TY - GEN
T1 - Containerized Workflow Builder for Kubernetes
AU - Shan, Chenggang
AU - Wang, Guan
AU - Xia, Yuanqing
AU - Zhan, Yufeng
AU - Zhang, Jinhui
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2022
Y1 - 2022
N2 - Docker and Kubernetes have recently dominated the whole cloud-native technology ecosystem and speeded up the containerization process of workflows. By optimizing the task scheduling order, workflow scheduling algorithms signifi-cantly improve the execution efficiency of workflows. However, existing works do not support workflow scheduling following the optimized task scheduling order on Kubernetes. How to ensure the consistency of workflow scheduling algorithms and Kubernetes scheduler in task scheduling order is challenging. In this paper, we propose a Containerized Workflow Builder (CWB) for Kubernetes, a framework able to implement con-tainerization of workflows in a two-level scheduling scheme and connect workflow scheduling algorithms to Kubernetes, ensuring the consistency of the task scheduling order. It uses the Informer component to watch the underlying resource events of Kubernetes, providing the event trigger mechanism to respond to event callback in real-time and implement containerization of workflows by the Client-go package. Experimental results show that our proposed CWB ensures the consistency of the workflow scheduling algorithms and Kubernetes scheduler in the task scheduling order. Compared with the state-of-the-art, the CWB achieves better performance in terms of average task pod execution time, average workflow lifecycle, and resource usage rate.
AB - Docker and Kubernetes have recently dominated the whole cloud-native technology ecosystem and speeded up the containerization process of workflows. By optimizing the task scheduling order, workflow scheduling algorithms signifi-cantly improve the execution efficiency of workflows. However, existing works do not support workflow scheduling following the optimized task scheduling order on Kubernetes. How to ensure the consistency of workflow scheduling algorithms and Kubernetes scheduler in task scheduling order is challenging. In this paper, we propose a Containerized Workflow Builder (CWB) for Kubernetes, a framework able to implement con-tainerization of workflows in a two-level scheduling scheme and connect workflow scheduling algorithms to Kubernetes, ensuring the consistency of the task scheduling order. It uses the Informer component to watch the underlying resource events of Kubernetes, providing the event trigger mechanism to respond to event callback in real-time and implement containerization of workflows by the Client-go package. Experimental results show that our proposed CWB ensures the consistency of the workflow scheduling algorithms and Kubernetes scheduler in the task scheduling order. Compared with the state-of-the-art, the CWB achieves better performance in terms of average task pod execution time, average workflow lifecycle, and resource usage rate.
KW - Containerization
KW - Event Trigger Mechanism
KW - Kubernetes
KW - Workflow Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85132431865&partnerID=8YFLogxK
U2 - 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00113
DO - 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00113
M3 - Conference contribution
AN - SCOPUS:85132431865
T3 - 2021 IEEE 23rd International Conference on High Performance Computing and Communications, 7th International Conference on Data Science and Systems, 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
SP - 685
EP - 692
BT - 2021 IEEE 23rd International Conference on High Performance Computing and Communications, 7th International Conference on Data Science and Systems, 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
Y2 - 20 December 2021 through 22 December 2021
ER -