如何單機部署Dapr叢集
第十篇講過了K8S叢集下如何使用Dapr執行程式,但是很多人一直在問如何單機下進行Dapr的負載,這節課我們來聊聊如何單機進行Dapr的負載。
首先要說的是單機下,通過 dapr run --app-id xxxxx這個命令是沒辦法直接執行dapr叢集的,因為同一個app-id只能通過dapr run執行一次。這時候我們就需要利用docker來實現dapr的單機叢集部署。下面我們就來實現dapr的單機叢集部署。
專案拓撲
我們採用在docker內部為frontend部署一個例項,為backend部署兩個例項的方法,來實現backend的叢集化負載,另外需要為frontend和2個backend分別啟動一個sidecar容器。因此此例項一共需要部署6個容器。
專案實戰
首先在BackEnd中新增控制器IpController,並新增獲取backend例項ip的介面
[Route("api/[controller]")] [ApiController] public class IpController : ControllerBase { public ActionResult Get() { var ip = System.Net.NetworkInformation.NetworkInterface.GetAllNetworkInterfaces().Select(p => p.GetIPProperties()).SelectMany(p => p.UnicastAddresses) .Where(p => p.Address.AddressFamily == System.Net.Sockets.AddressFamily.InterNetwork && !System.Net.IPAddress.IsLoopback(p.Address)) .FirstOrDefault()?.Address.ToString(); return Ok(new List<string> { ip }); } }
然後需要在FrontEnd的DaprController中新增呼叫獲取backend ip的介面
[HttpGet("ip")] public async Task<ActionResult> GetIpAsync() { using var _daprClient = new DaprClientBuilder().Build(); var result = await _daprClient.InvokeMethodAsync<List<string>>(HttpMethod.Get, "backend", "api/Ip"); return Ok(result); }
這樣我們就可以通過訪問frontend的Dapr/ip來驗證backend是不是可以實現負載均衡。
Docker執行
在前面的課程裡我們已經為backend和frontend建好了Dockerfile,這裡不再談Dockerfile的編寫
backend
#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"]
frontend
#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"]
右鍵backend新增容器適配支援,新增docker-compose支援
修改docker-compose.yaml的內容
version: '3.4'
services:
backend:
image: ${DOCKER_REGISTRY-}backend
build:
context: .
dockerfile: BackEnd/Dockerfile
ports:
- "51000:50001"
daprbackend-dapr:
image: "daprio/daprd:latest"
command: [ "./daprd", "-app-id", "backend", "-app-port", "5000" ]
depends_on:
- backend
network_mode: "service:backend"
backend2:
image: ${DOCKER_REGISTRY-}backend2
build:
context: .
dockerfile: BackEnd/Dockerfile
ports:
- "53000:50001"
daprbackend-dapr2:
image: "daprio/daprd:latest"
command: [ "./daprd", "-app-id", "backend", "-app-port", "5000" ]
depends_on:
- backend2
network_mode: "service:backend2"
frontend:
image: ${DOCKER_REGISTRY-}frontend
build:
context: .
dockerfile: FrontEnd/Dockerfile
ports:
- "54000:50001"
- "5001:5001"
daprfrontend-dapr:
image: "daprio/daprd:latest"
command: [ "./daprd", "-app-id", "frontend", "-app-port", "5001" ]
depends_on:
- frontend
network_mode: "service:frontend"
其中我們公開了frontend和backend的50001預設GRPC通訊埠,給frontend暴露了一個5001埠,另外給backend和frontend分別啟動了一個daprd容器,通過depends_on和network_mode實現繫結。
執行並驗證
我們通過docker-compose up -d 來執行
docker-compose up -d
看到以下內容則啟動成功
Creating dapr-aspnetcore-demo_backend2_1 ... done
Creating dapr-aspnetcore-demo_backend_1 ... done
Creating dapr-aspnetcore-demo_frontend_1 ... done
Creating dapr-aspnetcore-demo_daprbackend-dapr_1 ... done
Creating dapr-aspnetcore-demo_daprbackend-dapr2_1 ... done
Creating dapr-aspnetcore-demo_daprfrontend-dapr_1 ... done
通過postman呼叫frontend的dapr/ip,發現返回的backend的ip不一致,已成功實現負載均衡