Hongyu Zhu, Tina Samizadeh, Rute C. Sofia fortiss - research Institute of the Free State of Bavaria associated with the Technical University of Munich (TUM) Abstract--Autonomous Mobile Robots (AMRs) increasingly adopt containerized micro-services across the Edge-Cloud continuum. While Kubernetes is the de-facto orchestrator for such systems, its assumptions--stable networks, homogeneous resources, and ample compute capacity do not fully hold in mobile, resource-constrained robotic environments. The paper describes a case-study on smart-manufacturing AMR and performs an initial comparison between CODECO orchestration and standard Kubernetes using a controlled Kubernetes-in-Docker (KinD) environment. Metrics include pod deployment and deletion times, CPU and memory usage, and inter-pod data rates. The observed results indicate that CODECO offers reduced CPU consumption and more stable communication patterns, at the cost of modest memory overhead ( 10-15%) and slightly increased pod lifecycle latency due to secure overlay initialization. Kubernetes provides declarative configuration, automated scaling, and robust availability mechanisms that make it highly effective in cloud data-centers. However, its design assumptions, namely, the existence of relatively stable networks, abundant compute resources, and largely static infrastructure, do not fully hold in Edge-Edge and Edge-Cloud environments. In such settings, resources can be constrained and heterogeneous.