Kubernetes networking is evolving as organizations shift away from VMware and adapt to increased demands from AI workloads. Experts predict that 2026 will see a growing interest in running virtual machines (VMs) on Kubernetes, driven by the appeal of consolidating containers and VMs into a single platform. However, the transition remains challenging. The different operational model requires skilled management, especially in networking, where issues like performance and identity preservation during migrations often complicate matters. Improvements are underway, but teams need to manage their expectations regarding the complexity of moving legacy workloads to Kubernetes. KubeVirt is emerging as a popular solution for running VMs within Kubernetes, though it presents a steep learning curve for operators accustomed to traditional environments like vCenter. The user experience still involves navigating fragmented tools and workflows, leading to networking headaches. Operators frequently encounter issues with changing IPs and multi-tenancy that require careful planning. While improvements are expected in areas like setup and network behavior, managing KubeVirt effectively demands expertise and patience. A notable trend is the rise of the "Kubernetworker," a new role blending networking and platform skills. As Kubernetes deployments grow in size and complexity, organizations need professionals who can handle both networking policies and troubleshoot issues like BGP and load balancing. This hybrid operator will play a critical role in managing network policies using tools like Cilium, which bridges the gap between different teams. As Kubernetes adapts to AI workloads, traditional networking approaches struggle to keep up with increased traffic and demands for predictable performance. The integration of eBPF technology is helping to meet these challenges by enhancing speed and efficiency. Finally, microsegmentation is becoming a priority as organizations address vulnerabilities in their Kubernetes environments. The focus is shifting toward simpler, more effective designs that prevent lateral movement of threats while maintaining operational efficiency. As the landscape of Kubernetes networking evolves, the need for reliable, programmable solutions continues to grow, influenced heavily by the demands of AI and the movement away from legacy systems.