Backend Optimization
Backend Refactoring for 15-20% Performance Boost
ULOM
March 2024
3 months
2 engineers
The Challenge
ULOM's growth exposed structural limitations in its monolithic Flask application causing scalability risks and increasing costs.
- 25,949-line monolithic Flask application
- Redundant MongoDB queries slowing performance
- Increasing API dependency costs
- Slower translation-heavy pages
- Scalability risks from technical debt
- Compounding technical debt making safe improvements difficult
- Needed refactoring without disrupting operations
Our Solution
Executed comprehensive backend refactoring with query optimization, caching, and architectural improvements.
Query Optimization
- Eliminated redundant MongoDB queries
- Implemented efficient indexing strategies
- Optimized database connection pooling
- Reduced N+1 query problems
- Added query result caching with Redis
API Cost Reduction
- Reduced unnecessary API calls by 40%
- Implemented smart caching for API responses
- Batched API requests where possible
- Added fallback mechanisms
- Optimized translation API usage
Architecture Improvements
- Modularized monolithic codebase
- Improved code organization and maintainability
- Enhanced error handling and logging
- Implemented CI/CD for safe deployments
- Zero-downtime deployment strategy
The Impact
- 15-20% faster page loads across the platform
- 40% reduction in API dependency costs
- Improved scalability and performance
- Eliminated technical debt bottlenecks
- Zero-disruption deployment and transition
- Foundation for future feature development
- Better application maintainability and code quality
"They optimized our entire backend without any downtime. The performance improvements were immediate and the cost savings are significant."
C
CTO, ULOM
Chief Technology Officer
Technologies Used
FlaskMongoDBRedisGunicornCI/CDPython