Kubernetes 部署策略：滚动更新、蓝绿部署和金丝雀发布

Kubernetes 部署策略

选择合适的部署策略需要在风险、速度和复杂性之间取得平衡。

滚动更新（默认）

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api
spec:
  replicas: 6
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 2           # 更新期间允许超出期望副本数的最大 Pod 数
      maxUnavailable: 1     # 更新期间允许不可用的最大 Pod 数
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
        - name: api
          image: myapp/api:v2
          readinessProbe:
            httpGet:
              path: /health/ready
              port: 3000
            initialDelaySeconds: 5
            periodSeconds: 5
            failureThreshold: 3
          livenessProbe:
            httpGet:
              path: /health/live
              port: 3000
            initialDelaySeconds: 15
            periodSeconds: 20
      terminationGracePeriodSeconds: 30  # 让请求完成

# 执行滚动更新
kubectl set image deployment/api api=myapp/api:v2

# 监控滚动更新状态
kubectl rollout status deployment/api

# 如果需要，回滚
kubectl rollout undo deployment/api
kubectl rollout undo deployment/api --to-revision=2

蓝绿部署

# Blue（当前生产环境）
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-blue
spec:
  replicas: 5
  selector:
    matchLabels:
      app: api
      version: blue

---
# Green（新版本）
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-green
spec:
  replicas: 5
  selector:
    matchLabels:
      app: api
      version: green

---
# Service 初始指向 blue
apiVersion: v1
kind: Service
metadata:
  name: api
spec:
  selector:
    app: api
    version: blue  # 改为 "green" 以切换流量
  ports:
    - port: 80
      targetPort: 3000

# 将所有流量切换到 green
kubectl patch service api -p '{"spec":{"selector":{"version":"green"}}}'

# 验证 green 是否正常工作
kubectl get pods -l version=green

# 确认 green 稳定后，缩容 blue
kubectl scale deployment api-blue --replicas=0

# 或完全删除 blue
kubectl delete deployment api-blue

使用 Argo Rollouts 进行金丝雀发布

apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
  name: api
spec:
  replicas: 10
  strategy:
    canary:
      steps:
        - setWeight: 10    # 10% 流量到金丝雀
        - pause: { duration: 5m }
        - setWeight: 30
        - pause: { duration: 10m }
        - analysis:
            templates:
              - templateName: success-rate
        - setWeight: 60
        - pause: { duration: 10m }
        - setWeight: 100
      canaryMetadata:
        labels:
          version: canary
      stableMetadata:
        labels:
          version: stable
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
        - name: api
          image: myapp/api:v2

---
# 用于自动升级的分析模板
apiVersion: argoproj.io/v1alpha1
kind: AnalysisTemplate
metadata:
  name: success-rate
spec:
  metrics:
    - name: success-rate
      interval: 1m
      successCondition: result[0] >= 0.95
      failureLimit: 3
      provider:
        prometheus:
          address: http://prometheus:9090
          query: |
            sum(rate(http_requests_total{job="api",status!~"5.."}[5m]))
            /
            sum(rate(http_requests_total{job="api"}[5m]))

PodDisruptionBudget

# 确保在自愿中断期间的最小可用性
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: api-pdb
spec:
  minAvailable: 4    # 始终保持 4 个 Pod 运行
  selector:
    matchLabels:
      app: api

重要的健康检查

// Liveness vs Readiness vs Startup probes
app.get('/health/live', (req, res) => {
  // Liveness：进程是否存活？（失败则重启）
  res.json({ status: 'alive' })
})

app.get('/health/ready', async (req, res) => {
  // Readiness：是否可以处理流量？（失败则从负载均衡中移除）
  try {
    await db.query('SELECT 1')
    await redis.ping()
    res.json({ status: 'ready' })
  } catch (err) {
    res.status(503).json({ status: 'not ready', reason: err.message })
  }
})

app.get('/health/startup', (req, res) => {
  // Startup：初始化是否完成？（仅在启动期间）
  if (appStarted) {
    res.json({ status: 'started' })
  } else {
    res.status(503).json({ status: 'starting' })
  }
})