OpenAIOS is an incubating open-source distributed OS kernel based on Kubernetes for AI workloads

Overview

OpenAIOS-Platform

build status docker pulls

简介

OpenAIOS Platform是一款基于OpenAIOS搭建起来的开发应用平台,OpenAIOS也依托于此对外输出核心能力,平台目前作为公有服务对外开放,网站地址是 https://openaios.4paradigm.com 。平台基于OpenAIOS搭建了一个统一的基础设施抽象层——算力规格,让应用开发者更少的关注基础设施;并且平台还提供AI的基础组件,让开发者在享受云原生带来的便利的同时,更加快速的开发、使用AI应用。

社区团队目前在进行积极的使用反馈收集和文档的迭代,在使用过程,遇到任何问题或疑问,都可以通过发送邮件到 [email protected] 来获取帮助。

部署

依赖

  • Kubernetes >= 1.16
  • NGINX Ingress Controller
  • Harbor
  • Keycloak
  • CephFS
  • Mongodb

安装

通过helm安装,配置好charts/pineapple/values.yaml,然后执行

helm install ${RELEASE_NAME} charts/pineapple -n ${RELEASE_NAMESPACE}

基础概念解释

开发环境

开发环境是一个单pod容器,通过JupyterLab、SSH和WebTerminal与环境进行交互, JupyterLab和WebTerminal可以让我们基于网页与环境交互,SSH可以与本地IDE打通,例如vscode、pycharm等。

算力规格

每个算力规格可能包括CPU cores、内存、PMEM、GPU、FPGA等多种异构计算资源。可以根据自己所需的计算负载来选择相应的算力规格。不同的算力规格可以设置不同的计费规则用于管理。

镜像

镜像是运行时环境,在创建开发环境或者应用的时候选择,公共镜像包含主流的机器学习组件,可以满足大部分开发需求,私有镜像完全由用户自定义,当前我们支持从dockerhub引入镜像。

应用市场

应用市场目前采用了社区通用的Helm Chart通用部署规范,我们向应用开发者提供了一些轻量化允许用户定制的组件,支撑应用的快速开发和上线,降低开发门槛,最终开发者可对公网暴露出自己的一套服务;对于应用使用者则可以快速使用到第四范式自研的OpenMLDB等一系列应用。

快速上手

如何在5分钟实现线性回归预测过程

第一步,创建开发环境:

  • 选择所需的算力规格
  • 选择镜像
  • 挂载数据,文件管理中的训练数据和代码可以挂载进开发环境内
  • 选择交互方式,选用JupyterLab进行交互,需要设置一个token 最后,点击“准备环境”。

1 2

第二步,通过Jupyterlab访问开发环境,点击下方的图标即可进入。 3

第三步,来到了Jupyterlab,Jupyterlab左侧是挂载进去的数据和代码,可以选择自带的python和终端等来编辑和运行代码。 4

Owner
4Paradigm
4Paradigm Open Source Community
4Paradigm
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