Implementing Trunk-Based Development Workflow

Managing trunk-based effectively is a crucial skill for any system administrator. This tutorial provides step-by-step instructions for git configuration, along with best practices for production environments.

Prerequisites

• A Git repository for your project
• A registered domain name (for public-facing services)
• Basic familiarity with the Linux command line
• Root or sudo access to the server
• A VPS running Ubuntu 22.04 or later (2GB+ RAM recommended)

Pipeline Configuration

The default configuration works well for development environments, but production servers require additional tuning. Pay particular attention to connection limits, timeout values, and logging settings.

# .github/workflows/deploy.yml
name: Deploy to Production
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build
        run: |
          docker build -t myapp:latest .
      - name: Deploy
        run: |
          ssh deploy@server 'cd /opt/myapp && docker compose pull && docker compose up -d'

Note that file paths may vary depending on your Linux distribution. The examples here are for Debian/Ubuntu; adjust paths accordingly for RHEL/CentOS-based systems.

Build and Test Setup

It's recommended to test this configuration in a staging environment before deploying to production. This helps identify potential compatibility issues and allows you to benchmark performance differences.

# Set up deployment pipeline
mkdir -p /opt/myapp
cd /opt/myapp

# Create deployment script
cat << 'EOF' > deploy.sh
#!/bin/bash
set -euo pipefail
echo "Deploying version: $1"
docker pull myapp:$1
docker compose down
DOCKER_TAG=$1 docker compose up -d
echo "Deployment complete"
EOF
chmod +x deploy.sh

Make sure to restart the service after applying these changes. Some settings require a full restart rather than a reload to take effect.

• Enable automatic security updates for critical patches
• Test your backup restore procedure monthly
• Monitor disk space usage and set up alerts
• Keep your system packages updated regularly
• Review log files weekly for anomalies

Deployment Automation

Performance benchmarks show that properly tuned trunk-based can handle significantly more concurrent connections than the default configuration. The key improvements come from adjusting worker processes and connection pooling.

# .github/workflows/deploy.yml
name: Deploy to Production
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build
        run: |
          docker build -t myapp:latest .
      - name: Deploy
        run: |
          ssh deploy@server 'cd /opt/myapp && docker compose pull && docker compose up -d'

Each line in the configuration serves a specific purpose. The comments explain the reasoning behind each setting, making it easier to customize for your specific use case.

Common Issues and Solutions

• Connection timeout: Verify your firewall rules allow traffic on the required ports. Use ss -tlnp to confirm the service is listening on the expected port.
• Service won't start: Check the logs with journalctl -xe -u trunk-based. Common causes include port conflicts, missing configuration files, or insufficient permissions.
• High memory usage: Review the configuration for memory-related settings. Reduce worker counts or buffer sizes if running on a low-RAM VPS.

Next Steps

With trunk-based now set up and running, consider implementing monitoring to track performance metrics over time. Regularly review your configuration as your workload changes and scale resources accordingly.