Workload Deployment and Configuration Reconciliation at Scale in Kubernetes-Based Edge-Cloud Continuums

Abstract

Continuum computing promises the abstraction of physical node location and node platform stack in order to create a seamless application deployment and execution across edges and cloud data centres. For industrial IoT applications, the demand to generate data insights in conjunction with an installed base of increasingly capable edge devices is calling for appropriate continuum computing interfaces. Derived from a case study in industrial water flow monitoring and based on the industry's de-facto standard Kubernetes to deploy complex containerised workloads, we present an appropriate continuum deployment mechanism based on custom Kubernetes controllers and CI/CD, called Kontinuum Controller. Through synthetic experiments and a holistic cross-provider deployment, we investigate its scalability with emphasis on reconciling adjusted configuration per application and per node, a critical requirement by industrial customers. Our findings convey that Kubernetes by default would enter undesirable oscillation already for modestly sized deployments. Thus, we also discuss possible solutions.