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http://dx.doi.org/10.14372/IEMEK.2020.15.3.129

Kubernetes Scheduler Framework Implementation with Realtime Resource Monitoring  

Kim, Tae-Young (Daegu University)
Lee, Jae-Ryun (Kyungpook National University)
Kim, Tae-Hyun (Daegu University)
Chun, In-Geol (ETRI)
Park, Jeman (ETRI)
Jin, Sunggeun (Daegu University)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.15, no.3, 2020 , pp. 129-137 More about this Journal
Abstract
Kubernetes is one of the most widely used tool in cloud computing environments. It m anages POD as a basic operational unit, providing a isolated environments through container tech nology. Basically, its scheduler properly allocates POD, considering the utilizations of CPUs, mem ories and volumes on hosts. In our work, we develop a customized scheduling framework additio nally considering network resources. In the framework, we can monitor the dynamic variations of resources and make it possible to utilize the resources for the scheduler. This framework offers not only observing necessary information but also visualizing the data to scheduler for providing convenience.
Keywords
Cloud computing; Container; Kubernetes; Monitoring system; POD placement;
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