter the proximity of the users to their connected services. One solution to this problem is to regularly move services to computing nodes near the users. However, distributing the services in edge nodes only subject to user movements will result in the fragmentation of active nodes. This leads to having active nodes that do not use their full capacity. We have proposed a method called Mobile-Kube to reduce the latency of Kubernetes applications on mobile edge computing devices while maintaining energy consumption at a reasonable level. An experimental framework is designed on top of real-world Kubernetes clusters and real-world traces of mobile users' movements have been used to simulate the users' mobility. Experimental results show that Mobile-Kube can achieve similar energy consumption performance to a heuristic approach that focuses on reducing energy consumption only while reducing the latency of services by 43%.