Cłapa, KonradGrudzień, KrzysztofSierszeń, Artur2023-09-222023-09-222023Cłapa K., Grudzień K., Sierszeń A., Performance Analysis of Machine Learning Platforms Using Cloud Native Technology on Edge Devices. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 195-200, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.31.978-83-66741-92-8http://hdl.handle.net/11652/4807https://doi.org/10.34658/9788366741928.31This article presents the results of an experiment performed on a machine learning edge computing platform composed of a virtualized environment with a K3s cluster and Kubeflow software. The study aimed to analyze the effectiveness of executing Kubeflow pipelines for simulated parallel executions. A benchmarking environment was developed for the experiment to allow system performance measurements based on parameters, including the number of pipelines and nodes. The results demonstrate the impact of the number of cluster nodes on computational time, revealing insights that could inform future decisions regarding increasing the effectiveness of running machine learning pipelines on edge devices.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionmachine learningartificial intelligencecloud computingedge computinginternet of thingsuczenie maszynowesztuczna inteligencjaprzetwarzanie w chmurzeprzetwarzanie brzegoweinternet rzeczyRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.31