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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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2.2.16 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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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 使用kubectl
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3.2.2 docker用户过度到kubectl命令行指南
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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 kubectl的用户认证授权
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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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3.4 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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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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4.3 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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4.3.5 使用Jenkins进行持续构建与发布
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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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4.3.8 使用Prometheus监控kubernetes集群
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4.3.9 使用Heapster获取集群和对象的metric数据
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4.3.10 手动集群升级
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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 服务编排管理
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4.5.1 Helm
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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istio
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5.1.1.2 配置请求的路由规则
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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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5.2.1 Spark standalone on Kubernetes
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5.2.2 运行支持kubernetes原生调度的Spark程序
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5.3 Serverless架构
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6. 开发指南
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6.1 开发环境搭建
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6.2 单元测试和集成测试
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6.3 client-go示例
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6.4 社区贡献
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7. 附录
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7.1 Docker最佳实践
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7.2 问题记录
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7.3 使用技巧
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7.4 kubernetes service中的故障排查
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7.5 Kubernetes相关资讯和情报链接
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本书使用 GitBook 发布
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< a href = ".." > 3.2.3 管理namespace中的资源配额< / a >
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< h1 id = "管理namespace中的资源配额" > 管 理 namespace中 的 资 源 配 额 < / h1 >
< p > 当 用 多 个 团 队 或 者 用 户 共 用 同 一 个 集 群 的 时 候 难 免 会 有 资 源 竞 争 的 情 况 发 生 ， 这 时 候 就 需 要 对 不 同 团 队 或 用 户 的 资 源 使 用 配 额 做 出 限 制 。 < / p >
< h2 id = "开启资源配额限制功能" > 开 启 资 源 配 额 限 制 功 能 < / h2 >
< p > 目 前 有 两 种 资 源 分 配 管 理 相 关 的 控 制 策 略 插 件 < code > ResourceQuota< / code > 和 < code > LimitRange< / code > 。 < / p >
< p > 要 启 用 它 们 只 要 API Server 的 启 动 配 置 的 < code > KUBE_ADMISSION_CONTROL< / code > 参 数 中 加 入 了 < code > ResourceQuota< / code > 的 设 置 ， 这 样 就 给 集 群 开 启 了 资 源 配 额 限 制 功 能 ， 加 入 < code > LimitRange< / code > 可 以 用 来 限 制 一 个 资 源 申 请 的 范 围 限 制 ， 参 考 < a href = "https://k8smeetup.github.io/docs/tasks/administer-cluster/memory-default-namespace/" target = "_blank" > 为 namesapce 配 置 默 认 的 内 存 请 求 与 限 额 < / a > 和 < a href = "https://k8smeetup.github.io/docs/tasks/administer-cluster/cpu-default-namespace/" target = "_blank" > 在 namespace 中 配 置 默 认 的 CPU请 求 与 限 额 < / a > 。 < / p >
< p > 两 种 控 制 策 略 的 作 用 范 围 都 是 对 于 某 一 namespace， < code > ResourceQuota< / code > 用 来 限 制 namespace 中 所 有 的 Pod 占 用 的 总 的 资 源 request 和 limit， 而 < code > LimitRange< / code > 是 用 来 设 置 namespace 中 Pod 的 默 认 的 资 源 request 和 limit 值 。 < / p >
< p > 资 源 配 额 分 为 三 种 类 型 ： < / p >
< ul >
< li > 计 算 资 源 配 额 < / li >
< li > 存 储 资 源 配 额 < / li >
< li > 对 象 数 量 配 额 < / li >
< / ul >
< p > 关 于 资 源 配 额 的 详 细 信 息 请 参 考 kubernetes 官 方 文 档 < a href = "https://k8smeetup.github.io/docs/concepts/policy/resource-quotas/" target = "_blank" > 资 源 配 额 < / a > 。 < / p >
< h2 id = "示例" > 示 例 < / h2 >
< p > 我 们 为 < code > spark-cluster< / code > 这 个 namespace 设 置 < code > ResouceQuota< / code > 和 < code > LimitRange< / code > 。 < / p >
< p > 以 下 yaml 文 件 可 以 在 < a href = "https://github.com/rootsongjc/kubernetes-handbook" target = "_blank" > kubernetes-handbook< / a > 的 < code > manifests/spark-with-kubernetes-native-scheduler< / code > 目 录 下 找 到 。 < / p >
< h3 id = "配置计算资源配额" > 配 置 计 算 资 源 配 额 < / h3 >
< p > 配 置 文 件 ： < code > spark-compute-resources.yaml< / code > < / p >
< pre > < code class = "lang-yaml" > < span class = "hljs-attr" > apiVersion:< / span > v1
< span class = "hljs-attr" > kind:< / span > ResourceQuota
< span class = "hljs-attr" > metadata:< / span >
< span class = "hljs-attr" > name:< / span > compute-resources
< span class = "hljs-attr" > namespace:< / span > spark-cluster
< span class = "hljs-attr" > spec:< / span >
< span class = "hljs-attr" > hard:< / span >
< span class = "hljs-attr" > pods:< / span > < span class = "hljs-string" > " 20" < / span >
requests.cpu: < span class = "hljs-string" > " 20" < / span >
requests.memory: < span class = "hljs-number" > 100< / span > Gi
limits.cpu: < span class = "hljs-string" > " 40" < / span >
limits.memory: < span class = "hljs-number" > 200< / span > Gi
< / code > < / pre >
< p > 要 想 查 看 该 配 置 只 要 执 行 ： < / p >
< pre > < code class = "lang-bash" > kubectl -n spark-cluster describe resourcequota compute-resources
< / code > < / pre >
< h3 id = "配置对象数量限制" > 配 置 对 象 数 量 限 制 < / h3 >
< p > 配 置 文 件 ： < code > spark-object-counts.yaml< / code > < / p >
< pre > < code class = "lang-Yaml" > < span class = "hljs-attr" > apiVersion:< / span > v1
< span class = "hljs-attr" > kind:< / span > ResourceQuota
< span class = "hljs-attr" > metadata:< / span >
< span class = "hljs-attr" > name:< / span > object-counts
< span class = "hljs-attr" > namespace:< / span > spark-cluster
< span class = "hljs-attr" > spec:< / span >
< span class = "hljs-attr" > hard:< / span >
< span class = "hljs-attr" > configmaps:< / span > < span class = "hljs-string" > " 10" < / span >
< span class = "hljs-attr" > persistentvolumeclaims:< / span > < span class = "hljs-string" > " 4" < / span >
< span class = "hljs-attr" > replicationcontrollers:< / span > < span class = "hljs-string" > " 20" < / span >
< span class = "hljs-attr" > secrets:< / span > < span class = "hljs-string" > " 10" < / span >
< span class = "hljs-attr" > services:< / span > < span class = "hljs-string" > " 10" < / span >
services.loadbalancers: < span class = "hljs-string" > " 2" < / span >
< / code > < / pre >
< h3 id = "配置cpu和内存limitrange" > 配 置 CPU和 内 存 LimitRange< / h3 >
< p > 配 置 文 件 ： < code > spark-limit-range.yaml< / code > < / p >
< pre > < code class = "lang-yaml" > < span class = "hljs-attr" > apiVersion:< / span > v1
< span class = "hljs-attr" > kind:< / span > LimitRange
< span class = "hljs-attr" > metadata:< / span >
< span class = "hljs-attr" > name:< / span > mem-limit-range
< span class = "hljs-attr" > spec:< / span >
< span class = "hljs-attr" > limits:< / span >
< span class = "hljs-attr" > - default:< / span >
< span class = "hljs-attr" > memory:< / span > < span class = "hljs-number" > 50< / span > Gi
< span class = "hljs-attr" > cpu:< / span > < span class = "hljs-number" > 5< / span >
< span class = "hljs-attr" > defaultRequest:< / span >
< span class = "hljs-attr" > memory:< / span > < span class = "hljs-number" > 1< / span > Gi
< span class = "hljs-attr" > cpu:< / span > < span class = "hljs-number" > 1< / span >
< span class = "hljs-attr" > type:< / span > Container
< / code > < / pre >
< ul >
< li > < code > default< / code > 即 limit 的 值 < / li >
< li > < code > defaultRequest< / code > 即 request 的 值 < / li >
< / ul >
< h2 id = "参考" > 参 考 < / h2 >
< p > < a href = "https://k8smeetup.github.io/docs/concepts/policy/resource-quotas/" target = "_blank" > 资 源 配 额 < / a > < / p >
< p > < a href = "https://k8smeetup.github.io/docs/tasks/administer-cluster/memory-default-namespace/" target = "_blank" > 为 命 名 空 间 配 置 默 认 的 内 存 请 求 与 限 额 < / a > < / p >
< p > < a href = "https://k8smeetup.github.io/docs/tasks/administer-cluster/cpu-default-namespace/" target = "_blank" > 在 命 名 空 间 中 配 置 默 认 的 CPU请 求 与 限 额 < / a > < / p >
< footer class = "page-footer" > < span class = "copyright" > Copyright © jimmysong.io 2017 all right reserved， powered by Gitbook< / span > < span class = "footer-modification" > Updated:
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