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gcp-cloud-run

gcp-cloud-run

github.com/davila7云与 DevOps33.0k235 次安装今天更新
代码仓库

关于 gcp-cloud-run

gcp-cloud-run 是在 Google Cloud Run 上部署容器化服务和事件驱动函数的模式指南,面向构建 Web API 与事件处理程序的开发者。内容还涵盖冷启动优化和运行配置中的常见陷阱。

主要功能

  1. 01容器化服务部署模式
  2. 02HTTP 与事件驱动函数模式
  3. 03冷启动延迟优化
  4. 04Cloud Build 部署示例
  5. 05运行陷阱与配置建议

适用场景

  1. 01部署 Web 应用或 API
  2. 02处理 Pub/Sub 与 Cloud Storage 事件
  3. 03降低面向用户服务的启动延迟
  4. 04检查 Cloud Run 资源与并发设置

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/davila7/claude-code-templates --skill gcp-cloud-run

安装后在 Claude Code 中输入/gcp-cloud-run确认已加载。

详细介绍

GCP Cloud Run

模式

Cloud Run 服务模式

在 Cloud Run 上运行的容器化 Web 服务

适用场景:['Web 应用和 API','需要使用任意运行时或库','包含多个端点的复杂服务','无状态的容器化工作负载']

```dockerfile
# Dockerfile - Multi-stage build for smaller image
FROM node:20-slim AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production

FROM node:20-slim
WORKDIR /app

# Copy only production dependencies
COPY --from=builder /app/node_modules ./node_modules
COPY src ./src
COPY package.json ./

# Cloud Run uses PORT env variable
ENV PORT=8080
EXPOSE 8080

# Run as non-root user
USER node

CMD ["node", "src/index.js"]
// src/index.js
const express = require('express');
const app = express();

app.use(express.json());

// Health check endpoint
app.get('/health', (req, res) => {
  res.status(200).send('OK');
});

// API routes
app.get('/api/items/:id', async (req, res) => {
  try {
    const item = await getItem(req.params.id);
    res.json(item);
  } catch (error) {
    console.error('Error:', error);
    res.status(500).json({ error: 'Internal server error' });
  }
});

// Graceful shutdown
process.on('SIGTERM', () => {
  console.log('SIGTERM received, shutting down gracefully');
  server.close(() => {
    console.log('Server closed');
    process.exit(0);
  });
});

const PORT = process.env.PORT || 8080;
const server = app.listen(PORT, () => {
  console.log(`Server listening on port ${PORT}`);
});
# cloudbuild.yaml
steps:
  # Build the container image
  - name: 'gcr.io/cloud-builders/docker'
    args: ['build', '-t', 'gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA', '.']

  # Push the container image
  - name: 'gcr.io/cloud-builders/docker'
    args: ['push', 'gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA']

  # Deploy to Cloud Run
  - name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'
    entrypoint: gcloud
    args:
      - 'run'
      - 'deploy'
      - 'my-service'
      - '--image=gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA'
      - '--region=us-central1'
      - '--platform=managed'
      - '--allow-unauthenticated'
      - '--memory=512Mi'
      - '--cpu=1'
      - '--min-instances=1'
      - '--max-instances=100'
     
Cloud Run Functions 模式

事件驱动函数(原 Cloud Functions)

适用场景:['简单的事件处理程序','Pub/Sub 消息处理','Cloud Storage 触发器','HTTP Webhook']

```javascript
// HTTP Function
// index.js
const functions = require('@google-cloud/functions-framework');

functions.http('helloHttp', (req, res) => {
  const name = req.query.name || req.body.name || 'World';
  res.send(`Hello, ${name}!`);
});
// Pub/Sub Function
const functions = require('@google-cloud/functions-framework');

functions.cloudEvent('processPubSub', (cloudEvent) => {
  // Decode Pub/Sub message
  const message = cloudEvent.data.message;
  const data = message.data
    ? JSON.parse(Buffer.from(message.data, 'base64').toString())
    : {};

  console.log('Received message:', data);

  // Process message
  processMessage(data);
});
// Cloud Storage Function
const functions = require('@google-cloud/functions-framework');

functions.cloudEvent('processStorageEvent', async (cloudEvent) => {
  const file = cloudEvent.data;

  console.log(`Event: ${cloudEvent.type}`);
  console.log(`Bucket: ${file.bucket}`);
  console.log(`File: ${file.name}`);

  if (cloudEvent.type === 'google.cloud.storage.object.v1.finalized') {
    await processUploadedFile(file.bucket, file.name);
  }
});
# Deploy HTTP function
gcloud functions deploy hello-http \
  --gen2 \
  --runtime nodejs20 \
  --trigger-http \
  --allow-unauthenticated \
  --region us-central1

# Deploy Pub/Sub function
gcloud functions deploy process-messages \
  --gen2 \
  --runtime nodejs20 \
  --trigger-topic my-topic \
  --region us-central1

# Deploy Cloud Storage function
gcloud functions deploy process-uploads \
  --gen2 \
  --runtime nodejs20 \
  --trigger-event-filters="type=google.cloud.storage.object.v1.finalized" \
  --trigger-event-filters="bucket=my-bucket" \
  --region us-central1

### Cold Start Optimization Pattern

Minimize cold start latency for Cloud Run

**When to use**: ['Latency-sensitive applications', 'User-facing APIs', 'High-traffic services']

```javascript
## 1. Enable Startup CPU Boost

```bash
gcloud run deploy my-service \
  --cpu-boost \
  --region us-central1

2. 设置最小实例数

gcloud run deploy my-service \
  --min-instances 1 \
  --region us-central1

3. 优化容器镜像

# Use distroless for minimal image
FROM node:20-slim AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production

FROM gcr.io/distroless/nodejs20-debian12
WORKDIR /app
COPY --from=builder /app/node_modules ./node_modules
COPY src ./src
CMD ["src/index.js"]

4. 延迟初始化大型依赖项

// Lazy load heavy libraries
let bigQueryClient = null;

function getBigQueryClient() {
  if (!bigQueryClient) {
    const { BigQuery } = require('@google-cloud/bigquery');
    bigQueryClient = new BigQuery();
  }
  return bigQueryClient;
}

// Only initialize when needed
app.get('/api/analytics', async (req, res) => {
  const client = getBigQueryClient();
  const results = await client.query({...});
  res.json(results);
});

5. 增加内存(获得更多 CPU)

# Higher memory = more CPU during startup
gcloud run deploy my-service \
  --memory 1Gi \
  --cpu 2 \
  --region us-central1

## Anti-Patterns

### ❌ CPU-Intensive Work Without Concurrency=1

**Why bad**: CPU is shared across concurrent requests. CPU-bound work
will starve other requests, causing timeouts.

### ❌ Writing Large Files to /tmp

**Why bad**: /tmp is an in-memory filesystem. Large files consume
your memory allocation and can cause OOM errors.

### ❌ Long-Running Background Tasks

**Why bad**: Cloud Run throttles CPU to near-zero when not handling
requests. Background tasks will be extremely slow or stall.

## ⚠️ Sharp Edges

| Issue | Severity | Solution |
|-------|----------|----------|
| Issue | high | ## Calculate memory including /tmp usage |
| Issue | high | ## Set appropriate concurrency |
| Issue | high | ## Enable CPU always allocated |
| Issue | medium | ## Configure connection pool with keep-alive |
| Issue | high | ## Enable startup CPU boost |
| Issue | medium | ## Explicitly set execution environment |
| Issue | medium | ## Set consistent timeouts |

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