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1. 前言
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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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2.2.2 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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3.2 命令使用
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3.2.1 使用kubectl
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3.3 集群管理
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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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3.4 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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4.4 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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5. 领域应用
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5.1 微服务架构
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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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< li class = "chapter " data-level = "1.5.1.3" data-path = "../usecases/service-discovery-in-microservices.html" >
< a href = "../usecases/service-discovery-in-microservices.html" >
5.1.3 微服务中的服务发现
< / a >
< / li >
< / ul >
< / li >
< li class = "chapter " data-level = "1.5.2" data-path = "../usecases/big-data.html" >
< a href = "../usecases/big-data.html" >
5.2 大数据
< / a >
< ul class = "articles" >
2017-08-30 14:20:52 +08:00
< li class = "chapter " data-level = "1.5.2.1" data-path = "../usecases/spark-standalone-on-kubernetes.html" >
2017-08-21 18:44:34 +08:00
2017-08-30 14:20:52 +08:00
< a href = "../usecases/spark-standalone-on-kubernetes.html" >
2017-08-21 18:44:34 +08:00
2017-08-30 14:20:52 +08:00
5.2.1 Spark standalone on Kubernetes
2017-08-21 18:44:34 +08:00
< / a >
2017-08-31 14:23:44 +08:00
< / li >
< li class = "chapter " data-level = "1.5.2.2" data-path = "../usecases/support-spark-natively-in-kubernetes.html" >
< a href = "../usecases/support-spark-natively-in-kubernetes.html" >
5.2.2 运行支持kubernetes原生调度的Spark程序
< / a >
2017-08-21 18:44:34 +08:00
< / li >
< / ul >
2017-08-30 16:52:33 +08:00
< / li >
< li class = "chapter " data-level = "1.5.3" data-path = "../usecases/serverless.html" >
< a href = "../usecases/serverless.html" >
5.3 Serverless架构
< / a >
2017-08-21 18:44:34 +08:00
< / li >
< / ul >
< / li >
< li class = "chapter " data-level = "1.6" data-path = "../develop/" >
< a href = "../develop/" >
6. 开发指南
< / a >
< ul class = "articles" >
< li class = "chapter " data-level = "1.6.1" data-path = "../develop/developing-environment.html" >
< a href = "../develop/developing-environment.html" >
6.1 开发环境搭建
< / a >
< / li >
< li class = "chapter " data-level = "1.6.2" data-path = "../develop/testing.html" >
< a href = "../develop/testing.html" >
6.2 单元测试和集成测试
< / a >
< / li >
< li class = "chapter " data-level = "1.6.3" data-path = "../develop/client-go-sample.html" >
< a href = "../develop/client-go-sample.html" >
6.3 client-go示例
< / a >
< / li >
< li class = "chapter " data-level = "1.6.4" data-path = "../develop/contribute.html" >
< a href = "../develop/contribute.html" >
6.4 社区贡献
< / a >
< / li >
< / ul >
< / li >
< li class = "chapter " data-level = "1.7" data-path = "../appendix/" >
< a href = "../appendix/" >
7. 附录
< / a >
< ul class = "articles" >
< li class = "chapter " data-level = "1.7.1" data-path = "../appendix/docker-best-practice.html" >
< a href = "../appendix/docker-best-practice.html" >
7.1 Docker最佳实践
< / a >
< / li >
< li class = "chapter " data-level = "1.7.2" data-path = "../appendix/issues.html" >
< a href = "../appendix/issues.html" >
7.2 问题记录
< / a >
< / li >
< li class = "chapter " data-level = "1.7.3" data-path = "../appendix/tricks.html" >
< a href = "../appendix/tricks.html" >
7.3 使用技巧
< / a >
< / li >
< / ul >
< / li >
< li class = "divider" > < / li >
< li >
< a href = "https://www.gitbook.com" target = "blank" class = "gitbook-link" >
本書使用 GitBook 釋出
< / 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 = ".." > 3.5.2 迁移传统应用到kubernetes中——以Hadoop YARN为例< / a >
< / h1 >
< / div >
< div class = "page-wrapper" tabindex = "-1" role = "main" >
< div class = "page-inner" >
< div class = "search-plus" id = "book-search-results" >
< div class = "search-noresults" >
< section class = "normal markdown-section" >
< h1 id = "迁移传统应用到kubernetes步骤详解——以hadoop-yarn为例" > 迁 移 传 统 应 用 到 Kubernetes步 骤 详 解 — — 以 Hadoop YARN为 例 < / h1 >
< p > 本 文 档 不 是 说 明 如 何 在 kubernetes 中 开 发 和 部 署 应 用 程 序 ， 如 果 您 想 要 直 接 开 发 应 用 程 序 在 kubernetes 中 运 行 可 以 参 考 < a href = "deploy-applications-in-kubernetes.html" > 适 用 于 kubernetes的 应 用 开 发 部 署 流 程 < / a > 。 < / p >
< p > 本 文 旨 在 说 明 如 何 将 已 有 的 应 用 程 序 尤 其 是 传 统 的 分 布 式 应 用 程 序 迁 移 到 kubernetes 中 。 如 果 该 类 应 用 程 序 符 合 云 原 生 应 用 规 范 （ 如 12因 素 法 则 ） 的 话 ， 那 么 迁 移 会 比 较 顺 利 ， 否 则 会 遇 到 一 些 麻 烦 甚 至 是 阻 碍 。 具 体 请 参 考 < a href = "https://github.com/rootsongjc/migrating-to-cloud-native-application-architectures" target = "_blank" > 迁 移 至 云 原 生 应 用 架 构 < / a > 。 < / p >
< p > 接 下 来 我 们 将 以 Spark on YARN with kubernetes 为 例 来 说 明 ， 该 例 子 足 够 复 杂 也 很 有 典 型 性 ， 了 解 了 这 个 例 子 可 以 帮 助 大 家 将 自 己 的 应 用 迁 移 到 kubernetes 集 群 上 去 ， 代 码 和 配 置 文 件 可 以 在 < a href = "https://github.com/rootsongjc/kube-yarn" target = "_blank" > 这 里 < / a > 找 到 （ 本 文 中 加 入 Spark 的 配 置 ， 代 码 中 并 没 有 包 含 ， 读 者 可 以 自 己 配 置 ） 。 < / p >
< p > 下 图 即 整 个 架 构 的 示 意 图 ， 代 码 和 详 细 配 置 文 件 请 参 考 < a href = "https://github.com/rootsongjc/kube-yarn" target = "_blank" > kube-yarn< / a > （ 不 包 含 ingress、 spark 配 置 ） ， 所 有 的 进 程 管 理 和 容 器 扩 容 直 接 使 用 Makefile。 < / p >
< figure id = "fig1.3.5.2.1" > < img src = "../images/spark-on-yarn-with-kubernetes.png" alt = "spark on yarn with kubernetes" > < figcaption > Figure: spark on yarn with kubernetes< / figcaption > < / figure >
< p > < strong > 注 意 ： 该 例 子 仅 用 来 说 明 具 体 的 步 骤 划 分 和 复 杂 性 ， 在 生 产 环 境 应 用 还 有 待 验 证 ， 请 谨 慎 使 用 。 < / strong > < / p >
< h2 id = "术语" > 术 语 < / h2 >
< p > 对 于 为 曾 接 触 过 kubernetes 或 对 云 平 台 的 技 术 细 节 不 太 了 解 的 人 来 说 ， 如 何 将 应 用 迁 移 到 kubernetes 中 可 能 是 个 头 疼 的 问 题 ， 在 行 动 之 前 有 必 要 先 了 解 整 个 过 程 中 需 要 用 到 哪 些 概 念 和 术 语 ， 有 助 于 大 家 在 行 动 中 达 成 共 识 。 < / p >
< p > 过 程 中 可 能 用 到 的 概 念 和 术 语 初 步 整 理 如 下 ： < / p >
< figure id = "fig1.3.5.2.2" > < img src = "../images/terms-in-kubernetes-app-deployment.png" alt = "Terms" > < figcaption > Figure: Terms< / figcaption > < / figure >
< p > 为 了 讲 解 整 改 过 程 和 具 体 细 节 ， 我 们 所 有 操 作 都 是 通 过 命 令 手 动 完 成 ， 不 使 用 自 动 化 工 具 。 当 您 充 分 了 解 到 其 中 的 细 节 后 可 以 通 过 自 动 化 工 具 来 优 化 该 过 程 ， 以 使 其 更 加 自 动 和 高 效 ， 同 时 减 少 因 为 人 为 操 作 失 误 导 致 的 迁 移 失 败 。 < / p >
< h2 id = "迁移应用" > 迁 移 应 用 < / h2 >
< figure id = "fig1.3.5.2.3" > < img src = "../images/migrating-hadoop-yarn-to-kubernetes.png" alt = "分解步骤解析" > < figcaption > Figure: 分 解 步 骤 解 析 < / figcaption > < / figure >
< p > 整 个 迁 移 过 程 分 为 如 下 几 个 步 骤 ： < / p >
< ol >
< li > < p > < strong > 将 原 有 应 用 拆 解 为 服 务 < / strong > < / p >
< p > 我 们 不 是 一 上 来 就 开 始 做 镜 像 ， 写 配 置 ， 而 是 应 该 先 梳 理 下 要 迁 移 的 应 用 中 有 哪 些 可 以 作 为 服 务 运 行 ， 哪 些 是 变 的 ， 哪 些 是 不 变 的 部 分 。 < / p >
< p > 服 务 划 分 的 原 则 是 最 小 可 变 原 则 ， 这 个 同 样 适 用 于 镜 像 制 作 ， 将 服 务 中 不 变 的 部 分 编 译 到 同 一 个 镜 像 中 。 < / p >
< p > 对 于 像 Spark on YARN 这 样 复 杂 的 应 用 ， 可 以 将 其 划 分 为 三 大 类 服 务 ： < / p >
< ul >
< li > ResourceManager< / li >
< li > NodeManager< / li >
< li > Spark client< / li >
< / ul >
< / li >
< li > < p > < strong > 制 作 镜 像 < / strong > < / p >
< p > 根 据 拆 解 出 来 的 服 务 ， 我 们 需 要 制 作 两 个 镜 像 ： < / p >
< ul >
< li > Hadoop< / li >
< li > Spark (From hadoop docker image)< / li >
< / ul >
< p > 因 为 我 们 运 行 的 是 Spark on YARN， 因 此 Spark 依 赖 与 Hadoop 镜 像 ， 我 们 在 Spark 的 基 础 上 包 装 了 一 个 web service 作 为 服 务 启 动 。 < / p >
< p > 镜 像 制 作 过 程 中 不 需 要 在 Dockerfile 中 指 定 Entrypoint 和 CMD， 这 些 都 是 在 kubernetes 的 YAML 文 件 中 指 定 的 。 < / p >
< p > Hadoop YARN 的 Dockerfile 参 考 如 下 配 置 。 < / p >
< pre > < code class = "lang-dockerfile" > < span class = "hljs-keyword" > FROM< / span > my-docker-repo/jdk:< span class = "hljs-number" > 7< / span > u8< span class = "hljs-number" > 0
< / span >
< span class = "hljs-comment" > # Add native libs< / span >
ARG HADOOP_VERSION=< span class = "hljs-number" > 2.6< / span > .< span class = "hljs-number" > 0< / span > -cdh5.< span class = "hljs-number" > 5.2< / span >
< span class = "hljs-comment" > ## Prefer to download from server not use local storage< / span >
ADD hadoop-${HADOOP_VERSION}.tar.gz /usr/local
< span class = "hljs-keyword" > ADD< / span > < span class = "bash" > ./lib/* /usr/< span class = "hljs-built_in" > local< / span > /hadoop-< span class = "hljs-variable" > ${HADOOP_VERSION}< / span > /lib/native/
< / span > < span class = "hljs-keyword" > ADD< / span > < span class = "bash" > ./jars/* /usr/< span class = "hljs-built_in" > local< / span > /hadoop-< span class = "hljs-variable" > ${HADOOP_VERSION}< / span > /share/hadoop/yarn/
< / span > < span class = "hljs-keyword" > ENV< / span > HADOOP_PREFIX=/usr/local/hadoop \
HADOOP_COMMON_HOME=/usr/local/hadoop \
HADOOP_HDFS_HOME=/usr/local/hadoop \
HADOOP_MAPRED_HOME=/usr/local/hadoop \
HADOOP_YARN_HOME=/usr/local/hadoop \
HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop \
YARN_CONF_DIR=/usr/local/hadoop/etc/hadoop \
PATH=${PATH}:/usr/local/hadoop/bin
< span class = "hljs-keyword" > RUN< / span > < span class = "bash" > \
< span class = "hljs-built_in" > cd< / span > /usr/< span class = "hljs-built_in" > local< / span > & & ln < span class = "hljs-_" > -s< / span > ./hadoop-< span class = "hljs-variable" > ${HADOOP_VERSION}< / span > hadoop & & \
rm < span class = "hljs-_" > -f< / span > < span class = "hljs-variable" > ${HADOOP_PREFIX}< / span > /logs/*
< / span >
< span class = "hljs-keyword" > WORKDIR< / span > < span class = "bash" > < span class = "hljs-variable" > $HADOOP_PREFIX< / span >
< / span >
< span class = "hljs-comment" > # Hdfs ports< / span >
< span class = "hljs-keyword" > EXPOSE< / span > < span class = "hljs-number" > 50010< / span > < span class = "hljs-number" > 50020< / span > < span class = "hljs-number" > 50070< / span > < span class = "hljs-number" > 50075< / span > < span class = "hljs-number" > 50090< / span > < span class = "hljs-number" > 8020< / span > < span class = "hljs-number" > 9000< / span >
< span class = "hljs-comment" > # Mapred ports< / span >
< span class = "hljs-keyword" > EXPOSE< / span > < span class = "hljs-number" > 19888< / span >
< span class = "hljs-comment" > #Yarn ports< / span >
< span class = "hljs-keyword" > EXPOSE< / span > < span class = "hljs-number" > 8030< / span > < span class = "hljs-number" > 8031< / span > < span class = "hljs-number" > 8032< / span > < span class = "hljs-number" > 8033< / span > < span class = "hljs-number" > 8040< / span > < span class = "hljs-number" > 8042< / span > < span class = "hljs-number" > 8088< / span >
< span class = "hljs-comment" > #Other ports< / span >
< span class = "hljs-keyword" > EXPOSE< / span > < span class = "hljs-number" > 49707< / span > < span class = "hljs-number" > 2122< / span >
< / code > < / pre >
< / li >
< li > < p > < strong > 准 备 应 用 的 配 置 文 件 < / strong > < / p >
< p > 因 为 我 们 只 制 作 了 一 个 Hadoop 的 镜 像 ， 而 需 要 启 动 两 个 服 务 ， 这 就 要 求 在 服 务 启 动 的 时 候 必 须 加 载 不 同 的 配 置 文 件 ， 现 在 我 们 只 需 要 准 备 两 个 服 务 中 需 要 同 时 用 的 的 配 置 的 部 分 。 < / p >
< p > YARN 依 赖 的 配 置 在 < code > artifacts< / code > 目 录 下 ， 包 含 以 下 文 件 ： < / p >
< pre > < code > bootstrap.sh
capacity-scheduler.xml
container-executor.cfg
core-site.xml
hadoop-env.sh
hdfs-site.xml
log4j.properties
mapred-site.xml
nodemanager_exclude.txt
slaves
start-yarn-nm.sh
start-yarn-rm.sh
yarn-env.sh
yarn-site.xml
< / code > < / pre > < p > 其 中 作 为 bootstrap 启 动 脚 本 的 < code > bootstrap.sh< / code > 也 包 含 在 该 目 录 下 ， 该 脚 本 的 如 何 编 写 请 见 下 文 。 < / p >
< / li >
< li > < p > < strong > Kubernetes YAML 文 件 < / strong > < / p >
< p > 根 据 业 务 的 特 性 选 择 最 适 合 的 kubernetes 的 资 源 对 象 来 运 行 ， 因 为 在 YARN 中 NodeManager 需 要 使 用 主 机 名 向 ResourceManger 注 册 ， 因 此 需 要 沿 用 YARN 原 有 的 服 务 发 现 方 式 ， 使 用 headless service 和 StatefulSet 资 源 。 更 多 资 料 请 参 考 < a href = "../concepts/statefulset.html" > StatefulSet< / a > 。 < / p >
< p > 所 有 的 Kubernetes YAML 配 置 文 件 存 储 在 < code > manifest< / code > 目 录 下 ， 包 括 如 下 配 置 ： < / p >
< ul >
< li > yarn-cluster 的 namespace 配 置 < / li >
< li > Spark、 ResourceManager、 NodeManager 的 headless service 和 StatefulSet 配 置 < / li >
< li > 需 要 暴 露 到 kubernetes 集 群 外 部 的 ingress 配 置 （ ResourceManager 的 Web） < / li >
< / ul >
< pre > < code > kube-yarn-ingress.yaml
spark-statefulset.yaml
yarn-cluster-namespace.yaml
yarn-nm-statefulset.yaml
yarn-rm-statefulset.yaml
< / code > < / pre > < / li >
< li > < p > < strong > Bootstrap 脚 本 < / strong > < / p >
< p > Bootstrap 脚 本 的 作 用 是 在 启 动 时 根 据 Pod 的 环 境 变 量 、 主 机 名 或 其 他 可 以 区 分 不 同 Pod 和 将 启 动 角 色 的 变 量 来 修 改 配 置 文 件 和 启 动 服 务 应 用 。 < / p >
< p > 该 脚 本 同 时 将 原 来 YARN 的 日 志 使 用 stdout 输 出 ， 便 于 使 用 < code > kubectl logs< / code > 查 看 日 志 或 其 他 日 志 收 集 工 具 进 行 日 志 收 集 。 < / p >
< p > 启 动 脚 本 < code > bootstrap.sh< / code > 跟 Hadoop 的 配 置 文 件 同 时 保 存 在 < code > artifacts< / code > 目 录 下 。 < / p >
< p > 该 脚 本 根 据 Pod 的 主 机 名 ， 决 定 如 何 修 改 Hadoop 的 配 置 文 件 和 启 动 何 种 服 务 。 < code > bootstrap.sh< / code > 文 件 的 部 分 代 码 如 下 ： < / p >
< pre > < code class = "lang-bash" > < span class = "hljs-keyword" > if< / span > [[ < span class = "hljs-string" > " < span class = "hljs-variable" > ${HOSTNAME}< / span > " < / span > =~ < span class = "hljs-string" > " yarn-nm" < / span > ]]; < span class = "hljs-keyword" > then< / span >
sed -i < span class = "hljs-string" > ' /< \/configuration> /d' < / span > < span class = "hljs-variable" > $HADOOP_PREFIX< / span > /etc/hadoop/yarn-site.xml
cat > > < span class = "hljs-variable" > $HADOOP_PREFIX< / span > /etc/hadoop/yarn-site.xml < < - EOM
< property>
< name> yarn.nodemanager.resource.memory-mb< /name>
< value> < span class = "hljs-variable" > ${MY_MEM_LIMIT:-2048}< / span > < /value>
< /property>
< property>
< name> yarn.nodemanager.resource.cpu-vcores< /name>
< value> < span class = "hljs-variable" > ${MY_CPU_LIMIT:-2}< / span > < /value>
< /property>
EOM
< span class = "hljs-built_in" > echo< / span > < span class = "hljs-string" > ' < /configuration> ' < / span > > > < span class = "hljs-variable" > $HADOOP_PREFIX< / span > /etc/hadoop/yarn-site.xml
cp < span class = "hljs-variable" > ${CONFIG_DIR}< / span > /start-yarn-nm.sh < span class = "hljs-variable" > $HADOOP_PREFIX< / span > /sbin/
< span class = "hljs-built_in" > cd< / span > < span class = "hljs-variable" > $HADOOP_PREFIX< / span > /sbin
chmod +x start-yarn-nm.sh
./start-yarn-nm.sh
< span class = "hljs-keyword" > fi< / span >
< span class = "hljs-keyword" > if< / span > [[ < span class = "hljs-variable" > $1< / span > == < span class = "hljs-string" > " -d" < / span > ]]; < span class = "hljs-keyword" > then< / span >
until find < span class = "hljs-variable" > ${HADOOP_PREFIX}< / span > /logs -mmin -1 | egrep -q < span class = "hljs-string" > ' .*' < / span > ; < span class = "hljs-built_in" > echo< / span > < span class = "hljs-string" > " `date`: Waiting for logs..." < / span > ; < span class = "hljs-keyword" > do< / span > sleep 2 ; < span class = "hljs-keyword" > done< / span >
tail -F < span class = "hljs-variable" > ${HADOOP_PREFIX}< / span > /logs/* &
< span class = "hljs-keyword" > while< / span > < span class = "hljs-literal" > true< / span > ; < span class = "hljs-keyword" > do< / span > sleep 1000; < span class = "hljs-keyword" > done< / span >
< span class = "hljs-keyword" > fi< / span >
< / code > < / pre >
< p > 从 这 部 分 中 代 码 中 可 以 看 到 ， 如 果 Pod 的 主 机 名 中 包 含 < code > yarn-nm< / code > 字 段 则 向 < code > yarn-site.xml< / code > 配 置 文 件 中 增 加 如 下 内 容 ： < / p >
< pre > < code class = "lang-xml" > < span class = "hljs-tag" > < < span class = "hljs-name" > property< / span > > < / span >
< span class = "hljs-tag" > < < span class = "hljs-name" > name< / span > > < / span > yarn.nodemanager.resource.memory-mb< span class = "hljs-tag" > < /< span class = "hljs-name" > name< / span > > < / span >
< span class = "hljs-tag" > < < span class = "hljs-name" > value< / span > > < / span > ${MY_MEM_LIMIT:-2048}< span class = "hljs-tag" > < /< span class = "hljs-name" > value< / span > > < / span >
< span class = "hljs-tag" > < /< span class = "hljs-name" > property< / span > > < / span >
< span class = "hljs-tag" > < < span class = "hljs-name" > property< / span > > < / span >
< span class = "hljs-tag" > < < span class = "hljs-name" > name< / span > > < / span > yarn.nodemanager.resource.cpu-vcores< span class = "hljs-tag" > < /< span class = "hljs-name" > name< / span > > < / span >
< span class = "hljs-tag" > < < span class = "hljs-name" > value< / span > > < / span > ${MY_CPU_LIMIT:-2}< span class = "hljs-tag" > < /< span class = "hljs-name" > value< / span > > < / span >
< span class = "hljs-tag" > < /< span class = "hljs-name" > property< / span > > < / span >
< / code > < / pre >
< p > 其 中 < code > MY_MEM_LIMIT< / code > 和 < code > MY_CPU_LIMIT< / code > 是 kubernetes YAML 中 定 义 的 环 境 变 量 ， 该 环 境 变 量 又 是 引 用 的 Resource limit。 < / p >
< p > 所 有 的 配 置 准 备 完 成 后 ， 执 行 < code > start-yarn-nm.sh< / code > 脚 本 启 动 NodeManager。 < / p >
< p > 如 果 kubernetes YAML 中 的 container CMD args 中 包 含 < code > -d< / code > 则 在 后 台 运 行 NodeManger 并 tail 输 出 NodeManager 的 日 志 到 标 准 输 出 。 < / p >
< / li >
< li > < p > < strong > ConfigMaps< / strong > < / p >
< p > 将 Hadoop 的 配 置 文 件 和 bootstrap 脚 本 作 为 ConfigMap 资 源 保 存 ， 用 作 Pod 启 动 时 挂 载 的 volume。 < / p >
< pre > < code class = "lang-bash" > kubectl create configmap hadoop-config \
--from-file=artifacts/hadoop/bootstrap.sh \
--from-file=artifacts/hadoop/start-yarn-rm.sh \
--from-file=artifacts/hadoop/start-yarn-nm.sh \
--from-file=artifacts/hadoop/slaves \
--from-file=artifacts/hadoop/core-site.xml \
--from-file=artifacts/hadoop/hdfs-site.xml \
--from-file=artifacts/hadoop/mapred-site.xml \
--from-file=artifacts/hadoop/yarn-site.xml \
--from-file=artifacts/hadoop/capacity-scheduler.xml \
--from-file=artifacts/hadoop/container-executor.cfg \
--from-file=artifacts/hadoop/hadoop-env.sh \
--from-file=artifacts/hadoop/< span class = "hljs-built_in" > log< / span > 4j.properties \
--from-file=artifacts/hadoop/nodemanager_exclude.txt \
--from-file=artifacts/hadoop/yarn-env.sh
kubectl create configmap spark-config \
--from-file=artifacts/spark/spark-bootstrap.sh \
--from-file=artifacts/spark/spark-env.sh \
--from-file=artifacts/spark/spark-defaults.conf
< / code > < / pre >
< / li >
< / ol >
< p > 所 有 的 配 置 完 成 后 ， 可 以 可 以 使 用 kubectl 命 令 来 启 动 和 管 理 集 群 了 ， 我 们 编 写 了 Makefile， 您 可 以 直 接 使 用 该 Makefile 封 装 的 命 令 实 现 部 分 的 自 动 化 。 < / p >
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gitbook.page.hasChanged({"page":{"title":"3.5.2 迁移传统应用到kubernetes中——以Hadoop YARN为例","level":"1.3.5.2","depth":3,"next":{"title":"4. 最佳实践","level":"1.4","depth":1,"path":"practice/index.md","ref":"practice/index.md","articles":[{"title":" 4.1 在CentOS上部署kubernetes1.6集群","level":"1.4.1","depth":2,"path":"practice/install-kbernetes1.6-on-centos.md","ref":"practice/install-kbernetes1.6-on-centos.md","articles":[{"title":"4.1.1 创建TLS证书和秘钥","level":"1.4.1.1","depth":3,"path":"practice/create-tls-and-secret-key.md","ref":"practice/create-tls-and-secret-key.md","articles":[]},{"title":"4.1.2 创建kubeconfig文件","level":"1.4.1.2","depth":3,"path":"practice/create-kubeconfig.md","ref":"practice/create-kubeconfig.md","articles":[]},{"title":"4.1.3 创建高可用etcd集群","level":"1.4.1.3","depth":3,"path":"practice/etcd-cluster-installation.md","ref":"practice/etcd-cluster-installation.md","articles":[]},{"title":"4.1.4 安装kubectl命令行工具","level":"1.4.1.4","depth":3,"path":"practice/kubectl-installation.md","ref":"practice/kubectl-installation.md","articles":[]},{"title":"4.1.5 部署master节点","level":"1.4.1.5","depth":3,"path":"practice/master-installation.md","ref":"practice/master-installation.md","articles":[]},{"title":"4.1.6 部署node节点","level":"1.4.1.6","depth":3,"path":"practice/node-installation.md","ref":"practice/node-installation.md","articles":[]},{"title":"4.1.7 安装kubedns插件","level":"1.4.1.7","depth":3,"path":"practice/kubedns-addon-installation.md","ref":"practice/kubedns-addon-installation.md","articles":[]},{"title":"4.1.8 安装dashboard插件","level":"1.4.1.8","depth":3,"path":"practice/dashboard-addon-installation.md","ref":"practice/dashboard-addon-installation.md","articles":[]},{"title":"4.1.9 安装heapster插件","level":"1.4.1.9","depth":3,"path":"practice/heapster-addon-installation.md","ref":"practice/heapster-addon-installation.md","articles":[]},{"title":"4.1.10 安装EFK插件","level":"1.4.1.10","depth":3,"path":"practice/efk-addon-installation.md","ref":"practice/efk-addon-installation.md","articles":[]}]},{"title":"4.2 服务发现与负载均衡","level":"1.4.2","depth":2,"path":"practice/service-discovery-and-loadbalancing.md","ref":"practice/service-discovery-and-loadbalancing.md","articles":[{"title":"4.2.1 安装Traefik ingress","level":"1.4.2.1","depth":3,"path":"practice/traefik-ingress-installation.md","ref":"practice/traefik-ingress-installation.md","articles":[]},{"title":"4.2.2 分布式负载测试","level":"1.4.2.2","depth":3,"path":"practice/distributed-load-test.md","ref":"practice/distributed-load-test.md","articles":[]},{"title":"4.2.3 网络和集群性能测试","level":"1.4.2.3","depth":3,"path":"practice/network-and-cluster-perfermance-test.md","ref":"practice/network-and-cluster-perfermance-test.md","articles":[]},{"title":"4.2.4 边缘节点配置","level":"1.4.2.4","depth":3,"path":"practice/edge-node-configuration.md","ref":"practice/edge-node-configuration.md","articles":[]}]},{"title":"4.3 运维管理","level":"1.4.3","depth":2,"path":"practice/operation.md","ref":"practice/operation.md","articles":[{"title":"4.3.1 服务滚动升级","level":"1.4.3.1","depth":3,"path":"practice/service-rolling-update.md","ref":"practice/service-rolling-update.md","articles":[]},{"title":"4.3.2 应用日志收集","level":"1.4.3.2","depth":3,"path":"practice/app-log-collection.md","ref":"practice/app-log-collection.md","articles":[]},{"title":"4.3.3 配置最佳实践","level":"1.4.3.3","depth":3,"path":"practice/configuration-best-practice.md","ref":"practice/configuration-best-practice.md","articles":[]},{"title":"4.3.4 集群及应用监控","level":"1.4.3.4","depth":3,"path":"practice/monitor.md","ref":"practice/monitor.md","articles":[]},{"title":"4.3.5 使用Jenkins进行持续构建与发布","level":"1.4.3.5","depth":3,"path":"practice/jenkins-ci-cd.md","ref":"practice/jenkins-ci-cd.md","articles":[]},{"title":"4.3.6 数据持久化问题","level":"1.4.3.6","depth":3,"path
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