Building Scalable Microservices with NestJS and MongoDB

Business Challenge

At RWE Energy, our legacy Java monolith was struggling with 5,000+ daily queries. Critical issues included:

• 45+ minute export times - users waiting too long for large exports
• Memory crashes during peak loads - system unavailable during critical hours
• Monolithic deployment - minor updates required full system redeployment

Technical Solution: NestJS Microservices

Why NestJS: Enterprise-grade TypeScript framework with built-in dependency injection, decorators, and excellent MongoDB integration.

Architecture Overview

• API Gateway - Request routing and authentication (JWT)
• User Service - Authentication, profiles, permissions
• Data Processing Service - Heavy computations and exports
• Notification Service - Email, SMS, push notifications

Key Technical Implementation

MongoDB Integration: Connection pooling with 10 concurrent connections, optimized for high-performance queries with proper indexing strategies.

Caching Strategy: 10-minute cache on frequently accessed reports, reducing database load by 60% during peak hours.

Microservices Pattern: Each service independently deployable with Docker containers, enabling zero-downtime updates.

Business Results

Azure Deployment

Production Setup: Azure Container Instances with Application Gateway for load balancing. MongoDB Atlas for managed database with automatic failover.

Docker Strategy: Lightweight Alpine Linux containers with Node.js 18, optimized build process with production-only dependencies for faster startup times.

Key Takeaways

• Microservices aren't always the answer - evaluate complexity vs. benefits
• Database design matters - proper indexing reduced query times by 60%
• Monitoring is crucial - implemented comprehensive logging with Azure Application Insights
• Team adoption - TypeScript made transition smoother for Java developers