<![CDATA[Resource management, scalability, and Quality of Service are key challenges in deploying 5G networks, particularly regarding latency, throughput, and packet loss. Conventional network architectures often fail to meet the demands of high-speed and low-latency communication, especially for applications such as the Internet of Things and cloud computing. This study applies a Kubernetes-based clustering method to address these challenges to optimize 5G network performance through efficient resource allocation and load balancing. Experiments were conducted in a Containerized Network Function environment through simulations, demonstrating significant performance improvements. Test results recorded a 28.69% reduction in latency, a 34.52% increase in throughput, and a 32.14% reduction in packet loss compared to a non-clustered 5G network. These improvements are supported by Kubernetes features such as auto-scaling, traffic distribution, and real-time load balancing. This approach demonstrates that Kubernetes clustering effectively enhances Quality of Service, optimizes resource allocation, and improves the overall efficiency of 5G network systems. Keywords: 5G Networks, Clustering, Kubernetes, QoS, Resource Management]]>
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