Create 2015-04-00-Weekly-Kubernetes-Community-Hangout.md
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title: " 每周 Kubernetes 社区聚会笔记 - 2015年4月3日 "
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date: 2015-04-04
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slug: weekly-kubernetes-community-hangout
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url: /blog/2015/04/Weekly-Kubernetes-Community-Hangout
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---
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<!--
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---
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title: " Weekly Kubernetes Community Hangout Notes - April 3 2015 "
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date: 2015-04-04
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slug: weekly-kubernetes-community-hangout
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url: /blog/2015/04/Weekly-Kubernetes-Community-Hangout
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---
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-->
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<!--
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# Kubernetes: Weekly Kubernetes Community Hangout Notes
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-->
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# Kubernetes: 每周 Kubernetes 社区聚会笔记
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<!--
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Every week the Kubernetes contributing community meet virtually over Google Hangouts. We want anyone who's interested to know what's discussed in this forum.
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-->
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每周，Kubernetes 贡献社区几乎都会通过 Google Hangouts 开会。
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我们希望任何有兴趣的人都知道本论坛讨论的内容。
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<!--
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Agenda:
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议程：
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<!--
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* Quinton - Cluster federation
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* Satnam - Performance benchmarking update
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* Quinton - 集群联邦
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* Satnam - 性能基准测试更新
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*Notes from meeting:*
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*会议记录：*
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<!--
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1. Quinton - Cluster federation
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* Ideas floating around after meetup in SF
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* * Please read and comment
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* Not 1.0, but put a doc together to show roadmap
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* Can be built outside of Kubernetes
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* API to control things across multiple clusters, include some logic
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-->
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1. Quinton - 集群联邦
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* 在旧金山见面会后，想法浮出水面
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* * 请阅读并评论
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* 不是 1.0，而是将文档放在一起以显示路线图
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* 可以在 Kubernetes 之外构建
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* 用于控制多个集群中事物的 API ，包括一些逻辑
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<!--
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1. Auth(n)(z)
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2. Scheduling Policies
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3. …
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-->
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1. Auth(n)(z)
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2. 调度策略
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3. ……
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<!--
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* Different reasons for cluster federation
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1. Zone (un) availability : Resilient to zone failures
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2. Hybrid cloud: some in cloud, some on prem. for various reasons
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3. Avoid cloud provider lock-in. For various reasons
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4. "Cloudbursting" - automatic overflow into the cloud
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-->
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* 集群联邦的不同原因
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1. 区域(非)可用性:对区域故障的弹性
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2. 混合云：有些在云中，有些在本地。 由于各种原因
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3. 避免锁定云提供商。 由于各种原因
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4. "Cloudbursting" - 自动溢出到云中
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<!--
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* Hard problems
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1. Location affinity. How close do pods need to be?
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1. Workload coupling
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2. Absolute location (e.g. eu data needs to be in eu)
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2. Cross cluster service discovery
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1. How does service/DNS work across clusters
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3. Cross cluster workload migration
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1. How do you move an application piece by piece across clusters?
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4. Cross cluster scheduling
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1. How do know enough about clusters to know where to schedule
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2. Possibly use a cost function to achieve affinities with minimal complexity
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3. Can also use cost to determine where to schedule (under used clusters are cheaper than over-used clusters)
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-->
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* 困难的问题
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1. 位置的吸引力。Pod 需要多近？
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1. 工作负载的耦合
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2. 绝对位置(例如欧盟数据需要在欧盟内)
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2. 跨集群服务发现
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1. 服务/DNS 如何跨集群工作
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3. 跨集群工作负载迁移
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1. 如何在跨集群中逐块移动应用程序?
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4. 跨集群调度
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1. 如何充分了解集群以知道在哪里进行调度
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2. 可能使用成本函数以最小的复杂性获得关联
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3. 还可以使用成本来确定计划的时间（使用不足的集群比过度使用的集群便宜）
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<!--
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* Implicit requirements
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1. Cross cluster integration shouldn't create cross-cluster failure modes
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1. Independently usable in a disaster situation where Ubernetes dies.
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2. Unified visibility
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1. Want to have unified monitoring, alerting, logging, introspection, ux, etc.
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3. Unified quota and identity management
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-->
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* 隐含要求
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1. 跨集群集成不应创建跨集群故障模式
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1. 在 Ubernetes 死亡的灾难情况下可以独立使用。
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2. 统一可见性
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1. 希望有统一的监控，报警，日志，内省，用户体验等。
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3. 统一的配额和身份管理
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1. 希望将用户数据库和 auth（n）/（z）放在一个位置
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<!--
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* Important to note, most causes of software failure are not the infrastructure
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1. Botched software upgrades
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2. Botched config upgrades
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3. Botched key distribution
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4. Overload
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5. Failed external dependencies
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-->
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* 需要注意的是，导致软件故障的大多数原因不是基础架构
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1. 拙劣的软件升级
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2. 拙劣的配置升级
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3. 拙劣的密钥分发
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4. 过载
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5. 失败的外部依赖项
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<!--
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* Discussion:
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1. Where do you draw the "ubernetes" line
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1. Likely at the availability zone, but could be at the rack, or the region
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2. Important to not pigeon hole and prevent other users
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-->
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* 讨论：
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1. 在哪里画 ”ubernetes“ 线
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1. 可能在可用区，但也可能在机架，或地区
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2. 重要的是不要鸽子洞并防止其他用户
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<!--
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2. Satnam - Soak Test
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* Want to measure things that run for a long time to make sure that the cluster is stable over time. Performance doesn't degrade, no memory leaks, etc.
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* github.com/GoogleCloudPlatform/kubernetes/test/soak/…
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* Single binary, puts lots of pods on each node, and queries each pod to make sure that it is running.
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* Pods are being created much, much more quickly (even in the past week) to make things go more quickly.
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* Once the pods are up running, we hit the pods via the proxy. Decision to hit the proxy was deliberate so that we test the kubernetes apiserver.
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* Code is already checked in.
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* Pin pods to each node, exercise every pod, make sure that you get a response for each node.
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* Single binary, run forever.
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* Brian - v1beta3 is enabled by default, v1beta1 and v1beta2 deprecated, turned off in June. Should still work with upgrading existing clusters, etc.
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-->
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2. Satnam - 浸泡测试
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* 想要测量长时间运行的事务，以确保集群在一段时间内是稳定的。性能不会降低，不会发生内存泄漏等。
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* github.com/GoogleCloudPlatform/kubernetes/test/soak/…
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* 单个二进制文件，在每个节点上放置许多 Pod，并查询每个 Pod 以确保其正在运行。
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* Pod 的创建速度越来越快（即使在过去一周内），也可以使事情进展得更快。
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* Pod 运行起来后，我们通过代理点击 Pod。决定使用代理是有意的，因此我们测试了 kubernetes apiserver。
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* 代码已经签入。
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* 将 Pod 固定在每个节点上，练习每个 Pod，确保你得到每个节点的响应。
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* 单个二进制文件，永远运行。
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* Brian - v1beta3 默认启用， v1beta1 和 v1beta2 不支持，在6月关闭。仍应与升级现有集群等一起使用。
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