November 13–15, 2018 - Shanghai, China
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Wednesday, November 14 • 11:05 - 11:40
Kube-Arbitrator: A Batch System of Kubernetes - Da Ma, IBM & Ti Zhou

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Kubernetes started as a general purpose orchestration framework with a focus on serving jobs. But as it gains popularity, users want to run BigData and AI frameworks on Kubernetes, such as Spark, TensorFlow, etc. When running these batch processing frameworks in a multitenant system like Kubernetes, advanced scheduling features, e.g. fair-share scheduling, gang scheduling, become more important. In 2017, we launched a project into incubation, named kube-arbitrator, to provide policy-based resource scheduling for BigData and AI frameworks to meet these advanced scheduling and resource sharing requirements.

In this presentation, we will describe how we're trying to do batch scheduling in Kubernetes, and our journey building these components out of core.

avatar for Da Ma

Da Ma

Expert, Huawei
Kubernetes Maintainer, SIG-Scheduling Co-Leader, kube-batch Owner. Jilin University master’s degree, majoring in grid computing and distributed system. After graduation, he focus on resource management, resource scheduling in distributed system. | | Kubernetes Maintainer,SIG-Scheduling联合负责人,kube-batch... Read More →
avatar for Ti Zhou

Ti Zhou

Architect, Baidu Inc
Ti Zhou, Kubernetes member, currently serves as cloud software architect in Baidu Cloud, focusing on Baidu Cloud Container Engine and PaddlePaddle Deep Learning Framework, helps developers to deploy cloud-native machine learning on private and public cloud. | | 周倜,Kubern... Read More →

Wednesday November 14, 2018 11:05 - 11:40
2F Room 3
  • Skill Level Any