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.

Instance 1: v1 → v2  (update first)

Instance 2: v1        (still running v1)

Instance 3: v1        (still running v1)

Instance 1: v2

Instance 2: v1 → v2  (update second)

Instance 3: v1

Instance 1: v2

Instance 2: v2

Instance 3: v1 → v2  (update last)

Pros: Zero downtime, gradual rollout

Cons: Two versions run simultaneously — requires backward-compatible changes

Use when: Standard deployments, backward-compatible changes

Blue-Green Deployment

Run two identical environments. Switch traffic atomically.

Blue  (v1) ← traffic

Green (v2)   idle, running new version

# After verification:

Blue  (v1)   idle (becomes standby)

Green (v2) ← traffic

Pros: Instant rollback (switch back to blue), clean cutover

Cons: Requires 2x infrastructure during deployment

Use when: Critical services, zero-tolerance for issues

Canary Deployment

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

v1: 95% of traffic

v2:  5% of traffic  (canary)

# If metrics look good:

v1: 50% of traffic

v2: 50% of traffic

# Final:

v2: 100% of traffic

Pros: Catches issues with real traffic before full rollout

Cons: Requires traffic splitting infrastructure, monitoring

Use when: High-traffic services, risky changes, feature flags

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 (Go)

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"]

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

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"]

Docker Best Practices

# GOOD 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

- Set resource limits in docker-compose or k8s

# BAD practices

- Running as root

- Using :latest tags

- Copying entire repo in one COPY layer

- Installing dev dependencies in production image

- Storing secrets in image (use env vars or secrets manager)

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

      - 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 }}"

Pipeline Stages

PR opened:

  lint → typecheck → unit tests → integration tests → preview deploy

Merged to main:

  lint → typecheck → unit tests → integration tests → build image → deploy staging → smoke tests → deploy production

Health Checks

Health Check Endpoint

// 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" };

  }

}

Kubernetes Probes

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

Environment Configuration

Twelve-Factor App Pattern

# 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

Configuration Validation

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

Instant Rollback

# 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>

Rollback Checklist

• Previous image/artifact is available and tagged

• Database migrations are backward-compatible (no destructive changes)

• 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

Before any production deployment:

Application

• All tests pass (unit, integration, E2E)

• No hardcoded secrets in code or config files

• Error handling covers all edge cases

• Logging is structured (JSON) and does not contain PII

• 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)

• Horizontal scaling configured (min/max instances)

• SSL/TLS enabled on all endpoints

Monitoring

• Application metrics exported (request rate, latency, errors)

• Alerts configured for error rate > threshold

• Log aggregation set up (structured logs, searchable)

• 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

• Security headers set (CSP, HSTS, X-Frame-Options)

Operations

• Rollback plan documented and tested

• Database migration tested against production-sized data

• Runbook for common failure scenarios

• On-call rotation and escalation path defined