文件名称:
苏宁Heat实践分享: Explore and enable elastic cluster for Internet applications
开发工具:
文件大小: 1015kb
下载次数: 0
上传时间: 2015-06-22
详细说明： Suning Cloud Commerce is one of the largest privately owned retailers in China. Suning has more than 1600 stores covering over 700 cities of Mainland China, Hong Kong and Japan, and its e-commerce platform, Suning.com ranks among top three Chinese B2C companies. There are more than 180,000 employees, thousands of mixed power, x86, storage servers and tens of thousands of virtual machines from several large data center across China, HongKong and Japan. KVM, oVirt and virtualization technologies are widely used, and there are also very large server farm for VDI. Suning starts OpenStack journery from Jun 2013, and in 2014, an OpenStack based production environment has been put in use, to server Android Mobile Application and Service, Search Engine, Retailer related business needs, plus critical code repository server. More than half are resource intensive and heavy loaded virtual machines Cinder multi-backend provides extra storage by leveraging LVM and Gluster. A light VDI solution to serve desktop users by leveraging open source spice. Within this deployment, network separated and openvswitch bonding is supported. The successful story leads to large scale OpenStack deployment, and heat's auto-scaling pretty fits the scenarios for Suning's popular Internet applications. Here we use Heat to assiste 2 kinds of applications: 1. Eleastic Web computation. The web cluster that we are using is IHS + WAS, it is one of major web applications that serve tens of million visitors, and the visits changes sharply. We need to adjust the cluster scale based on visits and also CPU load; 2.Real-time image thumbnail processing. This requires to generate image and document preview, plus real-time video-transcoding. The distributed scheduling framework is used, Beyond this, we also leverage OpenStack Heat, to dynanically create or destroy workers based on requests. For example, there are concurrent image thumbnail requests, at minimum, there are less than 10 works per seconds to serve the requests. However during peak time, there might be thousands of workers to be created. This demand the clusters to be expand or shrink fully automated and fast response. Once the request volume drop down, the resources should be released immediately to be reused by other kind of jobs. We will share our story, experience and practice to enable such kind of big cloud and how to support them, best practise and lesson learn. ...展开收缩
(系统自动生成,下载前可以参看下载内容)
下载文件列表
相关说明
- 本站资源为会员上传分享交流与学习,如有侵犯您的权益,请联系我们删除.
- 本站是交换下载平台，提供交流渠道，下载内容来自于网络，除下载问题外，其它问题请自行百度。
- 本站已设置防盗链，请勿用迅雷、QQ旋风等多线程下载软件下载资源，下载后用WinRAR最新版进行解压.
- 如果您发现内容无法下载，请稍后再次尝试；或者到消费记录里找到下载记录反馈给我们.
- 下载后发现下载的内容跟说明不相乎，请到消费记录里找到下载记录反馈给我们，经确认后退回积分.
- 如下载前有疑问，可以通过点击"提供者"的名字，查看对方的联系方式，联系对方咨询.
