When one of our retail clients approached us with the challenge of handling massive traffic spikes during seasonal sales, we knew a traditional architecture would not suffice. This is the story of how we built a platform that handles 100,000+ concurrent users without breaking a sweat.
The Challenge
Our client's existing e-commerce platform regularly crashed during promotional events. Black Friday sales, flash deals, and product launches would bring the site down, costing thousands in lost revenue and damaging customer trust.
The requirements were clear:
- Handle 100,000+ concurrent users
- Sub-second page load times
- Zero downtime during traffic spikes
- Real-time inventory management
- Seamless checkout experience under load
The Architecture
Frontend: Static-First Approach
We built the frontend with Nuxt.js using static site generation for product catalog pages. These pre-rendered pages are served from a global CDN, ensuring lightning-fast load times regardless of traffic volume.
Dynamic elements like cart functionality and user sessions are handled client-side with API calls to our backend services.
Backend: Microservices on Kubernetes
The backend is decomposed into specialized services:
- Product Service — Manages catalog, pricing, and search
- Cart Service — Handles shopping cart state with Redis for speed
- Order Service — Processes orders with guaranteed delivery
- Inventory Service — Real-time stock management with optimistic locking
- Payment Service — Integrates with multiple payment gateways
Each service scales independently based on demand. During peak events, the cart and checkout services automatically scale up while catalog services remain stable.
Database Strategy
- PostgreSQL for transactional data (orders, users)
- Redis for session management and caching
- Elasticsearch for product search and filtering
The Results
After launching the new platform:
- 99.99% uptime during peak sales events
- 300ms average page load time globally
- 40% increase in conversion rate due to improved performance
- Zero crashes during the first Black Friday on the new platform
Key Takeaways
- Design for peak load from day one — Retrofitting scalability is expensive
- Cache aggressively — Most e-commerce content changes infrequently
- Test under realistic load — Load testing revealed bottlenecks we never anticipated
- Monitor everything — Real-time observability enabled us to respond to issues before they impacted users
This project reinforced our belief that architecture decisions made early in a project have the greatest impact on long-term success.
