Case Study - Database Migration & DevOps Modernization

Overview

This case study outlines how we successfully migrated from DocumentDB to PostgreSQL while simultaneously modernizing our client's DevOps practices through infrastructure as code.

Challenges Identified

• Legacy DocumentDB struggling with scaling demands
• Increasing database costs as application usage grew
• Inefficient data relationships limiting product capabilities
• Manual infrastructure management consuming significant engineering resources
• Frequent deployment errors and inconsistencies between environments
• Limited visibility into infrastructure changes and history

Business Impact

• Development velocity bottlenecks from database performance issues
• Rising operational costs threatening financial sustainability
• Engineering team spending excessive time on infrastructure maintenance
• Deployment issues causing reliability concerns for customers
• Technical debt accumulating across infrastructure components

Project Goals

• Migrate database system with zero data loss
• Improve query performance and reduce database costs
• Establish more efficient data relationships
• Implement Infrastructure as Code for greater reliability
• Create separated development/staging/production environments
• Reduce deployment errors and infrastructure management time

Solution

Database Migration

• Conducted comprehensive analysis of existing DocumentDB implementation
• Designed new PostgreSQL schema with improved data relationships
• Implemented new data models optimized for PostgreSQL
• Developed migration plan with detailed steps and fallback options
• Developed custom data migration scripts with validation checks
• Implemented seamless cutover strategy to minimize downtime

DevOps Modernization

• Selected AWS CDK as primary IaC tool for TypeScript compatibility
• Defined core infrastructure components as reusable constructs
• Incorporated security best practices into infrastructure definitions
• Created separate development, staging, and production environments
• Established monitoring and alerting with Cloudwatch and Sentry

Deployment Pipeline Automation

• Designed CI/CD workflows for infrastructure and application code
• Automated deployment processes with GitHub Actions
• Implemented approval gates for production deployments

Technoliogies Used

Results

• 40% improvement in query performance
• 50% reduction in database costs
• Zero data loss during migration
• 99% reduction in deployment errors
• 60% reduction in infrastructure management Time
• 100% infrastructure consiteny between environments