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序言
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1. Kubernetes与云原生应用概览
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2. 概念原理
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2.1 设计理念
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2.2 Objects
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2.2.1 Pod
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2.2.1.1 Pod解析
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2.2.1.2 Init容器
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2.2.1.3 Pod安全策略
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2.2.1.4 Pod的生命周期
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2.2.2 Node
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2.2.3 Namespace
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2.2.4 Service
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2.2.5 Volume和Persistent Volume
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2.2.6 Deployment
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2.2.7 Secret
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2.2.8 StatefulSet
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2.2.9 DaemonSet
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2.2.10 ServiceAccount
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2.2.11 ReplicationController和ReplicaSet
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2.2.12 Job
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2.2.13 CronJob
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2.2.14 Ingress
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2.2.15 ConfigMap
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2.2.15.1 ConfigMap的热更新
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2.2.16 Horizontal Pod Autoscaling
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2.2.17 Label
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2.2.18 垃圾收集
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2.2.19 NetworkPolicy
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2.2.20 Annotation
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3. 用户指南
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3.1 资源对象配置
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3.1.1 配置Pod的liveness和readiness探针
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3.1.2 配置Pod的Service Account
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3.1.3 Secret配置
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3.2.3 管理namespace中的资源配额
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3.2 命令使用
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3.2.1 docker用户过度到kubectl命令行指南
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3.2.2 kubectl命令概览
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3.2.3 kubectl命令技巧大全
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3.3 集群安全性管理
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3.3.1 管理集群中的TLS
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3.3.2 kubelet的认证授权
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3.3.3 TLS bootstrap
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3.3.4 创建用户认证授权的kubeconfig文件
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3.3.5 RBAC——基于角色的访问控制
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3.3.6 IP伪装代理
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3.3.7 使用kubeconfig或token进行用户身份认证
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3.3.8 kubernetes中的用户与身份认证授权
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3.4 访问 Kubernetes 集群
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3.4.1 访问集群
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3.4.2 使用 kubeconfig 文件配置跨集群认证
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3.4.3 通过端口转发访问集群中的应用程序
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3.4.4 使用 service 访问群集中的应用程序
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3.5 在kubernetes中开发部署应用
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3.5.1 适用于kubernetes的应用开发部署流程
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3.5.2 迁移传统应用到kubernetes中——以Hadoop YARN为例
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3.5.3 使用StatefulSet部署用状态应用
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4. 最佳实践
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4.1 在CentOS上部署kubernetes1.6集群
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4.1.1 创建TLS证书和秘钥
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4.1.2 创建kubeconfig文件
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4.1.3 创建高可用etcd集群
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4.1.4 安装kubectl命令行工具
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4.1.5 部署master节点
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4.1.6 部署node节点
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4.1.7 安装kubedns插件
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4.1.8 安装dashboard插件
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4.1.9 安装heapster插件
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4.1.10 安装EFK插件
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4.2 服务发现与负载均衡
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4.2.1 安装Traefik ingress
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4.2.2 分布式负载测试
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4.2.3 网络和集群性能测试
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4.2.4 边缘节点配置
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4.2.5 安装Nginx ingress
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4.3 运维管理
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4.3.1 服务滚动升级
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4.3.2 应用日志收集
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4.3.3 配置最佳实践
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4.3.4 集群及应用监控
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4.3.6 数据持久化问题
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4.3.7 管理容器的计算资源
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4.4 存储管理
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4.4.1 GlusterFS
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4.4.1.1 使用GlusterFS做持久化存储
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4.4.1.2 在OpenShift中使用GlusterFS做持久化存储
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4.4.2 CephFS
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4.4.2.1 使用Ceph做持久化存储
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4.5 集群与应用监控
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4.5.1 Heapster
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4.5.1.1 使用Heapster获取集群和对象的metric数据
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4.5.2 Prometheus
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4.5.2.1 使用Prometheus监控kubernetes集群
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4.6 服务编排管理
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4.6.1 使用Helm管理kubernetes应用
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4.6.2 构建私有Chart仓库
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4.7 持续集成与发布
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4.7.1 使用Jenkins进行持续集成与发布
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4.7.2 使用Drone进行持续集成与发布
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4.8 更新与升级
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4.8.1 手动升级kubernetes集群
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4.8.2 升级dashboard
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5. 领域应用
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5.1 微服务架构
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5.1.1 微服务中的服务发现
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5.2 Service Mesh 服务网格
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5.1.1 Istio
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5.1.1.1 安装并试用Istio service mesh
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5.1.1.2 配置请求的路由规则
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5.1.1.3 安装和拓展Istio service mesh
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5.1.1.4 集成虚拟机
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5.1.2 Linkerd
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5.1.2.1 Linkerd 使用指南
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5.2 大数据
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< li class = "chapter " data-level = "1.6.3.1" data-path = "../usecases/spark-standalone-on-kubernetes.html" >
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< a href = "../usecases/spark-standalone-on-kubernetes.html" >
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5.2.1 Spark standalone on Kubernetes
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< / a >
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< / li >
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< li class = "chapter " data-level = "1.6.3.2" data-path = "../usecases/running-spark-with-kubernetes-native-scheduler.html" >
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< a href = "../usecases/running-spark-with-kubernetes-native-scheduler.html" >
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5.2.2 运行支持kubernetes原生调度的Spark程序
< / a >
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< / li >
< / ul >
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< / li >
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< li class = "chapter " data-level = "1.6.4" data-path = "../usecases/serverless.html" >
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< a href = "../usecases/serverless.html" >
5.3 Serverless架构
< / a >
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< / li >
< li class = "chapter " data-level = "1.6.5" data-path = "../usecases/edge-computing.html" >
< a href = "../usecases/edge-computing.html" >
5.4 边缘计算
< / a >
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< / li >
< / ul >
< / li >
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< li class = "chapter " data-level = "1.7" data-path = "../develop/" >
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< a href = "../develop/" >
6. 开发指南
< / a >
< ul class = "articles" >
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< li class = "chapter " data-level = "1.7.1" data-path = "../develop/developing-environment.html" >
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< a href = "../develop/developing-environment.html" >
6.1 开发环境搭建
< / a >
< / li >
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< li class = "chapter " data-level = "1.7.2" data-path = "../develop/testing.html" >
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< a href = "../develop/testing.html" >
6.2 单元测试和集成测试
< / a >
< / li >
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< li class = "chapter " data-level = "1.7.3" data-path = "../develop/client-go-sample.html" >
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< a href = "../develop/client-go-sample.html" >
6.3 client-go示例
< / a >
< / li >
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< li class = "chapter " data-level = "1.7.4" data-path = "../develop/contribute.html" >
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< a href = "../develop/contribute.html" >
6.4 社区贡献
< / a >
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< / li >
< li class = "chapter " data-level = "1.7.5" data-path = "../develop/minikube.html" >
< a href = "../develop/minikube.html" >
6.5 Minikube
< / a >
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< / li >
< / ul >
< / li >
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< li class = "chapter " data-level = "1.8" data-path = "../appendix/" >
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< a href = "../appendix/" >
7. 附录
< / a >
< ul class = "articles" >
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< li class = "chapter " data-level = "1.8.1" data-path = "../appendix/docker-best-practice.html" >
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< a href = "../appendix/docker-best-practice.html" >
7.1 Docker最佳实践
< / a >
< / li >
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< li class = "chapter " data-level = "1.8.2" data-path = "../appendix/issues.html" >
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< a href = "../appendix/issues.html" >
7.2 问题记录
< / a >
< / li >
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< li class = "chapter " data-level = "1.8.3" data-path = "../appendix/tricks.html" >
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< a href = "../appendix/tricks.html" >
7.3 使用技巧
< / a >
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< / li >
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< li class = "chapter " data-level = "1.8.4" data-path = "../appendix/debug-kubernetes-services.html" >
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< a href = "../appendix/debug-kubernetes-services.html" >
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7.4 kubernetes中的应用故障排查
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< / a >
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< / li >
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< li class = "chapter " data-level = "1.8.5" data-path = "../appendix/material-share.html" >
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< a href = "../appendix/material-share.html" >
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7.5 Kubernetes相关资讯和情报链接
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< / a >
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< / li >
< / ul >
< / li >
< li class = "divider" > < / li >
< li >
< a href = "https://www.gitbook.com" target = "blank" class = "gitbook-link" >
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本书使用 GitBook 发布
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< / a >
< / li >
< / ul >
< / nav >
< / div >
< div class = "book-body" >
< div class = "body-inner" >
< div class = "book-header" role = "navigation" >
<!-- Title -->
< h1 >
< i class = "fa fa-circle-o-notch fa-spin" > < / i >
< a href = ".." > 2.2.16 Horizontal Pod Autoscaling< / a >
< / h1 >
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< div class = "page-wrapper" tabindex = "-1" role = "main" >
< div class = "page-inner" >
< div class = "search-plus" id = "book-search-results" >
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< section class = "normal markdown-section" >
< h1 id = "horizontal-pod-autoscaling" > Horizontal Pod Autoscaling< / h1 >
< p > 应 用 的 资 源 使 用 率 通 常 都 有 高 峰 和 低 谷 的 时 候 ， 如 何 削 峰 填 谷 ， 提 高 集 群 的 整 体 资 源 利 用 率 ， 让 service中 的 Pod个 数 自 动 调 整 呢 ？ 这 就 有 赖 于 Horizontal Pod Autoscaling了 ， 顾 名 思 义 ， 使 Pod水 平 自 动 缩 放 。 这 个 Object（ 跟 Pod、 Deployment一 样 都 是 API resource） 也 是 最 能 体 现 kubernetes之 于 传 统 运 维 价 值 的 地 方 ， 不 再 需 要 手 动 扩 容 了 ， 终 于 实 现 自 动 化 了 ， 还 可 以 自 定 义 指 标 ， 没 准 未 来 还 可 以 通 过 人 工 智 能 自 动 进 化 呢 ！ < / p >
< p > Horizontal Pod Autoscaling仅 适 用 于 Deployment和 ReplicationController（ ReplicaSet已 经 被 ReplicationController取 代 ） ， 在 V1版 本 中 仅 支 持 根 据 Pod的 CPU利 用 率 扩 所 容 ， 在 v1alpha版 本 中 ， 支 持 根 据 内 存 和 用 户 自 定 义 的 metric扩 缩 容 。 < / p >
< p > 如 果 你 不 想 看 下 面 的 文 章 可 以 直 接 看 下 面 的 示 例 图 ， 组 件 交 互 、 组 件 的 配 置 、 命 令 示 例 ， 都 画 在 图 上 了 。 < / p >
< p > Horizontal Pod Autoscaling由 API server和 controller共 同 实 现 。 < / p >
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< figure id = "fig1.3.2.16.1" > < img src = "../images/horizontal-pod-autoscaler.png" alt = "horizontal-pod-autoscaler" > < figcaption > 图 片 - horizontal-pod-autoscaler< / figcaption > < / figure >
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< h2 id = "metrics支持" > Metrics支 持 < / h2 >
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< p > 在 不 同 版 本 的 API中 ， HPA autoscale时 可 以 根 据 以 下 指 标 来 判 断 ： < / p >
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< ul >
< li > autoscaling/v1< ul >
< li > CPU< / li >
< / ul >
< / li >
< li > autoscaling/v2alpha1< ul >
< li > 内 存 < / li >
< li > 自 定 义 metrics< ul >
< li > kubernetes1.6起 支 持 自 定 义 metrics， 但 是 必 须 在 kube-controller-manager中 配 置 如 下 两 项 ： < ul >
< li > < code > --horizontal-pod-autoscaler-use-rest-clients=true< / code > < / li >
< li > < code > --api-server< / code > 指 向 < a href = "https://github.com/kubernetes/kube-aggregator" target = "_blank" > kube-aggregator< / a > ， 也 可 以 使 用 heapster来 实 现 ， 通 过 在 启 动 heapster的 时 候 指 定 < code > --api-server=true< / code > 。 查 看 < a href = "https://github.com/kubernetes/metrics" target = "_blank" > kubernetes metrics< / a > < / li >
< / ul >
< / li >
< / ul >
< / li >
< li > 多 种 metrics组 合 < ul >
< li > HPA会 根 据 每 个 metric的 值 计 算 出 scale的 值 ， 并 将 最 大 的 那 个 指 作 为 扩 容 的 最 终 结 果 。 < / li >
< / ul >
< / li >
< / ul >
< / li >
< / ul >
< h2 id = "使用kubectl管理" > 使 用 kubectl管 理 < / h2 >
< p > Horizontal Pod Autoscaling作 为 API resource也 可 以 像 Pod、 Deployment一 样 使 用 kubeclt命 令 管 理 ， 使 用 方 法 跟 它 们 一 样 ， 资 源 名 称 为 < code > hpa< / code > 。 < / p >
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< pre > < code class = "lang-bash" > kubectl create hpa
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kubectl get hpa
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kubectl describe hpa
kubectl delete hpa
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< / code > < / pre >
< p > 有 一 点 不 同 的 是 ， 可 以 直 接 使 用 < code > kubectl autoscale< / code > 直 接 通 过 命 令 行 的 方 式 创 建 Horizontal Pod Autoscaler。 < / p >
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< p > 用 法 如 下 ： < / p >
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< pre > < code class = "lang-bash" > kubectl autoscale (< span class = "hljs-_" > -f< / span > FILENAME | TYPE NAME | TYPE/NAME) [--min=MINPODS] --max=MAXPODS
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[--cpu-percent=CPU] [flags] [options]
< / code > < / pre >
< p > 举 个 例 子 ： < / p >
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< pre > < code class = "lang-bash" > kubectl autoscale deployment foo --min=2 --max=5 --cpu-percent=80
< / code > < / pre >
< p > 为 Deployment foo创 建 一 个 autoscaler， 当 Pod的 CPU利 用 率 达 到 80%的 时 候 ， RC的 replica数 在 2到 5之 间 。 该 命 令 的 详 细 使 用 文 档 见 < a href = "https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale" target = "_blank" > https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale< / a > 。 < / p >
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< p > < strong > 注 意 < / strong > ： 如 果 为 ReplicationController创 建 HPA的 话 ， 无 法 使 用 rolling update， 但 是 对 于 Deployment来 说 是 可 以 的 ， 因 为 Deployment在 执 行 rolling update的 时 候 会 自 动 创 建 新 的 ReplicationController。 < / p >
< h2 id = "什么是-horizontal-pod-autoscaling？" > 什 么 是 Horizontal Pod Autoscaling？ < / h2 >
< p > 利 用 Horizontal Pod Autoscaling， kubernetes 能 够 根 据 监 测 到 的 CPU 利 用 率 （ 或 者 在 alpha 版 本 中 支 持 的 应 用 提 供 的 metric） 自 动 的 扩 容 replication controller， deployment 和 replica set。 < / p >
< p > Horizontal Pod Autoscaler 作 为 kubernetes API resource 和 controller 的 实 现 。 Resource 确 定 controller 的 行 为 。 Controller 会 根 据 监 测 到 用 户 指 定 的 目 标 的 CPU 利 用 率 周 期 性 得 调 整 replication controller 或 deployment 的 replica 数 量 。 < / p >
< h2 id = "horizontal-pod-autoscaler-如何工作？" > Horizontal Pod Autoscaler 如 何 工 作 ？ < / h2 >
< p > Horizontal Pod Autoscaler 由 一 个 控 制 循 环 实 现 ， 循 环 周 期 由 controller manager 中 的 < code > --horizontal-pod-autoscaler-sync-period< / code > 标 志 指 定 （ 默 认 是 30 秒 ） 。 < / p >
< p > 在 每 个 周 期 内 ， controller manager 会 查 询 HorizontalPodAutoscaler 中 定 义 的 metric 的 资 源 利 用 率 。 Controller manager 从 resource metric API（ 每 个 pod 的 resource metric） 或 者 自 定 义 metric API（ 所 有 的 metric） 中 获 取 metric。 < / p >
< ul >
< li > 每 个 Pod 的 resource metric（ 例 如 CPU） ， controller 通 过 resource metric API 获 取 HorizontalPodAutoscaler 中 定 义 的 每 个 Pod 中 的 metric。 然 后 ， 如 果 设 置 了 目 标 利 用 率 ， controller 计 算 利 用 的 值 与 每 个 Pod 的 容 器 里 的 resource request 值 的 百 分 比 。 如 果 设 置 了 目 标 原 始 值 ， 将 直 接 使 用 该 原 始 metric 值 。 然 后 controller 计 算 所 有 目 标 Pod 的 利 用 率 或 原 始 值 （ 取 决 于 所 指 定 的 目 标 类 型 ） 的 平 均 值 ， 产 生 一 个 用 于 缩 放 所 需 replica 数 量 的 比 率 。 请 注 意 ， 如 果 某 些 Pod 的 容 器 没 有 设 置 相 关 的 resource request ， 则 不 会 定 义 Pod 的 CPU 利 用 率 ， 并 且 Aucoscaler 也 不 会 对 该 metric 采 取 任 何 操 作 。 有 关 自 动 缩 放 算 法 如 何 工 作 的 更 多 细 节 ， 请 参 阅 < a href = "https://git.k8s.io/community/contributors/design-proposals/horizontal-pod-autoscaler.md#autoscaling-algorithm" target = "_blank" > 自 动 缩 放 算 法 设 计 文 档 < / a > 。 < / li >
< li > 对 于 每 个 Pod 自 定 义 的 metric， controller 功 能 类 似 于 每 个 Pod 的 resource metric， 只 是 它 使 用 原 始 值 而 不 是 利 用 率 值 。 < / li >
< li > 对 于 object metric， 获 取 单 个 度 量 （ 描 述 有 问 题 的 对 象 ） ， 并 与 目 标 值 进 行 比 较 ， 以 产 生 如 上 所 述 的 比 率 。 < / li >
< / ul >
< p > HorizontalPodAutoscaler 控 制 器 可 以 以 两 种 不 同 的 方 式 获 取 metric ： 直 接 的 Heapster 访 问 和 REST 客 户 端 访 问 。 < / p >
< p > 当 使 用 直 接 的 Heapster 访 问 时 ， HorizontalPodAutoscaler 直 接 通 过 API 服 务 器 的 服 务 代 理 子 资 源 查 询 Heapster。 需 要 在 集 群 上 部 署 Heapster 并 在 kube-system namespace 中 运 行 。 < / p >
< p > 有 关 REST 客 户 端 访 问 的 详 细 信 息 ， 请 参 阅 < a href = "https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale.md#prerequisites" target = "_blank" > 支 持 自 定 义 度 量 < / a > 。 < / p >
< p > Autoscaler 访 问 相 应 的 replication controller， deployment 或 replica set 来 缩 放 子 资 源 。 < / p >
< p > Scale 是 一 个 允 许 您 动 态 设 置 副 本 数 并 检 查 其 当 前 状 态 的 接 口 。 < / p >
< p > 有 关 缩 放 子 资 源 的 更 多 细 节 可 以 在 < a href = "https://git.k8s.io/community/contributors/design-proposals/horizontal-pod-autoscaler.md#scale-subresource" target = "_blank" > 这 里 < / a > 找 到 。 < / p >
< h2 id = "api-object" > API Object< / h2 >
< p > Horizontal Pod Autoscaler 是 kubernetes 的 < code > autoscaling< / code > API 组 中 的 API 资 源 。 当 前 的 稳 定 版 本 中 ， 只 支 持 CPU 自 动 扩 缩 容 ， 可 以 在 < code > autoscaling/v1< / code > API 版 本 中 找 到 。 < / p >
< p > 在 alpha 版 本 中 支 持 根 据 内 存 和 自 定 义 metric 扩 缩 容 ， 可 以 在 < code > autoscaling/v2alpha1< / code > 中 找 到 。 < code > autoscaling/v2alpha1< / code > 中 引 入 的 新 字 段 在 < code > autoscaling/v1< / code > 中 是 做 为 annotation 而 保 存 的 。 < / p >
< p > 关 于 该 API 对 象 的 更 多 信 息 ， 请 参 阅 < a href = "https://git.k8s.io/community/contributors/design-proposals/horizontal-pod-autoscaler.md#horizontalpodautoscaler-object" target = "_blank" > HorizontalPodAutoscaler Object< / a > 。 < / p >
< h2 id = "在-kubectl-中支持-horizontal-pod-autoscaling" > 在 kubectl 中 支 持 Horizontal Pod Autoscaling< / h2 >
< p > Horizontal Pod Autoscaler 和 其 他 的 所 有 API 资 源 一 样 ， 通 过 < code > kubectl< / code > 以 标 准 的 方 式 支 持 。 < / p >
< p > 我 们 可 以 使 用 < code > kubectl create< / code > 命 令 创 建 一 个 新 的 autoscaler。 < / p >
< p > 我 们 可 以 使 用 < code > kubectl get hpa< / code > 列 出 所 有 的 autoscaler， 使 用 < code > kubectl describe hpa< / code > 获 取 其 详 细 信 息 。 < / p >
< p > 最 后 我 们 可 以 使 用 < code > kubectl delete hpa< / code > 删 除 autoscaler。 < / p >
< p > 另 外 ， 可 以 使 用 < code > kubectl autoscale< / code > 命 令 ， 很 轻 易 的 就 可 以 创 建 一 个 Horizontal Pod Autoscaler。 < / p >
< p > 例 如 ， 执 行 < code > kubectl autoscale rc foo — min=2 — max=5 — cpu-percent=80< / code > 命 令 将 为 replication controller < em > foo< / em > 创 建 一 个 autoscaler， 目 标 的 CPU 利 用 率 是 < code > 80%< / code > ， replica 的 数 量 介 于 2 和 5 之 间 。 < / p >
< p > 关 于 < code > kubectl autoscale< / code > 的 更 多 信 息 请 参 阅 < a href = "https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale" target = "_blank" > 这 里 < / a > 。 < / p >
< h2 id = "滚动更新期间的自动扩缩容" > 滚 动 更 新 期 间 的 自 动 扩 缩 容 < / h2 >
< p > 目 前 在 Kubernetes中 ， 可 以 通 过 直 接 管 理 replication controller 或 使 用 deployment 对 象 来 执 行 < a href = "https://kubernetes.io/docs/tasks/run-application/rolling-update-replication-controller" target = "_blank" > 滚 动 更 新 < / a > ， 该 deployment 对 象 为 您 管 理 基 础 replication controller。 < / p >
< p > Horizontal Pod Autoscaler 仅 支 持 后 一 种 方 法 ： Horizontal Pod Autoscaler 被 绑 定 到 deployment 对 象 ， 它 设 置 deployment 对 象 的 大 小 ， deployment 负 责 设 置 底 层 replication controller 的 大 小 。 < / p >
< p > Horizontal Pod Autoscaler 不 能 使 用 直 接 操 作 replication controller 进 行 滚 动 更 新 ， 即 不 能 将 Horizontal Pod Autoscaler 绑 定 到 replication controller， 并 进 行 滚 动 更 新 （ 例 如 使 用 < code > kubectl rolling-update< / code > ） 。 < / p >
< p > 这 不 行 的 原 因 是 ， 当 滚 动 更 新 创 建 一 个 新 的 replication controller 时 ， Horizontal Pod Autoscaler 将 不 会 绑 定 到 新 的 replication controller 上 。 < / p >
< h2 id = "支持多个-metric" > 支 持 多 个 metric< / h2 >
< p > Kubernetes 1.6 中 增 加 了 支 持 基 于 多 个 metric 的 扩 缩 容 。 您 可 以 使 用 < code > autoscaling/v2alpha1< / code > API 版 本 来 为 Horizontal Pod Autoscaler 指 定 多 个 metric。 然 后 Horizontal Pod Autoscaler controller 将 权 衡 每 一 个 metric， 并 根 据 该 metric 提 议 一 个 新 的 scale。 在 所 有 提 议 里 最 大 的 那 个 scale 将 作 为 最 终 的 scale。 < / p >
< h2 id = "支持自定义-metric" > 支 持 自 定 义 metric< / h2 >
< p > < strong > 注 意 ： < / strong > Kubernetes 1.2 根 据 特 定 于 应 用 程 序 的 metric ， 通 过 使 用 特 殊 注 释 的 方 式 ， 增 加 了 对 缩 放 的 alpha 支 持 。 < / p >
< p > 在 Kubernetes 1.6中 删 除 了 对 这 些 注 释 的 支 持 ， 有 利 于 < code > autoscaling/v2alpha1< / code > API。 虽 然 旧 的 收 集 自 定 义 metric 的 旧 方 法 仍 然 可 用 ， 但 是 这 些 metric 将 不 可 供 Horizontal Pod Autoscaler 使 用 ， 并 且 用 于 指 定 要 缩 放 的 自 定 义 metric 的 以 前 的 注 释 也 不 在 受 Horizontal Pod Autoscaler 认 可 。 < / p >
< p > Kubernetes 1.6增 加 了 在 Horizontal Pod Autoscale r中 使 用 自 定 义 metric 的 支 持 。 < / p >
< p > 您 可 以 为 < code > autoscaling/v2alpha1< / code > API 中 使 用 的 Horizontal Pod Autoscaler 添 加 自 定 义 metric 。 < / p >
< p > Kubernetes 然 后 查 询 新 的 自 定 义 metric API 来 获 取 相 应 自 定 义 metric 的 值 。 < / p >
< h2 id = "前提条件" > 前 提 条 件 < / h2 >
< p > 为 了 在 Horizontal Pod Autoscaler 中 使 用 自 定 义 metric， 您 必 须 在 您 集 群 的 controller manager 中 将 < code > --horizontal-pod-autoscaler-use-rest-clients< / code > 标 志 设 置 为 true。 然 后 ， 您 必 须 通 过 将 controller manager 的 目 标 API server 设 置 为 API server aggregator（ 使 用 < code > --apiserver< / code > 标 志 ） ， 配 置 您 的 controller manager 通 过 API server aggregator 与 API server 通 信 。 Resource metric API和 自 定 义 metric API 也 必 须 向 API server aggregator 注 册 ， 并 且 必 须 由 集 群 上 运 行 的 API server 提 供 。 < / p >
< p > 您 可 以 使 用 Heapster 实 现 resource metric API， 方 法 是 将 < code > --api-server< / code > 标 志 设 置 为 true 并 运 行 Heapster。 单 独 的 组 件 必 须 提 供 自 定 义 metric API（ 有 关 自 定 义 metric API的 更 多 信 息 ， 可 从 < a href = "https://github.com/kubernetes/metrics" target = "_blank" > k8s.io/metrics repository< / a > 获 得 ） 。 < / p >
< h2 id = "进一步阅读" > 进 一 步 阅 读 < / h2 >
< ul >
< li > 设 计 文 档 ： < a href = "https://git.k8s.io/community/contributors/design-proposals/horizontal-pod-autoscaler.md" target = "_blank" > Horizontal Pod Autoscaling< / a > < / li >
< li > kubectl autoscale 命 令 ： < a href = "https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale" target = "_blank" > kubectl autoscale< / a > < / li >
< li > 使 用 例 子 ： < a href = "https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough" target = "_blank" > Horizontal Pod Autoscaler< / a > < / li >
< / ul >
< h2 id = "参考" > 参 考 < / h2 >
< p > HPA设 计 文 档 ： < a href = "https://github.com/kubernetes/community/blob/master/contributors/design-proposals/horizontal-pod-autoscaler.md" target = "_blank" > https://github.com/kubernetes/community/blob/master/contributors/design-proposals/horizontal-pod-autoscaler.md< / a > < / p >
< p > HPA说 明 ： < a href = "https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/" target = "_blank" > https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/< / a > < / p >
< p > HPA详 解 ： < a href = "https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/" target = "_blank" > https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/< / a > < / p >
< p > kubectl autoscale命 令 详 细 使 用 说 明 ： < a href = "https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale" target = "_blank" > https://kubernetes.io/docs/user-guide/kubectl/v1.6/#autoscale< / a > < / p >
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< p > 自 定 义 metrics开 发 ： < a href = "https://github.com/kubernetes/metrics" target = "_blank" > https://github.com/kubernetes/metrics< / a > < / p >
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