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

apiVersion: apps/v1
kind: Deployment
spec:
  template:
    spec:
      containers:
      - name: {APP_NAME}
        image: {IMAGE_URL}
        imagePullPolicy: Always
        ports:
        - containerPort: {APP_PORT}
        - containerPort: 50000
        lifecycle:
          preStop:       # 结束回调钩子
            exec:
              command: ["curl", "-XPOST", "127.0.0.1:50000/actuator/shutdown"]

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

<!-- 引入Spring boot的监控机制-->
<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