TY - GEN
T1 - On the Resource Management of Kubernetes
AU - Kim, Eunsook
AU - Lee, Kyungwoon
AU - Yoo, Chuck
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/13
Y1 - 2021/1/13
N2 - Kubernetes is the most popular container orchestration platform that enables users to create and run multiple containers in cloud environments. Kubernetes offers resource management to isolate the resource usage of containers on a host server because performance isolation is an important factor in terms of service quality. This paper investigates whether the resource management of Kubernetes is sufficient to isolate the performance of containers. This is different from previous studies that mostly focuses on efficient resource management rather than the study on performance interference. We evaluate the performance interference 1) between CPU-intensive and networkintensive containers, and 2) between multiple network-intensive containers. Our evaluation results show that containers experience performance degradation by 50% due to the co-located containers even under the resource management of Kubernetes. This paper also points out that the root cause of the performance interference between multiple network-intensive containers is CPU contention, not network bandwidth. As a result, Kubernetes needs to consider the CPU usage of network-related workloads in resource management in order to mitigate the performance interference.
AB - Kubernetes is the most popular container orchestration platform that enables users to create and run multiple containers in cloud environments. Kubernetes offers resource management to isolate the resource usage of containers on a host server because performance isolation is an important factor in terms of service quality. This paper investigates whether the resource management of Kubernetes is sufficient to isolate the performance of containers. This is different from previous studies that mostly focuses on efficient resource management rather than the study on performance interference. We evaluate the performance interference 1) between CPU-intensive and networkintensive containers, and 2) between multiple network-intensive containers. Our evaluation results show that containers experience performance degradation by 50% due to the co-located containers even under the resource management of Kubernetes. This paper also points out that the root cause of the performance interference between multiple network-intensive containers is CPU contention, not network bandwidth. As a result, Kubernetes needs to consider the CPU usage of network-related workloads in resource management in order to mitigate the performance interference.
UR - http://www.scopus.com/inward/record.url?scp=85100748341&partnerID=8YFLogxK
U2 - 10.1109/ICOIN50884.2021.9333977
DO - 10.1109/ICOIN50884.2021.9333977
M3 - Conference contribution
AN - SCOPUS:85100748341
T3 - International Conference on Information Networking
SP - 154
EP - 158
BT - 35th International Conference on Information Networking, ICOIN 2021
PB - IEEE Computer Society
T2 - 35th International Conference on Information Networking, ICOIN 2021
Y2 - 13 January 2021 through 16 January 2021
ER -