As global mobile network usage increases rapidly and users demand lower latency, the importance of stable 5G networks is more critical than ever. Orchestrating mobile network backend by using Kubernetes is an up and coming way to ensure reliability and stability. This paper aims to identify ways to use load balancing inside a Kubernetes cluster to increase throughput and reduce latency in a mobile network system. We modeled a simplified mobile network system in a Kubernetes cluster and implemented a load balancer at the Service level. By running simulations on this model, we compared three existing Kubernetes algorithms and a dynamic algorithm using estimated workloads in terms of latency and throughput. The existing algorithms that are compared include Round Robin, Least Connections, and Random. The results show a potential to reduce latency by up to 31% compared to the native Random algorithm when utilizing a dynamic load balancer at the Service level.