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部署工作流、CI/CD流水线模式、Docker容器化、健康检查、回滚策略以及Web应用程序的生产就绪检查清单。
| name | deployment-patterns |
| description | 部署工作流、CI/CD流水线模式、Docker容器化、健康检查、回滚策略以及Web应用程序的生产就绪检查清单。 |
| origin | ECC |
生产环境部署工作流和 CI/CD 最佳实践。
逐步替换实例——在发布过程中，新旧版本同时运行。
实例 1: v1 → v2 (首次更新)
实例 2: v1 (仍在运行 v1)
实例 3: v1 (仍在运行 v1)
实例 1: v2
实例 2: v1 → v2 (第二次更新)
实例 3: v1
实例 1: v2
实例 2: v2
实例 3: v1 → v2 (最后更新)
优点： 零停机时间，渐进式发布 缺点： 两个版本同时运行——需要向后兼容的更改 适用场景： 标准部署，向后兼容的更改
运行两个相同的环境。原子化地切换流量。
Blue (v1) ← 流量
Green (v2) 空闲，运行新版本
# 验证后：
Blue (v1) 空闲（转为备用状态）
Green (v2) ← 流量
优点： 即时回滚（切换回蓝色环境），切换干净利落 缺点： 部署期间需要双倍的基础设施 适用场景： 关键服务，对问题零容忍
首先将一小部分流量路由到新版本。
v1：95% 的流量
v2：5% 的流量（金丝雀）
# 如果指标表现良好：
v1：50% 的流量
v2：50% 的流量
# 最终：
v2：100% 的流量
优点： 在全量发布前，通过真实流量发现问题 缺点： 需要流量分割基础设施和监控 适用场景： 高流量服务，风险性更改，功能标志
# Stage 1: Install dependencies
FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production=false
# Stage 2: Build
FROM node:22-alpine AS builder
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
RUN npm run build
RUN npm prune --production
# Stage 3: Production image
FROM node:22-alpine AS runner
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001
USER appuser
COPY --from=builder --chown=appuser:appgroup /app/node_modules ./node_modules
COPY --from=builder --chown=appuser:appgroup /app/dist ./dist
COPY --from=builder --chown=appuser:appgroup /app/package.json ./
ENV NODE_ENV=production
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD wget --no-verbose --tries=1 --spider http://localhost:3000/health || exit 1
CMD ["node", "dist/server.js"]
FROM golang:1.22-alpine AS builder
WORKDIR /app
COPY go.mod go.sum ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 GOOS=linux go build -ldflags="-s -w" -o /server ./cmd/server
FROM alpine:3.19 AS runner
RUN apk --no-cache add ca-certificates
RUN adduser -D -u 1001 appuser
USER appuser
COPY --from=builder /server /server
EXPOSE 8080
HEALTHCHECK --interval=30s --timeout=3s CMD wget -qO- http://localhost:8080/health || exit 1
CMD ["/server"]
FROM python:3.12-slim AS builder
WORKDIR /app
RUN pip install --no-cache-dir uv
COPY requirements.txt .
RUN uv pip install --system --no-cache -r requirements.txt
FROM python:3.12-slim AS runner
WORKDIR /app
RUN useradd -r -u 1001 appuser
USER appuser
COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages
COPY --from=builder /usr/local/bin /usr/local/bin
COPY . .
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
HEALTHCHECK --interval=30s --timeout=3s CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health/')" || exit 1
CMD ["gunicorn", "config.wsgi:application", "--bind", "0.0.0.0:8000", "--workers", "4"]
# 良好实践
- 使用特定版本标签（node:22-alpine，而非 node:latest）
- 采用多阶段构建以最小化镜像体积
- 以非 root 用户身份运行
- 优先复制依赖文件（利用分层缓存）
- 使用 .dockerignore 排除 node_modules、.git、tests 等文件
- 添加 HEALTHCHECK 指令
- 在 docker-compose 或 k8s 中设置资源限制
# 不良实践
- 以 root 身份运行
- 使用 :latest 标签
- 在单个 COPY 层中复制整个仓库
- 在生产镜像中安装开发依赖
- 在镜像中存储密钥（应使用环境变量或密钥管理器）
name: CI/CD
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 22
cache: npm
- run: npm ci
- run: npm run lint
- run: npm run typecheck
- run: npm test -- --coverage
- uses: actions/upload-artifact@v4
if: always()
with:
name: coverage
path: coverage/
build:
needs: test
runs-on: ubuntu-latest
if: github.ref == 'refs/heads/main'
steps:
- uses: actions/checkout@v4
- uses: docker/setup-buildx-action@v3
- uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- uses: docker/build-push-action@v5
with:
push: true
tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
cache-from: type=gha
cache-to: type=gha,mode=max
deploy:
needs: build
runs-on: ubuntu-latest
if: github.ref == 'refs/heads/main'
environment: production
steps:
- name: Deploy to production
run: |
# Platform-specific deployment command
# Railway: railway up
# Vercel: vercel --prod
# K8s: kubectl set image deployment/app app=ghcr.io/${{ github.repository }}:${{ github.sha }}
echo "Deploying ${{ github.sha }}"
PR 已开启：
lint → typecheck → 单元测试 → 集成测试 → 预览部署
合并到 main：
lint → typecheck → 单元测试 → 集成测试 → 构建镜像 → 部署到 staging → 冒烟测试 → 部署到 production
// Simple health check
app.get("/health", (req, res) => {
res.status(200).json({ status: "ok" });
});
// Detailed health check (for internal monitoring)
app.get("/health/detailed", async (req, res) => {
const checks = {
database: await checkDatabase(),
redis: await checkRedis(),
externalApi: await checkExternalApi(),
};
const allHealthy = Object.values(checks).every(c => c.status === "ok");
res.status(allHealthy ? 200 : 503).json({
status: allHealthy ? "ok" : "degraded",
timestamp: new Date().toISOString(),
version: process.env.APP_VERSION || "unknown",
uptime: process.uptime(),
checks,
});
});
async function checkDatabase(): Promise<HealthCheck> {
try {
await db.query("SELECT 1");
return { status: "ok", latency_ms: 2 };
} catch (err) {
return { status: "error", message: "Database unreachable" };
}
}
livenessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 10
periodSeconds: 30
failureThreshold: 3
readinessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 5
periodSeconds: 10
failureThreshold: 2
startupProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 0
periodSeconds: 5
failureThreshold: 30 # 30 * 5s = 150s max startup time
# All config via environment variables — never in code
DATABASE_URL=postgres://user:pass@host:5432/db
REDIS_URL=redis://host:6379/0
API_KEY=${API_KEY} # injected by secrets manager
LOG_LEVEL=info
PORT=3000
# Environment-specific behavior
NODE_ENV=production # or staging, development
APP_ENV=production # explicit app environment
import { z } from "zod";
const envSchema = z.object({
NODE_ENV: z.enum(["development", "staging", "production"]),
PORT: z.coerce.number().default(3000),
DATABASE_URL: z.string().url(),
REDIS_URL: z.string().url(),
JWT_SECRET: z.string().min(32),
LOG_LEVEL: z.enum(["debug", "info", "warn", "error"]).default("info"),
});
// Validate at startup — fail fast if config is wrong
export const env = envSchema.parse(process.env);
# Docker/Kubernetes: point to previous image
kubectl rollout undo deployment/app
# Vercel: promote previous deployment
vercel rollback
# Railway: redeploy previous commit
railway up --commit <previous-sha>
# Database: rollback migration (if reversible)
npx prisma migrate resolve --rolled-back <migration-name>
在任何生产部署之前：
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
Orchestrate bootstrapping a working MVP from a design or spec document — ingest the doc, plan thin vertical slices, scaffold the first end-to-end slice, then TDD-implement, review, and gated commit. Use to turn an SDD/PRD into a running starting point.
Orchestrate altering an existing, working feature to new desired behavior — update its tests to the new spec, change the implementation to match, review, and gated commit. Use when behavior is not broken but should be different.
Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
Shared orchestration engine for the orch-* skill family. Defines the gated Research-Plan-TDD-Review-Commit pipeline, the size classifier, the agent map, and the two human gates that the orch-* operation skills delegate to. Not usually invoked directly.