CI/CD Setup for Websites via GitHub Actions

CI/CD Setup for Websites via GitHub Actions

Every second production release fails due to human error: a file wasn't uploaded, a config wasn't updated, tests were skipped. CI/CD eliminates these risks. With 5+ years of experience, we've set up over 50 pipelines for projects ranging from landing pages to high-load SaaS. GitHub Actions is our go-to for fast automation. Order a setup and get a ready pipeline in 1–5 days.

Why GitHub Actions?

Unlike Jenkins or GitLab CI, there's no need to spin up a separate server, configure webhooks, or install plugins. Everything is managed via YAML files in the repository. For public projects, it's free indefinitely. For private ones, you get 2000 minutes per month on the free tier—enough for 400–1000 deploys. If you exceed that, attach a self-hosted runner on your server—minutes are not consumed. GitHub Actions is 2x faster to set up than GitLab CI and requires no server unlike Jenkins.

How to Speed Up Builds with Caching

Dependency caching is the main accelerator. actions/setup-node with cache: 'npm' automatically caches ~/.npm. For PHP, use actions/cache with a key based on composer.lock. Example for Composer:

- uses: actions/cache@v4
  with:
    path: vendor
    key: composer-${{ hashFiles('composer.lock') }}

After cache warm-up, run time drops from 3–5 minutes to 60–90 seconds. Matrix builds (multiple Node.js versions) run in parallel and are cached separately. The team saves 3 hours per week, which at average DevOps rates amounts to up to $350 per month.

Workflow Structure

A minimal workflow for a Node.js site with SSH deployment:

name: Deploy

on:
  push:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-22.04
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'
      - run: npm ci
      - run: npm test

  build:
    needs: test
    runs-on: ubuntu-22.04
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'
      - run: npm ci
      - run: npm run build
      - uses: actions/upload-artifact@v4
        with:
          name: dist
          path: dist/

  deploy:
    needs: build
    runs-on: ubuntu-22.04
    environment: production
    steps:
      - uses: actions/download-artifact@v4
        with:
          name: dist
          path: dist/
      - name: Deploy via rsync
        uses: burnett01/[email protected]
        with:
          switches: -avzr --delete
          path: dist/
          remote_path: /var/www/mysite
          remote_host: ${{ secrets.DEPLOY_HOST }}
          remote_user: deploy
          remote_key: ${{ secrets.DEPLOY_KEY }}

Three jobs: test, build, deploy. If tests fail, build doesn't run. We use artifacts to pass built files.

Secret Management

All sensitive data goes into Settings → Secrets and variables → Actions. No keys or passwords end up in code. For different environments, use Environments—each set of secrets is isolated. Production deployment can be protected by manual approval.

- name: Configure .env
  run: |
    echo "DATABASE_URL=${{ secrets.DATABASE_URL }}" >> .env
    echo "APP_KEY=${{ secrets.APP_KEY }}" >> .env

Docker Build and Registry Push

If deployment uses containers:

- name: Build and push Docker image
  uses: docker/build-push-action@v5
  with:
    context: .
    push: true
    tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
    cache-from: type=gha
    cache-to: type=gha,mode=max

GitHub Container Registry is free, authentication via built-in GITHUB_TOKEN.

Status Notifications

- name: Notify Telegram on failure
  if: failure()
  uses: appleboy/telegram-action@master
  with:
    to: ${{ secrets.TELEGRAM_CHAT_ID }}
    token: ${{ secrets.TELEGRAM_TOKEN }}
    message: "❌ Deploy failed: ${{ github.repository }} @ ${{ github.sha }}"

if: failure() runs only on failure. For start and success notifications, use if: always().

Step-by-Step CI/CD Setup Guide

1. Create a .github/workflows directory in the repo root.
2. Add a deploy.yml file with the configuration (example above).
3. Set up secrets in Settings → Secrets and variables → Actions.
4. Push changes to the main branch—the workflow triggers automatically.
5. Check the status in the Actions tab of the repository.
6. On success, deployment is done. On failure, you'll get a notification.

Comparison: GitHub Actions vs Other CI/CD

GitHub Actions is easier to set up than Jenkins and requires no dedicated server. For most web projects, it's the optimal choice.

Setup Stages and Timeline

What's Included

We provide the full CI/CD setup cycle:

• Analysis of the current deployment process and project architecture
• Creation of a YAML workflow with tests, build, and deployment
• Configuration of secrets and environments in the repository
• Build speed optimization (caching, matrices)
• Integration of notifications (Telegram, Slack, email)
• Workflow documentation and team instructions
• Training developers on pipeline usage

name: Deploy
on: [push]
jobs:
  test:
    runs-on: ubuntu-22.04
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'
      - run: npm ci
      - run: npm test
  build:
    needs: test
    runs-on: ubuntu-22.04
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'
      - run: npm ci
      - run: npm run build
      - name: Build Docker image
        run: docker build -t myapp .
      - name: Push to registry
        run: docker push ghcr.io/myorg/myapp:latest
  deploy:
    needs: build
    runs-on: ubuntu-22.04
    steps:
      - name: Deploy via SSH
        uses: appleboy/[email protected]
        with:
          host: ${{ secrets.DEPLOY_HOST }}
          username: deploy
          key: ${{ secrets.DEPLOY_KEY }}
          script: |
            docker pull ghcr.io/myorg/myapp:latest
            docker-compose up -d

Our Results and Experience

For 5+ years, we've set up CI/CD for projects of varying complexity—from landing pages to high-load SaaS. Over 50 implemented pipelines with guaranteed stable operation. Each case is documented so the client's team can maintain and extend the pipeline independently. Downtime costs due to deployment errors can reach $1,400 per day—CI/CD eliminates that.

Timeline and Pricing

• Basic workflow (test + SSH deploy) — 1–2 days
• Full pipeline (matrices, Docker, notifications, manual approvals) — 3–5 days

Cost is calculated individually based on complexity and stack. Contact us for a consultation—we'll find the optimal solution for your project.

We regularly encounter a situation: "The site is not opening" at 3 a.m. — and it turns out that the VPS disk is full because nginx logs haven't been rotated for six months. Or the server went down under load on the day of an advertising campaign launch because the shared hosting had a limit of 50 concurrent connections. Setting up hosting and deployment is not about "where it's cheaper" but about what happens when something goes wrong. Our team helps avoid such incidents by designing infrastructure that accounts for real load patterns.

When to choose Vercel and Netlify?

Vercel is built for Next.js — deploy in one push, preview deployments for every PR, automatic CDN, Edge Functions, ISR without configuration. For frontend projects and JAMstack, it's the optimal choice: no operational overhead, time-to-deploy measured in minutes.

Real limitations: Vercel Serverless Functions run in us-east-1 by default (latency for Europe +80–100ms), Function timeout 300 seconds on Pro, Bandwidth 1TB/month on Pro. For heavy backend, you need workers or a separate server.

Netlify is closer to static sites and Edge Functions based on Deno Deploy. Build minutes are the main limitation on the free tier.

Why is Docker the foundation of predictable deployment?

"It works on my machine" — classic. Docker solves this through environment containerization. But a bad Dockerfile creates new problems.

A typical mistake: copying everything into the image without .dockerignore, resulting in an 800MB image instead of 80MB. node_modules inside the image weighs as much. Correct approach: multi-stage build.

FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build

FROM node:20-alpine AS runner
WORKDIR /app
COPY --from=builder /app/.next ./.next
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/package.json ./package.json
EXPOSE 3000
CMD ["npm", "start"]

Final image: 180MB instead of 1.2GB. CI build time is reduced due to layer caching — if package.json hasn't changed, the layer with npm ci is taken from cache.

Docker Compose for local development and simple production scenarios: application + PostgreSQL + Redis in one configuration. For production on a single server, it's a perfectly viable option if there's no requirement for horizontal scaling.

More about containerization — Wikipedia: Docker.

How to set up Nginx as a reverse proxy?

Nginx in front of the application is standard for VPS and dedicated servers. Main functions: SSL termination, gzip, static files, rate limiting, upstream load balancing.

A configuration often done incorrectly: worker_processes auto — number of processes equals CPU count. worker_connections 1024 — that's 1024 per worker process. With 4 CPUs and 1024 connections = 4096 concurrent connections. For a high-traffic site, you need worker_connections 4096 and set keepalive_timeout 65.

For static assets with hash in the filename:

location ~* \.(js|css|woff2|png|webp)$ {
    expires 1y;
    add_header Cache-Control "public, immutable";
}

immutable tells the browser: don't revalidate this file even on hard refresh. This only works correctly with content-hashed filenames (which Vite/webpack do by default). Documentation — Wikipedia: Nginx.

AWS: flexibility and complexity

EC2 + Auto Scaling Group — classic for horizontal scaling. AMI with pre-installed application, Launch Template, ASG with min/desired/max instances, Application Load Balancer. When CPU > 70% for 3 minutes — scale out, when CPU < 30% for 15 minutes — scale in. Health check via ALB removes unhealthy instances from rotation.

ECS Fargate — containers without managing EC2. Deploy a Docker image, specify CPU/memory (512 CPU units = 0.5 vCPU, from 512MB memory), Fargate launches it. More expensive than Lambda, but no cold start and no timeout limitations. Suitable for long-running processes, WebSocket servers, heavy workers.

RDS for PostgreSQL with Multi-AZ: automatic failover in 1–2 minutes when primary fails. Read Replicas for scaling reads. RDS Proxy for connection pooling — Lambda functions cannot hold long-term connections, the proxy buffers this.

Kubernetes: when it is justified

K8s adds significant operational complexity. Justified when: multiple teams deploy independent services, fine-grained resource allocation per service is needed, canary deployments and blue/green without downtime are required.

AWS EKS, GKE, or managed k8s from Hetzner (cheaper). Helm charts for standard services. Horizontal Pod Autoscaler based on CPU and custom metrics (RPS via Prometheus).

For most startups and medium-sized projects, Kubernetes is overkill. ECS or Fly.io provide 80% of the capabilities with 20% of the operational complexity.

Monitoring and alerting

A server without monitoring is waiting for an incident. Minimal stack: Prometheus + Grafana (or Grafana Cloud for managed), alerting on disk > 80%, memory > 85%, CPU > 90% over 5 minutes, error rate > 1%. Uptime via Better Uptime or Upptime (self-hosted).

Logs: Loki + Grafana or CloudWatch Logs Insights. Structured JSON logs (winston, pino) are mandatory — otherwise, log searching becomes a pain.

What is included in hosting setup

• Audit of current infrastructure and load profiling
• Selection of target architecture (VPS, AWS, serverless, Kubernetes)
• Setting up CI/CD pipeline (GitHub Actions, GitLab CI) with automatic deployment
• IaC via Terraform or Pulumi (infrastructure as code)
• Configuration of Nginx, SSL certificates, HTTP/2, brotli
• Monitoring and alerting (Prometheus + Grafana, PagerDuty)
• Documentation of runbooks and team training

Additionally, contact us if you need migration from current hosting or integration with external services.

Work process

1. Audit of current infrastructure (2–5 days)
2. Selection of target architecture with load and budget justification (1–3 days)
3. Setting up CI/CD pipeline (GitHub Actions, GitLab CI) (2–5 days)
4. IaC via Terraform or Pulumi (3–10 days)
5. Setting up monitoring and alerting (2–5 days)
6. Documentation of runbooks and team training (1–3 days)

Our experience — 7 years on the market, over 50 projects, guarantee of operability after deployment.

Timeline

• Basic deployment on VPS with Docker + Nginx + CI/CD: 1–2 weeks.
• Setting up AWS infrastructure with Auto Scaling, RDS, CDN: 3–6 weeks.
• Migration to EKS from scratch: 6–12 weeks.
• Setting up Vercel/Netlify for JAMstack: 3–5 days.

The cost is calculated individually depending on complexity and scope of work. Get a consultation — we'll evaluate your architecture in one day.