2021 · 44 citations · 20 references
ComputingCloud ComputingComputer ScienceCluster ComputingDistributed SystemsGrid ComputingCloud Resource ManagementCluster ArchitectureCluster ManagementFog ComputingResource ProvisioningCluster OrchestrationDistributed Resource ManagementFragmentationGeo-distributed SystemsKubernetes FederationOrchestrationOrchestration Platform ArchitectureOrchestration Platforms
Following the adoption of cloud computing, the proliferation of cloud data centers in multiple regions, and the emergence of computing paradigms such as fog computing, there is a need for integrated and efficient management of geo-distributed clusters. Geo-distributed deployments suffer from resource fragmentation, as the resources in certain locations are over-allocated while others are under-utilized. Orchestration platforms such as Kubernetes and Kubernetes Federation offer the conceptual models and building blocks that can be used to build integrated solutions that address the resource fragmentation challenge. In this work, we propose mck8s – an orchestration platform for multi-cluster applications on multiple geo-distributed Kubernetes clusters. It offers controllers that automatically place, scale, and burst multi-cluster applications across multiple geo-distributed Kubernetes clusters. mck8s allocates the requested resources to all incoming applications while making efficient use of resources. We designed mck8s to be easy to use by development and operation teams by adopting Kubernetes’ design principles and manifest files. We evaluated mck8s in a geo-distributed experimental testbed in Grid’5000. Our results show that mck8s balances the resource allocation across multiple clusters and reduces the fraction of pending pods to 6% as opposed to 65% in the case of Kubernetes Federation for the same workload.
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