Ultra-wideband (UWB)-based localization systems offer a cost-effective solution with relatively accurate performance. However, in a distributed ROS 2 multi-robot system, sudden failures of localization-related programs such as the UWB ranging error mitigation program, can degrade overall system accuracy. While Kubernetes provides automated deployment capabilities, its performance with ROS 2 remains unevaluated within a specific robotic application. This letter addresses this gap by integrating Kubernetes with ROS 2 in a UWB-based multi-robot localization system. An edge cluster composed of five Jetson Nano and one laptop is orchestrated with Kubernetes. The node of Jetson Nano is set on each robot. We then deploy LSTM-based UWB ranging error mitigation programs on edge nodes. By inducing failures in various combinations of LSTM programs, we comprehensively assess the system's resilience and robustness through position error evaluation under different failure scenarios.