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Merge pull request #33990 from Sea-n/fix-zh-link-blog
[zh] Fix links for blog
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content/zh/blog/_posts/2016-02-00-Kubernetes-Community-Meeting-Notes.md

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slug: kubernetes-community-meeting-notes
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title: " Kubernetes community meeting notes - 20160204 "
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date: 2016-02-09
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slug: kubernetes-community-meeting-notes
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url: /zh/blog/2016/02/Kubernetes-Community-Meeting-Notes
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#### February 4th - rkt demo (congratulations on the 1.0, CoreOS!), eBay puts k8s on Openstack and considers Openstack on k8s, SIGs, and flaky test surge makes progress.
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#### 2月4日 - rkt演示(祝贺 1.0 版本, CoreOS!), eBay 将 k8s 放在 Openstack 上并认为 Openstack 在 k8s, SIG 和片状测试激增方面取得了进展。
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#### 2 月 4 日 - rkt 演示(祝贺 1.0 版本,CoreOS!),eBay 将 k8s 放在 Openstack 上并认为 Openstack 在 k8s,SIG 和片状测试激增方面取得了进展。
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The Kubernetes contributing community meets most Thursdays at 10:00PT to discuss the project's status via a videoconference. Here are the notes from the latest meeting.
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* But need more work on e2e test suites
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* 书记员:Rob Hirschfeld
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* 演示视频(20分钟):CoreOS rkt + Kubernetes[Shaya Potter]
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* 期待在未来几个月内看到与rkt和k8s的整合(“rkt-netes”)。 还没有集成到 v1.2版本中
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* 演示视频(20 分钟):CoreOS rkt + Kubernetes [Shaya Potter]
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* 期待在未来几个月内看到与rkt和k8s的整合(“rkt-netes”)。 还没有集成到 v1.2 版本中
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* Shaya 做了一个演示(8分钟的会议视频参考)
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* rkt的CLI显示了旋转容器
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* rkt 的 CLI 显示了旋转容器
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* [注意:音频在点数上是乱码]
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* 关于 k8s&rkt 整合的讨论
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* 下周 rkt 社区同步:https://groups.google.com/forum/#!topic/rkt-dev/FlwZVIEJGbY
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* 下周 rkt 社区同步: https://groups.google.com/forum/#!topic/rkt-dev/FlwZVIEJGbY
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* Dawn Chen:
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* 将 rkt 与 kubernetes 集成的其余问题:1)cadivsor 2) DNS 3)与日志记录相关的错误
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* 但是需要在 e2e 测试套件上做更多的工作
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<!--
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To get involved in the Kubernetes community consider joining our [Slack channel][2], taking a look at the [Kubernetes project][3] on GitHub, or join the [Kubernetes-dev Google group][4]. If you're really excited, you can do all of the above and join us for the next community conversation -- February 11th, 2016. Please add yourself or a topic you want to know about to the [agenda][5] and get a calendar invitation by joining [this group][6].
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-->
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要参与 Kubernetes 社区,请考虑加入我们的[Slack 频道][2],查看 GitHub上的 [Kubernetes 项目][3],或加入[Kubernetes-dev Google 小组][4]。如果你真的很兴奋,你可以完成上述所有工作并加入我们的下一次社区对话-2016年2月11日。请将您自己或您想要了解的主题添加到[议程][5]并通过加入[此组][6]来获取日历邀请。
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要参与 Kubernetes 社区,请考虑加入我们的 [Slack 频道][2],查看 GitHub 上的
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[Kubernetes 项目][3],或加入 [Kubernetes-dev Google 小组][4]
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如果你真的很兴奋,你可以完成上述所有工作并加入我们的下一次社区对话 - 2016 年 2 月 11 日。
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请将你自己或你想要了解的主题添加到[议程][5]并通过加入[此组][6]来获取日历邀请。
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"https://youtu.be/IScpP8Cj0hw?list=PL69nYSiGNLP1pkHsbPjzAewvMgGUpkCnJ"
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[1]: https://github.com/kubernetes/kubernetes/pull/19714
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[2]: http://slack.k8s.io/
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[2]: https://slack.k8s.io/
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[3]: https://github.com/kubernetes/
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[4]: https://groups.google.com/forum/#!forum/kubernetes-dev
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[5]: https://docs.google.com/document/d/1VQDIAB0OqiSjIHI8AWMvSdceWhnz56jNpZrLs6o7NJY/edit#

content/zh/blog/_posts/2018-08-02-dynamically-expand-volume-csi.md

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title: 'Dynamically Expand Volume with CSI and Kubernetes'
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For more details, please visit: https://github.com/container-storage-interface/spec/blob/master/spec.md
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更多详细信息,请访问:https://github.com/container-storage-interface/spec/blob/master/spec.md
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更多详细信息,请访问: https://github.com/container-storage-interface/spec/blob/master/spec.md
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## Extend CSI and Kubernetes

content/zh/blog/_posts/2018-10-11-topology-aware-volume-provisioning.md

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The multi-zone cluster experience with persistent volumes is improving in Kubernetes 1.12 with the topology-aware dynamic provisioning beta feature. This feature allows Kubernetes to make intelligent decisions when dynamically provisioning volumes by getting scheduler input on the best place to provision a volume for a pod. In multi-zone clusters, this means that volumes will get provisioned in an appropriate zone that can run your pod, allowing you to easily deploy and scale your stateful workloads across failure domains to provide high availability and fault tolerance.
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通过提供拓扑感知动态卷供应功能,具有持久卷的多区域集群体验在 Kubernetes 1.12 中得到了改进。此功能使得 Kubernetes 在动态供应卷时能做出明智的决策,方法是从调度器获得为 Pod 提供数据卷的最佳位置。在多区域集群环境,这意味着数据卷能够在满足你的 Pod 运行需要的合适的区域被供应,从而允许您跨故障域轻松部署和扩展有状态工作负载,从而提供高可用性和容错能力。
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通过提供拓扑感知动态卷供应功能,具有持久卷的多区域集群体验在 Kubernetes 1.12
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中得到了改进。此功能使得 Kubernetes 在动态供应卷时能做出明智的决策,方法是从调度器获得为
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Pod 提供数据卷的最佳位置。在多区域集群环境,这意味着数据卷能够在满足你的 Pod
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运行需要的合适的区域被供应,从而允许你跨故障域轻松部署和扩展有状态工作负载,从而提供高可用性和容错能力。
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Before this feature, running stateful workloads with zonal persistent disks (such as AWS ElasticBlockStore, Azure Disk, GCE PersistentDisk) in multi-zone clusters had many challenges. Dynamic provisioning was handled independently from pod scheduling, which meant that as soon as you created a PersistentVolumeClaim (PVC), a volume would get provisioned. This meant that the provisioner had no knowledge of what pods were using the volume, and any pod constraints it had that could impact scheduling.
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在此功能被提供之前,在多区域集群中使用区域化的持久磁盘(例如 AWS ElasticBlockStore,Azure Disk,GCE PersistentDisk)运行有状态工作负载存在许多挑战。动态供应独立于 Pod 调度处理,这意味着只要您创建了一个 PersistentVolumeClaim(PVC),一个卷就会被供应。这也意味着供应者不知道哪些 Pod 正在使用该卷,也不清楚任何可能影响调度的 Pod 约束。
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在此功能被提供之前,在多区域集群中使用区域化的持久磁盘(例如 AWS ElasticBlockStore、
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Azure Disk、GCE PersistentDisk)运行有状态工作负载存在许多挑战。动态供应独立于 Pod
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调度处理,这意味着只要你创建了一个 PersistentVolumeClaim(PVC),一个卷就会被供应。
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这也意味着供应者不知道哪些 Pod 正在使用该卷,也不清楚任何可能影响调度的 Pod 约束。
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* GCE PD(包括 Regional PD)
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该机制允许您定义自己的拓扑边界,例如内部部署集群中的机架,而无需修改调度程序以了解这些自定义拓扑。
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该机制允许你定义自己的拓扑边界,例如内部部署集群中的机架,而无需修改调度程序以了解这些自定义拓扑。
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这意味着您可以在多个集群、环境和存储系统中使用相同的 Pod 规范。
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这意味着你可以在多个集群、环境和存储系统中使用相同的 Pod 规范。
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要启用此功能,您需要做的就是创建一个将 `volumeBindingMode` 设置为 `WaitForFirstConsumer` 的 StorageClass:
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要启用此功能,你需要做的就是创建一个将 `volumeBindingMode` 设置为 `WaitForFirstConsumer` 的 StorageClass:
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之后,您可以看到根据 Pod 设置的策略在区域中配置卷:
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之后,你可以看到根据 Pod 设置的策略在区域中配置卷:
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有关拓扑感知动态供应功能的官方文档可在此处获取:
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有关 CSI 驱动程序的文档,请访问: https://kubernetes-csi.github.io/docs/
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如果您对此功能有反馈意见或有兴趣参与设计和开发,请加入 [Kubernetes 存储特别兴趣小组](https://github.com/kubernetes/community/tree/master/sig-storage)(SIG)。我们正在快速成长,并始终欢迎新的贡献者。
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如果你对此功能有反馈意见或有兴趣参与设计和开发,请加入
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我们正在快速成长,并始终欢迎新的贡献者。
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Special thanks to all the contributors that helped bring this feature to beta, including Cheng Xing ([verult](https://github.com/verult)), Chuqiang Li ([lichuqiang](https://github.com/lichuqiang)), David Zhu ([davidz627](https://github.com/davidz627)), Deep Debroy ([ddebroy](https://github.com/ddebroy)), Jan Šafránek ([jsafrane](https://github.com/jsafrane)), Jordan Liggitt ([liggitt](https://github.com/liggitt)), Michelle Au ([msau42](https://github.com/msau42)), Pengfei Ni ([feiskyer](https://github.com/feiskyer)), Saad Ali ([saad-ali](https://github.com/saad-ali)), Tim Hockin ([thockin](https://github.com/thockin)), and Yecheng Fu ([cofyc](https://github.com/cofyc)).
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特别感谢帮助推出此功能的所有贡献者,包括 Cheng Xing ([verult](https://github.com/verult))、Chuqiang Li ([lichuqiang](https://github.com/lichuqiang))、David Zhu ([davidz627](https://github.com/davidz627))、Deep Debroy ([ddebroy](https://github.com/ddebroy))、Jan Šafránek ([jsafrane](https://github.com/jsafrane))、Jordan Liggitt ([liggitt](https://github.com/liggitt))、Michelle Au ([msau42](https://github.com/msau42))、Pengfei Ni ([feiskyer](https://github.com/feiskyer))、Saad Ali ([saad-ali](https://github.com/saad-ali))、Tim Hockin ([thockin](https://github.com/thockin)),以及 Yecheng Fu ([cofyc](https://github.com/cofyc))。
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特别感谢帮助推出此功能的所有贡献者,包括 Cheng Xing ([verult](https://github.com/verult))、
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Chuqiang Li ([lichuqiang](https://github.com/lichuqiang))、David Zhu ([davidz627](https://github.com/davidz627))、
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Deep Debroy ([ddebroy](https://github.com/ddebroy))、Jan Šafránek ([jsafrane](https://github.com/jsafrane))、
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Jordan Liggitt ([liggitt](https://github.com/liggitt))、Michelle Au ([msau42](https://github.com/msau42))、
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Pengfei Ni ([feiskyer](https://github.com/feiskyer))、Saad Ali ([saad-ali](https://github.com/saad-ali))、
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Tim Hockin ([thockin](https://github.com/thockin)),以及 Yecheng Fu ([cofyc](https://github.com/cofyc))。

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