WebAssembly 微服务与边缘计算实践

# 快速安装（Linux/macOS）
curl -sSf https://raw.githubusercontent.com/WasmEdge/WasmEdge/master/utils/install.sh | bash
source $HOME/.wasmedge/env

# 验证
wasmedge --version

# 运行简单的 WASM 模块
wasmedge hello.wasm

# 启用 wasi_nn 插件（用于 AI 推理）
# 支持 TensorFlow Lite、PyTorch、OpenVINO
wasmedge --dir .:. hello.wasm

// Rust 中使用 wasi_nn 进行推理
use wasi_nn;

pub fn classify_image(image_data: &[u8]) -> Result<String, String> {
    // 加载模型（在宿主预装载）
    let graph = wasi_nn::GraphBuilder::new(
        wasi_nn::GraphEncoding::TensorflowLite,
        wasi_nn::ExecutionTarget::Cpu,
    )
    .build_from_cache("mobilenet-v2")
    .map_err(|e| format!("模型加载失败: {:?}", e))?;

    let mut context = graph.init_execution_context()
        .map_err(|e| format!("初始化上下文失败: {:?}", e))?;

    // 设置输入张量
    context.set_input(0, wasi_nn::TensorType::F32, &[1, 224, 224, 3], image_data)
        .map_err(|e| format!("设置输入失败: {:?}", e))?;

    // 执行推理
    context.compute()
        .map_err(|e| format!("推理失败: {:?}", e))?;

    // 获取输出
    let mut output_buffer = vec![0u8; 1001 * 4]; // 1001 个类别
    context.get_output(0, &mut output_buffer)
        .map_err(|e| format!("获取输出失败: {:?}", e))?;

    // 解析 top-1 类别
    let scores: Vec<f32> = output_buffer.chunks_exact(4)
        .map(|b| f32::from_le_bytes([b[0], b[1], b[2], b[3]]))
        .collect();

    let top_class = scores.iter().enumerate()
        .max_by(|a, b| a.1.partial_cmp(b.1).unwrap())
        .map(|(i, score)| format!("类别 {}: 置信度 {:.2}%", i, score * 100.0))
        .unwrap_or_default();

    Ok(top_class)
}

# 安装 wasi_nn 的 Rust SDK
cargo add wasi_nn

# 编译为 WASM
cargo build --target wasm32-wasi --release

# 使用 WasmEdge 与预加载模型运行
wasmedge --nn-preload default:TensorFlowLite:CPU:model.tflite \
  target/wasm32-wasi/release/edge-ai.wasm

// worker.ts
import wasmModule from './image-processor.wasm';

export interface Env {
  // KV 存储、R2 对象存储等
}

export default {
  async fetch(request: Request, env: Env, ctx: ExecutionContext): Promise<Response> {
    const url = new URL(request.url);

    if (url.pathname === '/process') {
      // 实例化 WASM 模块
      const instance = await WebAssembly.instantiate(wasmModule, {
        env: {
          memory: new WebAssembly.Memory({ initial: 10 }),
        },
      });

      // 获取上传的图片数据
      const imageData = new Uint8Array(await request.arrayBuffer());
      const memory = instance.exports.memory as WebAssembly.Memory;

      // 写入 WASM 内存
      const ptr = (instance.exports.alloc as Function)(imageData.length);
      new Uint8Array(memory.buffer).set(imageData, ptr);

      // 调用 WASM 函数处理
      const resultPtr = (instance.exports.process_image as Function)(ptr, imageData.length);

      // 读取结果
      const resultLen = new DataView(memory.buffer).getUint32(resultPtr + 4, true);
      const resultData = new Uint8Array(memory.buffer, resultPtr, resultLen);

      return new Response(resultData, {
        headers: { 'Content-Type': 'image/webp' },
      });
    }

    return new Response('Not Found', { status: 404 });
  },
};

# 使用 Fastly CLI 部署 WASM 服务
fastly compute init --from https://github.com/fastly/compute-starter-kit-rust-default

# 编译
cargo build --release --target wasm32-wasi

# 部署（WASM 直接部署到全球 80+ 边缘节点）
fastly compute publish

apiVersion: apps/v1
kind: Deployment
metadata:
  name: wasm-edge-service
spec:
  replicas: 3
  selector:
    matchLabels:
      app: wasm-service
  template:
    metadata:
      labels:
        app: wasm-service
      annotations:
        dapr.io/enabled: "true"
        dapr.io/app-id: "wasm-processor"
        dapr.io/app-port: "8080"
    spec:
      runtimeClassName: crun-wasm
      containers:
      - name: app
        image: myregistry/wasm-image-processor:latest
        # 实际为 OCI 封装的 WASM 模块
        ports:
        - containerPort: 8080

# 最严格：只允许 CPU 计算，禁止一切 I/O
wasmedge --no-stdin --no-stdout --no-stderr compute.wasm

# 适度开放：只读 /data 目录
wasmedge --dir /data:/data:ro compute.wasm

# 网络隔离：仅允许访问特定域名
wasmedge --allow-host "api.example.com" fetch-service.wasm

# 限制内存和 CPU 时间
wasmedge --memory-limit 32MB --time-limit 5000ms compute.wasm