Deployment Automation

deployment-automation

One-command deployment to Vercel, Railway, Netlify, and Heroku

Overview

Automate deployments to popular hosting platforms with a single command. Detects platform configuration, installs required CLIs, and handles deployment workflow automatically.

Time Saved: ~30 minutes per deployment
Complexity: Medium
Prerequisites: Node.js, npm, git

When to Use

• Deploying web applications to production
• Setting up CI/CD pipelines
• Switching between hosting platforms
• Automating deployment workflows
• Teaching deployment best practices

Supported Platforms

1. Vercel - Next.js, React, static sites
2. Railway - Full-stack apps, databases, backend
3. Netlify - Static sites, JAMstack
4. Heroku - Traditional web apps, APIs

Quick Start

1. Deploy a Project

python3 /home/ubuntu/skills/deployment-automation/scripts/deploy.py /path/to/project

2. Deploy Preview/Staging

python3 /home/ubuntu/skills/deployment-automation/scripts/deploy.py /path/to/project --preview

How It Works

Phase 1: Detection

• Scans project for platform configuration files
• Identifies: vercel.json, railway.toml, netlify.toml, Procfile
• Checks package.json for custom deploy scripts

Phase 2: CLI Setup

• Checks if platform CLI is installed
• Offers to install if missing
• Verifies authentication

Phase 3: Deployment

• Runs platform-specific deploy command
• Handles production vs preview modes
• Reports success/failure

Usage Examples

Example 1: Deploy Next.js App to Vercel

# Project has vercel.json
python3 /home/ubuntu/skills/deployment-automation/scripts/deploy.py ~/my-nextjs-app

# Output:
# 📁 Project: /home/ubuntu/my-nextjs-app
# 🎯 Mode: Production
# ✅ Detected platforms: vercel
# 🚀 Deploying to Vercel...
# ✅ Deployment successful!

Example 2: Deploy Full-Stack App to Railway

# Project has railway.toml
python3 /home/ubuntu/skills/deployment-automation/scripts/deploy.py ~/my-fullstack-app

# Output:
# 📁 Project: /home/ubuntu/my-fullstack-app
# 🎯 Mode: Production
# ✅ Detected platforms: railway
# 🚀 Deploying to Railway...
# ✅ Deployment successful!

Example 3: Deploy Preview

# Deploy to preview/staging environment
python3 /home/ubuntu/skills/deployment-automation/scripts/deploy.py ~/my-app --preview

# Output:
# 📁 Project: /home/ubuntu/my-app
# 🎯 Mode: Preview
# ✅ Detected platforms: vercel
# 🚀 Deploying to Vercel...
# ✅ Deployment successful!

Configuration Templates

Vercel (vercel.json)

Use template: /home/ubuntu/skills/deployment-automation/templates/vercel.json

{
  "version": 2,
  "name": "my-project",
  "builds": [
    {
      "src": "package.json",
      "use": "@vercel/next"
    }
  ],
  "env": {
    "DATABASE_URL": "@database_url"
  }
}

Railway (railway.toml)

Use template: /home/ubuntu/skills/deployment-automation/templates/railway.toml

[build]
builder = "NIXPACKS"
buildCommand = "npm run build"

[deploy]
startCommand = "npm start"

Platform Selection Guide

Choose Vercel If:

• Using Next.js or React
• Need fast global CDN
• Want preview deployments
• Deploying frontend only

Choose Railway If:

• Need database included
• Building full-stack app
• Want simple pricing
• Need backend services

Choose Netlify If:

• Building static site
• Using JAMstack
• Need forms handling

Choose Heroku If:

• Using traditional frameworks
• Need extensive add-ons
• Want mature ecosystem

Environment Variables

Set Variables

Vercel:

vercel env add DATABASE_URL
vercel env pull

Railway:

railway variables set DATABASE_URL=postgres://...
railway variables

Netlify:

netlify env:set DATABASE_URL postgres://...
netlify env:list

Heroku:

heroku config:set DATABASE_URL=postgres://...
heroku config

Troubleshooting

Build Fails

1. Check build logs
2. Verify dependencies in package.json
3. Test build locally: npm run build
4. Check Node version compatibility

Deploy Succeeds But Site Broken

1. Check runtime logs
2. Verify environment variables set
3. Test API endpoints
4. Check database connection

CLI Not Installed

Script will prompt to install automatically:

⚠️  vercel CLI not installed
Install vercel CLI? (y/n): y
📦 Installing vercel CLI...

Authentication Required

# Vercel
vercel login

# Railway
railway login

# Netlify
netlify login

# Heroku
heroku login

Best Practices

1. Test Locally First

   npm run build
   npm start
   

2. Use Preview Deployments

   deploy.py /path/to/project --preview
   

3. Set Up Health Checks

   // pages/api/health.js
   export default function handler(req, res) {
     res.status(200).json({ status: 'ok' });
   }
   

4. Monitor Logs

   vercel logs
   railway logs
   netlify logs
   heroku logs --tail
   

5. Version Control

   git tag v1.0.0
   git push --tags
   

Integration with CI/CD

GitHub Actions

name: Deploy
on:
  push:
    branches: [main]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Deploy
        run: |
          python3 skills/deployment-automation/scripts/deploy.py .

Advanced Usage

Custom Deploy Script

If project has "deploy" script in package.json:

{
  "scripts": {
    "deploy": "custom-deploy-command"
  }
}

The skill will detect and use it automatically.

Multiple Platforms

If multiple platforms detected, first one is used:

✅ Detected platforms: vercel, netlify
🚀 Deploying to Vercel...

To use different platform, remove unwanted config files.

Files

Scripts

• scripts/deploy.py - Main deployment automation script

Templates

• templates/vercel.json - Vercel configuration template
• templates/railway.toml - Railway configuration template

References

• references/platforms.md - Complete platform comparison and guide

Related Skills

• github-workflow-automation - Automate CI/CD with GitHub Actions
• error-monitoring-setup - Set up Sentry for deployed apps
• database-schema-generator - Generate database schemas before deployment

Workflow

1. User runs deploy.py with project path
2. Script detects platform (vercel.json, railway.toml, etc.)
3. Script checks if CLI installed
4. Script prompts to install if missing
5. Script runs deployment command
6. Script reports success/failure

Success Criteria

✅ Platform detected automatically
✅ CLI installed if needed
✅ Deployment succeeds
✅ URL returned
✅ Logs accessible

Time Savings

Manual Deployment: ~30 minutes

• Install CLI: 5 min
• Configure: 10 min
• Set environment variables: 5 min
• Deploy: 5 min
• Troubleshoot: 5 min

With This Skill: ~2 minutes

• Run script: 30 sec
• Automated detection and deployment: 1.5 min

Savings: ~28 minutes per deployment

Future Enhancements

• Support for AWS, Azure, GCP
• Automatic database migrations
• Blue-green deployments
• Canary releases
• Automatic rollback on errors
• Deployment notifications (Slack, email)
• Performance monitoring integration

Created: February 10, 2026
Status: Production Ready
Tested: Vercel, Railway, Netlify, Heroku