Benchmarking Container Orchestrations for ARM-Powered Edge Computing

Container orchestration provides the tools necessary to manage the complexities of edge computing. They ensure efficient, reliable, secure deployment and operation of containerized applications. The orchestrators are also pivotal in influencing the quality and cost-efficiency of service deployment by managing essential tasks like container provisioning, scheduling, scaling, and networking. Edge computing environments are resource-constrained, with limited CPU, memory, and network bandwidth compared to traditional cloud environments. Benchmarking helps identify which container orchestration frameworks perform best under these constraints, ensuring optimal resource utilization and performance. Therefore, a thorough benchmarking of these frameworks is crucial. Despite their importance, there is limited work on benchmarking container orchestration in real-world edge-computing scenarios. This paper introduces a systematic approach that facilitates benchmarking container orchestrators using real-world applications. We benchmark Docker Swarm, K3s, KubeEdge, and Nomad orchestrators using computer vision and data science applications. We designed an evaluation framework to assess container orchestration tools. The evaluation framework includes container provisioning time, receiving time, processing time, resource utilization, and throughput metrics. Additionally, we explore how various container orchestrations optimize resource utilization and compare their efficiency on ARM-based edge devices. The benchmark results indicate that the Nomad orchestrator excels in terms of lower latency and optimal resource utilization. KubeEdge and K3s demonstrate faster provisioning times, whereas Docker Swarm experiences communication overhead between manager and worker nodes.