deployment-patterns

Deployment Patterns

Production deployment workflows and CI/CD best practices.

When to Activate

• Setting up CI/CD pipelines
• Dockerizing an application
• Planning deployment strategy (blue-green, canary, rolling)
• Implementing health checks and readiness probes
• Preparing for a production release
• Configuring environment-specific settings

Deployment Strategies

Rolling Deployment (Default)

Replace instances gradually -- old and new versions run simultaneously during rollout.

Pros: Zero downtime, gradual rollout Cons: Two versions run simultaneously -- requires backward-compatible changes

Blue-Green Deployment

Run two identical environments. Switch traffic atomically.

Pros: Instant rollback (switch back to blue), clean cutover Cons: Requires 2x infrastructure during deployment

Canary Deployment

Route a small percentage of traffic to the new version first.

Pros: Catches issues with real traffic before full rollout Cons: Requires traffic splitting infrastructure, monitoring

Docker

Multi-Stage Dockerfile (Node.js)

# 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"]

Multi-Stage Dockerfile (Python/Django)

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

CMD ["gunicorn", "config.wsgi:application", "--bind", "0.0.0.0:8000", "--workers", "4"]

Docker Best Practices

• Use specific version tags (node:22-alpine, not node:latest)
• Multi-stage builds to minimize image size
• Run as non-root user
• Copy dependency files first (layer caching)
• Use .dockerignore to exclude node_modules, .git, tests
• Add HEALTHCHECK instruction

CI/CD Pipeline

GitHub Actions (Standard Pipeline)

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

  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/build-push-action@v5
        with:
          push: true
          tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
          cache-from: type=gha
          cache-to: type=gha,mode=max

Health Checks

Health Check Endpoint

app.get("/health", (req, res) => {
  res.status(200).json({ status: "ok" });
});

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(),
    uptime: process.uptime(),
    checks,
  });
});

Environment Configuration

Twelve-Factor App Pattern

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);

Rollback Strategy

# Docker/Kubernetes: point to previous image
kubectl rollout undo deployment/app

# Vercel: promote previous deployment
vercel rollback

Rollback Checklist

• Previous image/artifact is available and tagged
• Database migrations are backward-compatible
• Feature flags can disable new features without deploy
• Monitoring alerts configured for error rate spikes
• Rollback tested in staging before production release

Production Readiness Checklist

Application

• All tests pass (unit, integration, E2E)
• No hardcoded secrets in code or config files
• Error handling covers all edge cases
• Health check endpoint returns meaningful status

Infrastructure

• Docker image builds reproducibly (pinned versions)
• Environment variables documented and validated at startup
• Resource limits set (CPU, memory)
• SSL/TLS enabled on all endpoints

Monitoring

• Application metrics exported (request rate, latency, errors)
• Alerts configured for error rate > threshold
• Log aggregation set up
• Uptime monitoring on health endpoint

Security

• Dependencies scanned for CVEs
• CORS configured for allowed origins only
• Rate limiting enabled on public endpoints
• Authentication and authorization verified

Operations

• Rollback plan documented and tested
• Database migration tested against production-sized data
• On-call rotation and escalation path defined