On the Resource Management of Kubernetes

Eunsook Kim; Kyungwoon Lee; Chuck Yoo

doi:10.1109/ICOIN50884.2021.9333977

On the Resource Management of Kubernetes

Eunsook Kim, Kyungwoon Lee, Chuck Yoo

Department of Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	35th International Conference on Information Networking, ICOIN 2021
Publisher	IEEE Computer Society
Pages	154-158
Number of pages	5
ISBN (Electronic)	9781728191003
DOIs	https://doi.org/10.1109/ICOIN50884.2021.9333977
Publication status	Published - 2021 Jan 13
Event	35th International Conference on Information Networking, ICOIN 2021 - Jeju Island, Korea, Republic of Duration: 2021 Jan 13 → 2021 Jan 16

Publication series

Name	International Conference on Information Networking
Volume	2021-January
ISSN (Print)	1976-7684

Conference

Conference	35th International Conference on Information Networking, ICOIN 2021
Country/Territory	Korea, Republic of
City	Jeju Island
Period	21/1/13 → 21/1/16

Bibliographical note

Funding Information:
∗Corresponding author: Chuck Yoo ∗This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation grant funded by the Korea government (MSIT) (No. 2015-0-00280, (SW Starlab) Next generation cloud infra-software toward the guarantee of performance and security SLA) and by National Research Foundation of Korea funded by the MSIT (No. NRF-2019H1D8A2105513).

Publisher Copyright:
© 2021 IEEE.

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICOIN50884.2021.9333977

Cite this

Kim, E, Lee, K & Yoo, C 2021, On the Resource Management of Kubernetes. in 35th International Conference on Information Networking, ICOIN 2021., 9333977, International Conference on Information Networking, vol. 2021-January, IEEE Computer Society, pp. 154-158, 35th International Conference on Information Networking, ICOIN 2021, Jeju Island, Korea, Republic of, 21/1/13. https://doi.org/10.1109/ICOIN50884.2021.9333977

@inproceedings{d6cab17d67ce4a38b3634e18592b7687,

title = "On the Resource Management of Kubernetes",

abstract = "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.",

author = "Eunsook Kim and Kyungwoon Lee and Chuck Yoo",

note = "Funding Information: ∗Corresponding author: Chuck Yoo ∗This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation grant funded by the Korea government (MSIT) (No. 2015-0-00280, (SW Starlab) Next generation cloud infra-software toward the guarantee of performance and security SLA) and by National Research Foundation of Korea funded by the MSIT (No. NRF-2019H1D8A2105513). Publisher Copyright: {\textcopyright} 2021 IEEE.; 35th International Conference on Information Networking, ICOIN 2021 ; Conference date: 13-01-2021 Through 16-01-2021",

year = "2021",

month = jan,

day = "13",

doi = "10.1109/ICOIN50884.2021.9333977",

language = "English",

series = "International Conference on Information Networking",

publisher = "IEEE Computer Society",

pages = "154--158",

booktitle = "35th International Conference on Information Networking, ICOIN 2021",

}

TY - GEN

T1 - On the Resource Management of Kubernetes

AU - Kim, Eunsook

AU - Lee, Kyungwoon

AU - Yoo, Chuck

N1 - Funding Information: ∗Corresponding author: Chuck Yoo ∗This work was partly supported by Institute of Information & Communications Technology Planning & Evaluation grant funded by the Korea government (MSIT) (No. 2015-0-00280, (SW Starlab) Next generation cloud infra-software toward the guarantee of performance and security SLA) and by National Research Foundation of Korea funded by the MSIT (No. NRF-2019H1D8A2105513). 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 -

On the Resource Management of Kubernetes

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this