[英]Kubeflow VS generic workflow orchestrator?
i am struggling understanding the functional role of Kubeflow (KF) compared with other (generic) workflow orchestrator.与其他(通用)工作流编排器相比,我很难理解 Kubeflow (KF) 的功能角色。
I know KF is oriented to ML tasks, and is built on top of Argo.我知道 KF 面向 ML 任务,并且构建在 Argo 之上。
Two questions:两个问题:
pre-defined component - https://www.kubeflow.org/docs/components/pipelines/sdk-v2/component-development/预定义组件 - https://www.kubeflow.org/docs/components/pipelines/sdk-v2/component-development/
python component - https://www.kubeflow.org/docs/components/pipelines/sdk-v2/python-function-components/ python 组件 - https://www.kubeflow.org/docs/components/pipelines/sdk-v2/python-function-components/
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.