.NET項(xiàng)目在k8s中運(yùn)行的Dapr持續(xù)集成流程

更新時(shí)間：2022年04月02日 08:35:50 作者：重典

這篇文章主要介紹了.NET項(xiàng)目在k8s中運(yùn)行的Dapr持續(xù)集成流程，有需要的朋友可以借鑒參考下，希望能夠有所幫助，祝大家多多進(jìn)步早日升職加薪

流程選擇

基于 Dapr 的項(xiàng)目持續(xù)集成包含以下流程

編譯并打包項(xiàng)目
構(gòu)建 Dockerfile,并推送鏡像push image至私有倉庫
準(zhǔn)備 k8s 部署的配置文件
通過 kubectl 部署鏡像至 k8s 中

這里面有多種方案

-	Pipeline的操作	Publish的操作	優(yōu)點(diǎn)	缺點(diǎn)
1. 直接BuildImage并發(fā)布	1. 直接使用 Docker Build Image 2. push image 3.復(fù)制Yaml至Artifacts	K8s 直接發(fā)布對應(yīng)版本的yaml + 指定Image	直接,操作簡單	1. 產(chǎn)生大量不必要的Image 2.持續(xù)集成消耗時(shí)間較長3.每次持續(xù)集成都有Image產(chǎn)生
2. Publish時(shí)再進(jìn)行Build	1. 僅 dotnet publish zip	1. Build Image / Push Image （可選）2. K8S 部署+指定Image	單次部署減慢，多次增快	部署過程會(huì)比直接接取鏡像慢
3. 僅發(fā)布 Zip，并Build一個(gè)使用Volume的專署鏡像	僅 dotnet publish zip	使用編譯好的鏡像修改Volume參數(shù)	快	跨環(huán)境部署時(shí)會(huì)導(dǎo)致對于文件系統(tǒng)依賴過重

鑒于以上優(yōu)缺點(diǎn)，最終我選擇了第二種折衷方案，這種方案既不影響持續(xù)集成的速度，也不會(huì)產(chǎn)生過多的鏡像，只是在部署時(shí)會(huì)產(chǎn)生多余的鏡像構(gòu)建時(shí)間。

項(xiàng)目結(jié)構(gòu)

每個(gè)要發(fā)布的API的 project 文件夾中增加以下文件

dapr.yaml

Dockerfile

dapr.yaml

kind: Deployment
apiVersion: apps/v1
metadata:
  name: demo
  namespace: dapr-api
  labels:
    app: .api
    service: demo
spec:
  replicas: 1
  selector:
    matchLabels:
      service: demo
  template:
    metadata:
      labels:
        app: .api
        service: demo
      annotations:
        dapr.io/enabled: "true"
        dapr.io/app-id: "demo-api"
        dapr.io/app-port: "80"
        dapr.io/log-as-json: "true"
    spec:
      containers:
        - name: demo-api
          image: 倉庫地址/鏡像名:220310.13
          ports:
            - name: http
              containerPort: 80
              protocol: TCP
          imagePullPolicy: IfNotPresent
---
kind: Service
apiVersion: v1
metadata:
  name: demo-api
  namespace: dapr-api
  labels:
    app: .api
    service: demo
spec:
  type: NodePort
  selector:
    service: demo
  ports:
  - protocol: TCP
    port: 80
    targetPort: 80
    nodePort: 30004

Dockerfile

FROM mcr.microsoft.com/dotnet/aspnet:6.0 AS final
WORKDIR /app
EXPOSE 80
COPY ["./projectfolder", "/app"]
ENTRYPOINT ["dotnet", "projectdll.dll"]

這兩個(gè)文件需要每個(gè)項(xiàng)目不同，后面在編譯和部署流程中會(huì)用到。

Pipelines 持續(xù)集成的配置文件

trigger:
  batch: true
pool:
  name: Default
name: $(Date:yy)$(Date:MM)$(Date:dd)$(Rev:.r)

variables:
    BuildConfiguration: 'Release'
steps:
- task: UseDotNet@2
  displayName: 'Check and Install .NET SDK 6.0'
  inputs:
    version: '6.0.x'
    includePreviewVersions: false

- task: DotNetCoreCLI@2
  displayName: 'Publish to zip'
  inputs:
    command: publish
    publishWebProjects: false
    projects: './src/projectfolder/project.csproj'
    arguments: '--configuration $(BuildConfiguration) --output $(build.artifactstagingdirectory) -v n'
    zipAfterPublish: false
    workingDirectory: '$(Build.SourcesDirectory)/src'
## 復(fù)制上文中的兩個(gè)文件到 Artifact
- task: CopyFiles@2
  displayName: 'Copy dapr.yaml to: $(build.artifactstagingdirectory)'
  inputs:
    SourceFolder: './src/${{ parameters.project }}/'
    Contents: |
      Dockerfile
      dapr.yaml
    TargetFolder: '$(build.artifactstagingdirectory)'
- task: PublishBuildArtifacts@1
  displayName: 'Publish Artifact'
  inputs:
    PathtoPublish: '$(build.artifactstagingdirectory)'

Release 發(fā)布流程配置文件

發(fā)布流程新建兩個(gè)作業(yè)

作業(yè)1 Build Image

variables:
  image: '自定義鏡像名'
steps:
- task: Docker@2
  displayName: buildAndPush
  inputs:
    containerRegistry: harbor
    repository: '$(image)'
    Dockerfile: '$(System.DefaultWorkingDirectory)/_dapr-demo/drop/Dockerfile'
    tags: '$(Build.BuildNumber)'

作業(yè)2 KubeDeploy

variables:
  image: '自定義鏡像名,與上文須一致'

steps:
- task: KubernetesManifest@0
  displayName: deploy
  inputs:
    kubernetesServiceConnection: online
    namespace: '$(ns)' ## k8s的部署目標(biāo)命名空間
    strategy: canary ## 灰度部署策略
    percentage: 50
    manifests: '$(System.DefaultWorkingDirectory)/_dapr-demo/drop/dapr.yaml'
    containers: '$(harborUrl)/$(image):$(Build.BuildNumber)'

這樣，在首次部署時(shí)執(zhí)行全部管道。