Hetzner Cloud Deployment: Terraform, CI/CD, Docker Swarm

You bought a VPS on Hetzner, installed Ubuntu, and deployed your site via manual scp. A month later, you realize: code updates are a nightmare, Nginx isn't tuned for high load, and your SSL certificate expired on a Friday evening. Each release turns into hours of stress, clients complain about slow loading. We set up deployment so everything runs automatically: press a button in GitHub — the site updates in a minute, monitoring alerts you on failure. Saving time and nerves is our priority. Contact us for a free consultation — we'll tell you how to accelerate your release cycle.

Problems We Solve

• Manual deployment via FTP/SCP — slow, error-prone, no change history. We replace it with Git-based CI/CD with rollback capabilities.
• Nginx without caching and gzip — high TTFB, Core Web Vitals failure. We optimize LCP and CLS.
• SSL certificate expires — we set up Let's Encrypt with auto-renewal via systemd timer.
• No monitoring — you don't know about server downtime until morning. We install Prometheus + Node Exporter + Alertmanager.
• Scaling — a single server can't handle the load. We use Docker Swarm across multiple VPS with Load Balancer.

How We Do It

We use infrastructure as code: all configs are in Git. Terraform creates servers, firewall, DNS, Object Storage. Packer builds images. Ansible configures software. GitHub Actions handles deployment after every push.

Real case: a marketplace client with 50,000 products. Previously, deployment took 2 hours via manual rsync. We built a pipeline:

1. GitHub Actions builds Docker images.
2. Uploads them to a registry (GitHub Container Registry).
3. Via SSH, runs docker stack deploy on a Swarm cluster of 3 nodes.

Release time dropped to 2 minutes. Rollback is even faster: git revert and a new push.

How the CI/CD Pipeline Works

Every push to the main branch triggers a build, tests (if any), and deployment to staging. After manual confirmation, deployment to production. All steps are defined in a YAML file in the repository, so changes are tracked and reproducible.

Terraform for Infrastructure

# main.tf (beginning)
terraform {
  required_providers {
    hcloud = {
      source  = "hetznercloud/hcloud"
      version = "~> 1.44"
    }
  }
}

provider "hcloud" {
  token = var.hcloud_token
}

resource "hcloud_server" "app" {
  name        = "myapp-prod"
  image       = "ubuntu-22.04"
  server_type = "cpx21"
  location    = "nbg1"
  ssh_keys    = [hcloud_ssh_key.default.id]
  user_data   = file("cloud-init.yaml")

  labels = {
    env  = "production"
    app  = "myapp"
  }
}

resource "hcloud_firewall" "app" {
  name = "myapp-firewall"

  rule {
    direction = "in"
    protocol  = "tcp"
    port      = "22"
    source_ips = ["10.0.0.0/8"]
  }

  rule {
    direction = "in"
    protocol  = "tcp"
    port      = "80"
    source_ips = ["0.0.0.0/0", "::/0"]
  }

  rule {
    direction = "in"
    protocol  = "tcp"
    port      = "443"
    source_ips = ["0.0.0.0/0", "::/0"]
  }
}

resource "hcloud_load_balancer" "lb" {
  name               = "myapp-lb"
  load_balancer_type = "lb11"
  location           = "nbg1"
}

resource "hcloud_load_balancer_target" "server" {
  type             = "server"
  load_balancer_id = hcloud_load_balancer.lb.id
  server_id        = hcloud_server.app.id
}

GitHub Actions for CI/CD

name: Deploy to Hetzner

on:
  push:
    branches: [ main ]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Deploy via SSH
        uses: appleboy/ssh-action@v1
        with:
          host: ${{ secrets.HETZNER_IP }}
          username: deploy
          key: ${{ secrets.SSH_PRIVATE_KEY }}
          script: |
            set -e
            cd /var/www/myapp
            git fetch origin main
            git reset --hard origin/main
            composer install --no-dev --optimize-autoloader
            npm ci --omit=dev
            npm run build
            php artisan migrate --force
            php artisan optimize
            sudo systemctl reload php8.3-fpm nginx
            php artisan queue:restart

Hetzner Object Storage for Static Files

aws configure set aws_access_key_id $HETZNER_S3_KEY
aws configure set aws_secret_access_key $HETZNER_S3_SECRET
aws configure set region eu-central

aws --endpoint-url https://fsn1.your-objectstorage.com s3 mb s3://myapp-assets

aws --endpoint-url https://fsn1.your-objectstorage.com s3 sync ./dist/assets s3://myapp-assets/assets --cache-control "public, max-age=31536000, immutable"

What Is Docker Swarm and Why Do You Need It?

Docker Swarm is a native Docker clusterizer that combines multiple servers into a single compute space. It provides automatic container distribution, load balancing, and failure recovery. For projects that need horizontal scaling and fault tolerance without the complexity of Kubernetes, Swarm is the optimal choice. Swarm is up to 5x simpler to configure and 3x lighter than Kubernetes, making it ideal for small to medium workloads.

Docker Swarm Cluster

# Initialize on the first server
ssh server1 "docker swarm init"

# Get the token
JOIN_TOKEN=$(ssh server1 "docker swarm join-token worker -q")

# Add worker nodes
ssh server2 "docker swarm join --token $JOIN_TOKEN server1:2377"
ssh server3 "docker swarm join --token $JOIN_TOKEN server1:2377"

# Deploy a stack
docker -H ssh://deploy@server1 stack deploy -c docker-compose.prod.yml myapp

Process of Work

1. Analysis — study current infrastructure, load requirements, and budget.
2. Design — choose server types, load balancing scheme, software stack.
3. Implementation — write Terraform, Ansible, CI/CD, monitoring.
4. Testing — verify deployment on a staging server, perform load testing.
5. Deployment — move to production, configure alerts and backups.

Estimated Timelines

Cost is calculated individually — contact us for an estimate.

Typical Problems and Solutions

What Is Included in the Work

• Comprehensive documentation of the scheme and configurations.
• Server and admin panel access.
• Training for your team (1–2 hour call).
• Support for 1 month after delivery.
• Detailed configuration as code (Terraform, Ansible) in your git repository.

How to Set Up Deployment on Hetzner in 1 Day?

If your site is already running on a single server, we add:

1. Automatic SSL (Certbot systemd timer).
2. GitHub Actions with a fast deployment script.
3. Uptime Kuma monitoring on a separate VPS.
4. Daily database backup to Object Storage.

All of this is guaranteed to work. Over the years, we have completed more than 50 projects on Hetzner — from small landing pages to high-load marketplaces. Order a turnkey setup — we'll select the optimal configuration and draw a migration roadmap.

Why Choose Hetzner for Production?

• GDPR-compliant data centers in Europe.
• Price 3–5 times lower than AWS/GCP with similar performance.
• High reliability: 99.9% uptime per SLA.
• Simple API and CLI for automation.

Get a consultation — we'll tell you how to optimize your current deployment.

Note: All prices are estimates; final cost depends on scope.

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.