運算服務選擇（VM vs Container vs Serverless）

// Azure Functions（Serverless）— 事件驅動
public class OrderFunctions
{
    // HTTP 觸發
    [Function("ProcessOrder")]
    public async Task<IActionResult> ProcessOrder(
        [HttpTrigger(AuthorizationLevel.Function, "post")] HttpRequest req)
    {
        var order = await req.ReadFromJsonAsync<OrderDto>();
        await _orderService.ProcessAsync(order!);
        return new OkObjectResult(new { status = "processed" });
    }
 
    // Queue 觸發 — 有新訊息就自動執行
    [Function("SendOrderEmail")]
    public async Task SendOrderEmail(
        [QueueTrigger("order-emails")] OrderEmailMessage message)
    {
        await _emailService.SendAsync(message.Email, message.OrderId);
    }
 
    // Timer 觸發 — 排程執行
    [Function("DailyReport")]
    public async Task DailyReport(
        [TimerTrigger("0 0 8 * * *")] TimerInfo timer) // 每天早上 8 點
    {
        await _reportService.GenerateDailyAsync();
    }
}

// AWS Lambda（Serverless）— 事件驅動
import { APIGatewayProxyHandler, SQSHandler } from "aws-lambda";
 
// HTTP 觸發
export const processOrder: APIGatewayProxyHandler = async (event) => {
  const order = JSON.parse(event.body || "{}");
  await orderService.process(order);
  return {
    statusCode: 200,
    body: JSON.stringify({ status: "processed" }),
  };
};
 
// SQS 觸發 — Queue 有新訊息就執行
export const sendEmail: SQSHandler = async (event) => {
  for (const record of event.Records) {
    const message = JSON.parse(record.body);
    await emailService.send(message.email, message.orderId);
  }
};
 
// Kubernetes Deployment（Container）— 長時間運行的 API
// deployment.yaml 搭配 TypeScript Express 應用
// 適合持續運行的核心 API 服務

# Azure Functions（Python）
import azure.functions as func
 
app = func.FunctionApp()
 
# HTTP 觸發
@app.function_name("ProcessOrder")
@app.route(route="orders", methods=["POST"])
async def process_order(req: func.HttpRequest) -> func.HttpResponse:
    order = req.get_json()
    await order_service.process(order)
    return func.HttpResponse('{"status": "processed"}', status_code=200)
 
# Blob 觸發 — 有新檔案上傳就執行
@app.function_name("ProcessUpload")
@app.blob_trigger(arg_name="blob", path="uploads/{name}", connection="StorageConn")
async def process_upload(blob: func.InputStream):
    content = blob.read()
    await file_service.process(blob.name, content)
 
# Google Cloud Run（Managed Container）
# 不需要管 K8s，直接部署 Docker Image
# gcloud run deploy myapi --image gcr.io/myproject/myapi:v1