K8s + SpringBoot实现零宕机发布

偏执的太偏执、 2023-09-23 21:53 68阅读 0赞

## 前言 ##

K8s + SpringBoot实现零宕机发布：健康检查+滚动更新+优雅停机+弹性伸缩+Prometheus监控+配置分离（镜像复用）

## 配置 ##

### 健康检查 ###

*  健康检查类型：就绪探针（readiness）+ 存活探针（liveness）
 *  探针类型：exec（进入容器执行脚本）、tcpSocket（探测端口）、httpGet（调用接口）

业务层面

项目依赖 pom.xml

<dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-actuator</artifactId>
    </dependency>

定义访问端口、路径及权限 application.yaml

management:
      server:
        port: 50000                         # 启用独立运维端口
      endpoint:                             # 开启health端点
        health:
          probes:
            enabled: true
      endpoints:
        web:
          exposure:
            base-path: /actuator            # 指定上下文路径，启用相应端点
            include: health

将暴露`/actuator/health/readiness`和`/actuator/health/liveness`两个接口，访问方式如下：

http://127.0.0.1:50000/actuator/health/readiness
    http://127.0.0.1:50000/actuator/health/liveness

运维层面

k8s部署模版deployment.yaml

apiVersion: apps/v1
    kind: Deployment
    spec:
      template:
        spec:
          containers:
          - name: {APP_NAME}
            image: {IMAGE_URL}
            imagePullPolicy: Always
            ports:
            - containerPort: {APP_PORT}
            - name: management-port
              containerPort: 50000         # 应用管理端口
            readinessProbe:                # 就绪探针
              httpGet:
                path: /actuator/health/readiness
                port: management-port
              initialDelaySeconds: 30      # 延迟加载时间
              periodSeconds: 10            # 重试时间间隔
              timeoutSeconds: 1            # 超时时间设置
              successThreshold: 1          # 健康阈值
              failureThreshold: 6          # 不健康阈值
            livenessProbe:                 # 存活探针
              httpGet:
                path: /actuator/health/liveness
                port: management-port
              initialDelaySeconds: 30      # 延迟加载时间
              periodSeconds: 10            # 重试时间间隔
              timeoutSeconds: 1            # 超时时间设置
              successThreshold: 1          # 健康阈值
              failureThreshold: 6          # 不健康阈值

### 滚动更新 ###

k8s资源调度之滚动更新策略，若要实现零宕机发布，需支持健康检查

优雅停机

在K8s中，当我们实现滚动升级之前，务必要实现应用级别的优雅停机。否则滚动升级时，还是会影响到业务。使应用关闭线程、释放连接资源后再停止服务

业务层面

项目依赖 pom.xml

<dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-actuator</artifactId>
    </dependency>

定义访问端口、路径及权限 application.yaml

spring:
      application:
        name: <xxx>
      profiles:
        active: @profileActive@
      lifecycle:
        timeout-per-shutdown-phase: 30s     # 停机过程超时时长设置30s，超过30s，直接停机
    
    server:
      port: 8080
      shutdown: graceful                    # 默认为IMMEDIATE，表示立即关机；GRACEFUL表示优雅关机
    
    management:
      server:
        port: 50000                         # 启用独立运维端口
      endpoint:                             # 开启shutdown和health端点
        shutdown:
          enabled: true
        health:
          probes:
            enabled: true
      endpoints:
        web:
          exposure:
            base-path: /actuator            # 指定上下文路径，启用相应端点
            include: health,shutdown

将暴露`/actuator/shutdown`接口，调用方式如下：

curl -X POST 127.0.0.1:50000/actuator/shutdown

运维层面

确保dockerfile模版集成curl工具，否则无法使用curl命令

FROM openjdk:8-jdk-alpine
    #构建参数
    ARG JAR_FILE
    ARG WORK_PATH="/app"
    ARG EXPOSE_PORT=8080
    
    #环境变量
    ENV JAVA_OPTS=""\
        JAR_FILE=${JAR_FILE}
    
    #设置时区
    RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
    RUN sed -i 's/dl-cdn.alpinelinux.org/mirrors.ustc.edu.cn/g' /etc/apk/repositories  \
        && apk add --no-cache curl
    #将maven目录的jar包拷贝到docker中，并命名为for_docker.jar
    COPY target/$JAR_FILE $WORK_PATH/
    
    
    #设置工作目录
    WORKDIR $WORK_PATH
    
    
    # 指定于外界交互的端口
    EXPOSE $EXPOSE_PORT
    # 配置容器，使其可执行化
    ENTRYPOINT exec java $JAVA_OPTS -jar $JAR_FILE

k8s部署模版deployment.yaml

> 注：经验证，java项目可省略结束回调钩子的配置

此外，若需使用回调钩子，需保证镜像中包含curl工具，且需注意应用管理端口（50000）不能暴露到公网

### 弹性伸缩 ###

为pod设置资源限制后，创建HPA

apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: {APP_NAME}
      labels:
        app: {APP_NAME}
    spec:
      template:
        spec:
          containers:
          - name: {APP_NAME}
            image: {IMAGE_URL}
            imagePullPolicy: Always
            resources:                     # 容器资源管理
              limits:                      # 资源限制（监控使用情况）
                cpu: 0.5
                memory: 1Gi
              requests:                    # 最小可用资源（灵活调度）
                cpu: 0.15
                memory: 300Mi
    ---
    kind: HorizontalPodAutoscaler            # 弹性伸缩控制器
    apiVersion: autoscaling/v2beta2
    metadata:
      name: {APP_NAME}
    spec:
      scaleTargetRef:
        apiVersion: apps/v1
        kind: Deployment
        name: {APP_NAME}
      minReplicas: {REPLICAS}                # 缩放范围
      maxReplicas: 6
      metrics:
        - type: Resource
          resource:
            name: cpu                        # 指定资源指标
            target:
              type: Utilization
              averageUtilization: 50

### Prometheus集成 ###

业务层面

项目依赖 pom.xml

<dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-actuator</artifactId>
    </dependency>
    <dependency>
        <groupId>io.micrometer</groupId>
        <artifactId>micrometer-registry-prometheus</artifactId>
    </dependency>

定义访问端口、路径及权限 application.yaml

management:
      server:
        port: 50000                         # 启用独立运维端口
      metrics:
        tags:
          application: ${spring.application.name}
      endpoints:
        web:
          exposure:
            base-path: /actuator            # 指定上下文路径，启用相应端点
            include: metrics,prometheus

将暴露`/actuator/metric`和`/actuator/prometheus`接口，访问方式如下：

http://127.0.0.1:50000/actuator/metric
    http://127.0.0.1:50000/actuator/prometheus

运维层面

deployment.yaml

apiVersion: apps/v1
    kind: Deployment
    spec:
      template:
        metadata:
          annotations:
            prometheus:io/port: "50000"
            prometheus.io/path: /actuator/prometheus  # 在流水线中赋值
            prometheus.io/scrape: "true"              # 基于pod的服务发现

### 配置分离 ###

方案：通过configmap挂载外部配置文件，并指定激活环境运行

作用：配置分离，避免敏感信息泄露；镜像复用，提高交付效率

通过文件生成configmap

# 通过dry-run的方式生成yaml文件
    kubectl create cm -n <namespace> <APP_NAME> --from-file=application-test.yaml --dry-run=1 -oyaml > configmap.yaml
    
    # 更新
    kubectl apply -f configmap.yaml

挂载configmap并指定激活环境

apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: {APP_NAME}
      labels:
        app: {APP_NAME}
    spec:
      template:
        spec:
          containers:
          - name: {APP_NAME}
            image: {IMAGE_URL}
            imagePullPolicy: Always
            env:
              - name: SPRING_PROFILES_ACTIVE   # 指定激活环境
                value: test
            volumeMounts:                      # 挂载configmap
            - name: conf
              mountPath: "/app/config"         # 与Dockerfile中工作目录一致
              readOnly: true
          volumes:
          - name: conf
            configMap:
              name: {APP_NAME}

## 汇总配置 ##

### 业务层面 ###

项目依赖 pom.xml

定义访问端口、路径及权限 application.yaml

spring:
      application:
        name: project-sample
      profiles:
        active: @profileActive@
      lifecycle:
        timeout-per-shutdown-phase: 30s     # 停机过程超时时长设置30s，超过30s，直接停机
    
    server:
      port: 8080
      shutdown: graceful                    # 默认为IMMEDIATE，表示立即关机；GRACEFUL表示优雅关机
    
    management:
      server:
        port: 50000                         # 启用独立运维端口
      metrics:
        tags:
          application: ${spring.application.name}
      endpoint:                             # 开启shutdown和health端点
        shutdown:
          enabled: true
        health:
          probes:
            enabled: true
      endpoints:
        web:
          exposure:
            base-path: /actuator            # 指定上下文路径，启用相应端点
            include: health,shutdown,metrics,prometheus

### 运维层面 ###

确保dockerfile模版集成curl工具，否则无法使用curl命令

k8s部署模版deployment.yaml

apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: {APP_NAME}
      labels:
        app: {APP_NAME}
    spec:
      selector:
        matchLabels:
          app: {APP_NAME}
      replicas: {REPLICAS}                            # Pod副本数
      strategy:
        type: RollingUpdate                           # 滚动更新策略
        rollingUpdate:
          maxSurge: 1
          maxUnavailable: 0
      template:
        metadata:
          name: {APP_NAME}
          labels:
            app: {APP_NAME}
          annotations:
            timestamp: {TIMESTAMP}
            prometheus.io/port: "50000"               # 不能动态赋值
            prometheus.io/path: /actuator/prometheus
            prometheus.io/scrape: "true"              # 基于pod的服务发现
        spec:
          affinity:                                   # 设置调度策略，采取多主机/多可用区部署
            podAntiAffinity:
              preferredDuringSchedulingIgnoredDuringExecution:
              - weight: 100
                podAffinityTerm:
                  labelSelector:
                    matchExpressions:
                    - key: app
                      operator: In
                      values:
                      - {APP_NAME}
                  topologyKey: "kubernetes.io/hostname" # 多可用区为"topology.kubernetes.io/zone"
          terminationGracePeriodSeconds: 30             # 优雅终止宽限期
          containers:
          - name: {APP_NAME}
            image: {IMAGE_URL}
            imagePullPolicy: Always
            ports:
            - containerPort: {APP_PORT}
            - name: management-port
              containerPort: 50000         # 应用管理端口
            readinessProbe:                # 就绪探针
              httpGet:
                path: /actuator/health/readiness
                port: management-port
              initialDelaySeconds: 30      # 延迟加载时间
              periodSeconds: 10            # 重试时间间隔
              timeoutSeconds: 1            # 超时时间设置
              successThreshold: 1          # 健康阈值
              failureThreshold: 9          # 不健康阈值
            livenessProbe:                 # 存活探针
              httpGet:
                path: /actuator/health/liveness
                port: management-port
              initialDelaySeconds: 30      # 延迟加载时间
              periodSeconds: 10            # 重试时间间隔
              timeoutSeconds: 1            # 超时时间设置
              successThreshold: 1          # 健康阈值
              failureThreshold: 6          # 不健康阈值
            resources:                     # 容器资源管理
              limits:                      # 资源限制（监控使用情况）
                cpu: 0.5
                memory: 1Gi
              requests:                    # 最小可用资源（灵活调度）
                cpu: 0.1
                memory: 200Mi
            env:
              - name: TZ
                value: Asia/Shanghai
    ---
    kind: HorizontalPodAutoscaler            # 弹性伸缩控制器
    apiVersion: autoscaling/v2beta2
    metadata:
      name: {APP_NAME}
    spec:
      scaleTargetRef:
        apiVersion: apps/v1
        kind: Deployment
        name: {APP_NAME}
      minReplicas: {REPLICAS}                # 缩放范围
      maxReplicas: 6
      metrics:
        - type: Resource
          resource:
            name: cpu                        # 指定资源指标
            target:
              type: Utilization
              averageUtilization: 50