作業原理

為了實作在k8s上安裝Dapr，Dapr需要部署dapr-sidecar-injector、dapr-operator、dapr-placement和dapr-sentry服務，

dapr-operator: 管理組件(state stores, pub/subs, etc.)
dapr-sidecar-injector: 將 Dapr 注入 annotated pods，并添加環境變數 DAPR_HTTP_PORT 和 DAPR_GRPC_PORT，以使用戶定義的應用程式能夠輕松地與 Dapr Sidecar通信，而無需硬編碼 Dapr 埠值，
dapr-placement: 將 actor 實體映射到 pods，
dapr-sentry: 管理服務之間的mTLS并作為證書頒發機構，

2.安裝K8s集群

通常使用以下方法本地安裝的K8S集群

k8s-for-docker-desktop
kubeadm

我本地已經安裝好了這兩種，這次使用kubeadm 1.20版本演示dapr

3.將Frontend和Backend build成docker Image

vs中分別右擊Frontend和Backend，添加Docker支持，即可生成對應的Dockerfile，修改暴露埠

#See https://aka.ms/containerfastmode to understand how Visual Studio uses this Dockerfile to build your images for faster debugging.

FROM mcr.microsoft.com/dotnet/aspnet:5.0 AS base
WORKDIR /app
EXPOSE 5001

FROM mcr.microsoft.com/dotnet/sdk:5.0 AS build
WORKDIR /src
COPY ["FrontEnd/FrontEnd.csproj", "FrontEnd/"]
RUN dotnet restore "FrontEnd/FrontEnd.csproj"
COPY . .
WORKDIR "/src/FrontEnd"
RUN dotnet build "FrontEnd.csproj" -c Release -o /app/build

FROM build AS publish
RUN dotnet publish "FrontEnd.csproj" -c Release -o /app/publish

FROM base AS final
WORKDIR /app
COPY --from=publish /app/publish .
ENTRYPOINT ["dotnet", "FrontEnd.dll"]

#See https://aka.ms/containerfastmode to understand how Visual Studio uses this Dockerfile to build your images for faster debugging.

FROM mcr.microsoft.com/dotnet/aspnet:5.0 AS base
WORKDIR /app
EXPOSE 5000

FROM mcr.microsoft.com/dotnet/sdk:5.0 AS build
WORKDIR /src
COPY ["BackEnd/BackEnd.csproj", "BackEnd/"]
RUN dotnet restore "BackEnd/BackEnd.csproj"
COPY . .
WORKDIR "/src/BackEnd"
RUN dotnet build "BackEnd.csproj" -c Release -o /app/build

FROM build AS publish
RUN dotnet publish "BackEnd.csproj" -c Release -o /app/publish

FROM base AS final
WORKDIR /app
COPY --from=publish /app/publish .
ENTRYPOINT ["dotnet", "BackEnd.dll"]

通過以下命令Build Image

docker build -t frontend -f  ./FrontEnd/Dockerfile .

docker build -t backend -f  ./BackEnd/Dockerfile .

4.將Docker Image推送到倉庫

我使用阿里云私有倉庫來上傳鏡像，創建frontend和backend兩個庫

按照以下提示步驟將frontend和backend Image上傳到指定庫

5.讓k8s使用私有倉庫拉取鏡像

k8s主節點登錄阿里云私庫

docker login --username=xxx registry.cn-beijing.aliyuncs.com

docker登錄之后，會把密鑰存到一個組態檔，通過下面命令拿到base64編碼資訊

cat ~/.docker/config.json | base64

新建ali-docker-repo.yaml，.dockerconfigjson就是上一步得到的base64

[root@k8s-master dapr-demo]# cat ali-docker-repo.yaml
apiVersion: v1
kind: Secret
metadata:
 name: ali-key
type: kubernetes.io/dockerconfigjson
data:
 .dockerconfigjson: ewoJImF1dGhzIjogewoJCSJyZWdpc3RyeS5jbi1iZWlqaW5nLmFsaXl1bmNzLmNvbSI6IHs..............

apply secret

[root@k8s-master dapr-demo]# kubectl apply -f ali-docker-repo.yaml

6.安裝Dapr CLI

下面命令將DaprCLI安裝到 /usr/local/bin

wget -q https://raw.githubusercontent.com/dapr/cli/master/install/install.sh -O - | /bin/bash

7.驗證Dapr CLI

dapr

8.初始化Dapr

首先，請確保你的機器已經安裝了 Helm 3 ，

然后，添加 Helm 庫并更新

helm repo add dapr https://dapr.github.io/helm-charts/
helm repo update
# See which chart versions are available
helm search repo dapr --devel --versions

將 Dapr 圖表安裝在你的集群的 dapr-system命名空間中，

helm upgrade --install dapr dapr/dapr \
--version=1.2 \
--namespace dapr-system \
--create-namespace \
--wait

驗證安裝

[root@k8s-master dapr-demo]# kubectl get pods --namespace dapr-system
NAME                                     READY   STATUS    RESTARTS   AGE
dapr-dashboard-58b4647996-828n8          1/1     Running   2          9d
dapr-operator-85bdd7d89d-5d8dw           1/1     Running   19         9d
dapr-placement-server-0                  1/1     Running   3          9d
dapr-sentry-76bfc5f7c7-vn2qt             1/1     Running   2          9d
dapr-sidecar-injector-786645f444-dmzm7   1/1     Running   2          9d

9.配置狀態存盤和訂閱發布組件

我們仍然通過helm安裝redis，因為redis是statefulset，因此需要先把redis依賴的storageclass和pv創建好

新建redis-storage-class.yaml

[root@k8s-master dapr-demo]# cat redis-storage-class.yaml
kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: local-storage-redis
provisioner: kubernetes.io/no-provisioner
volumeBindingMode: WaitForFirstConsumer

apply storageclass

[root@k8s-master dapr-demo]# kubectl apply -f redis-storage-class.yaml

由于我們即將安裝的redis，使用默認的storageclass，我們需要把我們剛剛新建的storageclass置為默認

kubectl patch storageclass local-storage-redis -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true"}}}'

因為我們即將安裝的redis集群有四個節點，我們需新建四個pv，新建檔案redis-pv.yaml

apiVersion: v1
kind: PersistentVolume
metadata:
  name: local-pv-redis
spec:
  capacity:
    storage: 8Gi
  # volumeMode field requires BlockVolume Alpha feature gate to be enabled.
  volumeMode: Filesystem
  accessModes:
  - ReadWriteOnce
  storageClassName: local-storage-redis
  persistentVolumeReclaimPolicy: Retain
  local:
    path: /local-storage/redis
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - k8s-node1

---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: local-pv-redis2
spec:
  capacity:
    storage: 8Gi
  # volumeMode field requires BlockVolume Alpha feature gate to be enabled.
  volumeMode: Filesystem
  accessModes:
  - ReadWriteOnce
  storageClassName: local-storage-redis
  persistentVolumeReclaimPolicy: Retain
  local:
    path: /local-storage/redis
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - k8s-node1

---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: local-pv-redis3
spec:
  capacity:
    storage: 8Gi
  # volumeMode field requires BlockVolume Alpha feature gate to be enabled.
  volumeMode: Filesystem
  accessModes:
  - ReadWriteOnce
  storageClassName: local-storage-redis
  persistentVolumeReclaimPolicy: Retain
  local:
    path: /local-storage/redis
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - k8s-node1


---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: local-pv-redis4
spec:
  capacity:
    storage: 8Gi
  # volumeMode field requires BlockVolume Alpha feature gate to be enabled.
  volumeMode: Filesystem
  accessModes:
  - ReadWriteOnce
  storageClassName: local-storage-redis
  persistentVolumeReclaimPolicy: Retain
  local:
    path: /local-storage/redis
  nodeAffinity:
    required:
      nodeSelectorTerms:
      - matchExpressions:
        - key: kubernetes.io/hostname
          operator: In
          values:
          - k8s-node1

因為我們指定了四個pv調度在k8s-node1上，所以需要去node1上新建掛載目錄/local-storage/redis

mkdir /local-storage
cd /local-storage
mkdir /redis

apply pv

kubectl apply -f redis-pv.yaml

安裝redis到集群

helm repo add bitnami https://charts.bitnami.com/bitnami
helm repo update
helm install redis bitnami/redis

查看redis pod

[root@k8s-master dapr-demo]# kubectl get pod
redis-master-0              1/1     Running   0          141m
redis-replicas-0            1/1     Running   0          141m
redis-replicas-1            1/1     Running   0          141m
redis-replicas-2            1/1     Running   0          140m

創建storestate組件，新建redis-state.yaml

[root@k8s-master dapr-demo]# cat redis-state.yaml
apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: statestore
  namespace: default
spec:
  type: state.redis
  version: v1
  metadata:
  - name: redisHost
    value: redis-master.default.svc.cluster.local:6379
  - name: redisPassword
    secretKeyRef:
      name: redis
      key: redis-password
  - name: actorStateStore
    value: "true"

新建pubsub組件

[root@k8s-master dapr-demo]# cat redis-pubsub.yaml
apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: pubsub
  namespace: default
spec:
  type: pubsub.redis
  version: v1
  metadata:
  - name: redisHost
    value: redis-master.default.svc.cluster.local:6379
  - name: redisPassword
    secretKeyRef:
      name: redis
      key: redis-password

apply statestore和pubsub

kubectl apply -f redis-state.yaml
kubectl apply -f redis-pubsub.yaml

驗證

[root@k8s-master dapr-demo]# kubectl get component.dapr.io
NAME         AGE
pubsub       135m
statestore   135m

10.分別為frontend和backend新建deployment

在 Kubernetes 集群中部署和運行啟用 Dapr 的應用程式非常簡單，只需向 deployment 方案添加一些annotations

[root@k8s-master dapr-demo]# cat frontend.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: frontend
  labels:
    app: frontend
spec:
  replicas: 1
  selector:
    matchLabels:
      app: frontend
  template:
    metadata:
      labels:
        app: frontend
      annotations:
        dapr.io/enabled: "true"
        dapr.io/app-id: "frontend"
        dapr.io/app-port: "5001"
    spec:
      imagePullSecrets:
      - name: ali-key
      containers:
      - name: frontend
        image: registry.cn-beijing.aliyuncs.com/chester-dapr/frontend:latest
        ports:
        - containerPort: 5001
        imagePullPolicy: Always

[root@k8s-master dapr-demo]# cat backend.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: backend
  labels:
    app: backend
spec:
  replicas: 1
  selector:
    matchLabels:
      app: backend
  template:
    metadata:
      labels:
        app: backend
      annotations:
        dapr.io/enabled: "true"
        dapr.io/app-id: "backend"
        dapr.io/app-port: "5000"
    spec:
      imagePullSecrets:
      - name: ali-key
      containers:
      - name: backend
        image: registry.cn-beijing.aliyuncs.com/chester-dapr/backend:latest
        ports:
        - containerPort: 5000
        imagePullPolicy: Always

分別apply backend和frontend

[root@k8s-master dapr-demo]# kubectl apply -f frontend.yaml
[root@k8s-master dapr-demo]# kubectl apply -f backend.yaml

查看pod

[root@k8s-master dapr-demo]# kubectl get pod
NAME                        READY   STATUS    RESTARTS   AGE
backend-7fff74f544-f6xms    2/2     Running   0          134m
frontend-5c479c9948-tmz5k   2/2     Running   0          99m
redis-master-0              1/1     Running   0          147m
redis-replicas-0            1/1     Running   0          147m
redis-replicas-1            1/1     Running   0          146m
redis-replicas-2            1/1     Running   0          146m

11.驗證

為frontend創建service

[root@k8s-master dapr-demo]# cat frontend-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: frontend-svc
spec:
  type: NodePort
  selector:
    app: frontend
  ports:
    - port: 5001
      targetPort: 5001
      nodePort: 31111

采用nodeport方式暴露31111埠，apply service