Website Migration to New Hosting with Minimal Downtime

Imagine you decide to move to a new server to boost performance. But something goes wrong during the transfer — a corrupted database dump, files not copied, the site goes down for a day. This is a typical situation for those attempting migration for the first time. Our engineers (5+ years experience) have performed 200+ successful migrations with a 99.9% success rate. Our process guarantees downtime under 15 minutes — we use parallel operation and preliminary testing. In detail: before switching DNS, we spin up a full copy on the new server, check all scenarios (authorization, payment, forms). Only then do we change the A-record with a TTL of 300 seconds. This approach eliminates data loss and long downtime. We also keep both servers active for up to 72 hours after the switch — in case of rollback.

What Are the Risks of Changing Hosting?

Incorrect hosting transfer leads to:

• Web server configuration errors (incompatible PHP versions, modules)
• Data loss due to incomplete DB dump or corrupted archive
• Long downtime (12+ hours instead of 15 minutes)
• Broken links in content (absolute paths left from the old server)

We solve these problems step by step with redundant checks.

How to Minimize Downtime During Migration?

The key principle is parallel operation (hot standby). We perform the migration on the new server while the old one serves visitors. After full verification via hosts file, we switch DNS with a low TTL (300 s). Average downtime is 5–15 minutes. Our method reduces downtime by 95% compared to traditional migration.

Comparison of Data Transfer Methods

rsync is 5–10 times faster than FTP for volumes >10 GB according to rsync documentation. We use rsync for primary copy and tar for backup archive. Additionally, we use pigz for parallel compression — speeding up the process by 30%.

What Is Included in the Work?

• File transfer (rsync with exclusion of .git, cache)
• Database migration (dump + restore on the new DBMS version)
• Web server (Nginx/Apache) and environment (PHP, Node.js, Redis) setup
• SSL certificate installation (Let's Encrypt or your own)
• Cron, queue workers, environment variables configuration
• Verification via /etc/hosts before DNS switch
• 72-hour monitoring after the switch

Deliverables

• Detailed migration report
• Server access credentials
• 72-hour post-migration support
• 30-minute training session on new server management

A typical seamless migration costs between $300 and $800 depending on complexity, saving you up to $500 in potential lost revenue from downtime.

What Are Typical Mistakes in Self-Migration?

Developers often forget:

• To sync .env and storage permissions (chmod 775)
• To export the database with --add-drop-table and --complete-insert flags for InnoDB
• To check redirects (http→https, www→non-www) on the new server
• To update IP in CDN settings (Cloudflare, Vercel)

Migration Stages: Step-by-step

Step 1: Prepare the new server

Install the required stack (LEMP, Node.js, etc.):

# Install LEMP stack on Ubuntu 22.04
sudo apt update && sudo apt upgrade -y
sudo apt install -y nginx mysql-server php8.2-fpm php8.2-mysql php8.2-gd \
  php8.2-curl php8.2-zip php8.2-mbstring php8.2-xml php8.2-intl redis-server

# For Node.js projects
curl -fsSL https://deb.nodesource.com/setup_20.x | sudo -E bash -
sudo apt install -y nodejs

Step 2: Transfer files and database

First copy the database, then the files — to minimize data discrepancy:

# MySQL: dump and restore
mysqldump -u root -p mysite_db > /tmp/mysite_db.sql
scp /tmp/mysite_db.sql user@new-server:/tmp/
ssh user@new-server "mysql -u root -p new_db < /tmp/mysite_db.sql"

# rsync files (excluding .git)
rsync -avz --progress --exclude='.git' \
  -e "ssh -p 22" \
  user@old-server:/var/www/mysite/ \
  user@new-server:/var/www/mysite/

For PostgreSQL, use pg_dump/psql. Important: for large databases (50+ GB), use streaming dump via pg_dump -Fc and pg_restore -j 4 for speed.

Step 3: Configure the new server

• Create virtual host (Nginx/Apache)
• Transfer .env with current data
• Install SSL certificate
• Set permissions on directories: storage, cache, uploads
• Configure cron and queue workers

Step 4: Verify via hosts file

Before DNS switch, test the site locally:

# On local machine, add to /etc/hosts (or C:\Windows\System32\drivers\etc\hosts)
NEW_SERVER_IP  mysite.com www.mysite.com

Open the site in a browser, check forms, authorization, payment scenarios. Perform thorough site testing to ensure all functions work, including critical flows like payments and email sends.

Step 5: Perform DNS switching

A day before the switch, lower TTL to 300 seconds. At the switch moment, change the A-record to the new server's IP. After propagation, revert TTL to 3600+.

# Monitor DNS propagation
watch -n 5 "dig @8.8.8.8 mysite.com A +short"
watch -n 5 "dig @1.1.1.1 mysite.com A +short"

Step 6: Post-migration monitoring

Keep the old server active for 48–72 hours. Perform:

• curl availability checks
• SSL certificate verification (openssl)
• Redirect checks (http→https, www→non-www)

curl -I https://mysite.com
echo | openssl s_client -connect mysite.com:443 2>/dev/null | grep "Verify return code"
curl -I http://mysite.com  # expect 301

Importance of Testing on the New Server Before DNS Switch

If you switch DNS without prior testing, you may end up with a broken site: forms not working, broken CSS, data loss. We always test via hosts file to ensure the new server handles all scenarios, including critical ones like payments, registration, and email sends.

Timeline and Pricing

A standard migration takes from 4 to 16 hours depending on data volume, number of databases, and environment specifics. Pricing is individual — contact us to evaluate your project. We work with hosting of any complexity: from shared to dedicated. Our no data loss migration guarantee ensures zero data loss, and we offer a migration to VPS service with full support.

Order a turnkey migration — get a seamless transfer with a full operability guarantee. Contact us for a consultation.

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.