Chapter 10: Deployment Strategies

From Development to Production

Building a comment system is one thing; deploying and running it reliably is another. This chapter covers the strategies and considerations for getting your system live and keeping it running smoothly.

Deployment Environments

Development Environment

Where you build and test:

Considerations:

Staging Environment

Pre-production testing:

Considerations:

Production Environment

The live system:

Considerations:

Deployment Options

Static Hosting Platforms

For the frontend widget and static assets:

Netlify, Vercel, Cloudflare Pages:

Advantages:

Use for:

Serverless Platforms

For API backend:

AWS Lambda, Cloudflare Workers, Netlify Functions:

Advantages:

Disadvantages:

Container Platforms

For more control over the runtime:

Docker-based Options:

Advantages:

Disadvantages:

Traditional VPS/Server

Maximum control:

Providers:

Advantages:

Disadvantages:

Deployment Process

Continuous Deployment

Automated deployment on code changes:

Basic Flow:

  1. Code pushed to repository
  2. CI system detects change
  3. Tests run automatically
  4. If tests pass, deploy to staging
  5. Manual approval for production
  6. Deploy to production

Benefits:

Blue-Green Deployment

Running two identical environments:

Process:

  1. “Blue” is current production
  2. Deploy new version to “Green”
  3. Test Green environment
  4. Switch traffic to Green
  5. Blue becomes standby

Benefits:

Rolling Deployment

Gradually updating instances:

Process:

  1. Update one instance
  2. Verify it’s healthy
  3. Update next instance
  4. Repeat until all updated

Benefits:

Canary Deployment

Testing with subset of users:

Process:

  1. Deploy new version to small percentage
  2. Monitor for issues
  3. Gradually increase percentage
  4. Full rollout if stable

Benefits:

Infrastructure as Code

Define infrastructure in version-controlled files:

Benefits

Tools

Terraform: Multi-cloud infrastructure provisioning.

Pulumi: Infrastructure using real programming languages.

CloudFormation (AWS): AWS-specific infrastructure definition.

Platform-Specific: Many platforms have their own config files (netlify.toml, vercel.json, etc.).

Database Deployment

Migrations

Managing database schema changes:

Principles:

Process:

  1. Create migration file
  2. Test in development
  3. Apply to staging
  4. Verify
  5. Apply to production
  6. Monitor

Data Seeding

Initial data setup:

Backup Before Changes

Always before migrations:

Configuration Management

Environment Variables

Store configuration outside code:

What to Include:

Security:

Secrets Management

For sensitive configuration:

Options:

Feature Flags

Control features independently of deployment:

Benefits:

Monitoring and Observability

Health Checks

Verify system is running:

Endpoint Health:

Process:

Logging

Capture system activity:

What to Log:

Where to Send:

Metrics

Quantitative measurements:

Key Metrics:

Tools:

Alerting

Automated notification of problems:

Alert On:

Alert Channels:

Security Considerations

SSL/TLS

All traffic encrypted:

Firewall and Access

Limit exposure:

Updates and Patches

Keep systems current:

Penetration Testing

Verify security:

Rollback Procedures

When things go wrong:

Preparation

Quick Rollback

For code issues:

Data Rollback

More complex:

Deployment Checklist

Pre-Deployment

Deployment

Post-Deployment

Disaster Recovery

Backup Strategy

Recovery Procedures

Documented processes for:

Recovery Objectives

RTO (Recovery Time Objective): How long can you be down? Design for this.

RPO (Recovery Point Objective): How much data can you lose? Backup frequency should match.

Summary

Successful deployment requires:

  1. Environments: Development → Staging → Production
  2. Automation: CI/CD pipelines for consistent deployment
  3. Configuration: Secure, environment-specific settings
  4. Monitoring: Know when things go wrong
  5. Rollback: Ability to quickly recover
  6. Documentation: Clear procedures for common scenarios

Start simple (direct deploys to production) and add sophistication as your needs grow. The goal is reliable, repeatable deployments with minimal stress.

The next chapter covers maintenance and operations—keeping your system running long-term.