Scalability
Scalability strategies for the Plus261 platform. The system is designed to scale horizontally and vertically to handle growing loads.
What You’ll Learn
Section intitulée « What You’ll Learn »This guide will help you understand:
- ✅ Horizontal and vertical scaling
- ✅ Database scaling strategies
- ✅ API scaling techniques
- ✅ Client optimization
- ✅ Caching strategies
- ✅ Performance optimization
Overview
Section intitulée « Overview »The platform is designed to be scalable:
| Strategy | Description | Use Case |
|---|---|---|
| Horizontal | Adding servers | High traffic, distributed load |
| Vertical | Increasing resources | Resource-intensive operations |
| Cache | Caching frequently accessed data | Read-heavy workloads |
| Optimization | Query and code optimization | Performance improvements |
Database
Section intitulée « Database »Indexing
Section intitulée « Indexing »Indexes optimize performance:
- ✅ Primary key indexes
- ✅ Foreign key indexes
- ✅ Composite indexes for queries
- ✅ Full-text indexes for search
Learn more: Database Architecture
Partitioning
Section intitulée « Partitioning »Partitioning can be used for large tables:
- ✅ Range partitioning by date
- ✅ Hash partitioning for distribution
- ✅ List partitioning by category
Replication
Section intitulée « Replication »Replication enables high availability:
- ✅ Master-slave replication
- ✅ Read replicas for scaling reads
- ✅ Automatic failover
Load Balancing
Section intitulée « Load Balancing »Load balancing distributes the load:
- ✅ Round-robin distribution
- ✅ Least connections
- ✅ Health checks
- ✅ Session affinity
Cache reduces load on the database:
- ✅ Query result caching
- ✅ Response caching
- ✅ CDN for static assets
- ✅ Redis for distributed cache
Horizontal Scaling
Section intitulée « Horizontal Scaling »- ✅ Stateless API design
- ✅ Shared session storage
- ✅ Load balancer configuration
- ✅ Auto-scaling groups
Code Splitting
Section intitulée « Code Splitting »Code splitting optimizes loading:
- ✅ Route-based splitting
- ✅ Component-based splitting
- ✅ Lazy loading
- ✅ Dynamic imports
Lazy Loading
Section intitulée « Lazy Loading »Lazy loading loads resources on demand:
- ✅ Images on scroll
- ✅ Components on route
- ✅ Data on interaction
- ✅ Modules on import
Service Worker Caching
Section intitulée « Service Worker Caching »- ✅ Static asset caching
- ✅ API response caching
- ✅ Offline support
- ✅ Background sync
Performance Optimization
Section intitulée « Performance Optimization »Database
Section intitulée « Database »- ✅ Query optimization
- ✅ Connection pooling
- ✅ Prepared statements
- ✅ Batch operations
- ✅ GraphQL query optimization
- ✅ DataLoader for N+1 prevention
- ✅ Response compression
- ✅ HTTP/2 support
- ✅ Bundle size optimization
- ✅ Image optimization
- ✅ Lazy loading
- ✅ Service Worker caching
Quick Reference
Section intitulée « Quick Reference »| Topic | Documentation |
|---|---|
| 📊 Database | Database Architecture |
| 📈 Monitoring | Monitoring Guide |
| 🚀 Deployment | Deployment Strategies |
Next Steps
Section intitulée « Next Steps »Continue learning:
- 📊 Monitoring - Monitoring and alerts
- 🚀 Deployment - Deployment strategies
- 🗄️ Database Architecture - Database scaling
- 📈 Performance Guide - Performance optimization
Related Topics
Section intitulée « Related Topics »- Monitoring - Monitoring and alerts
- Deployment - Deployment strategies
- Database Architecture - Database scaling
- Architecture Overview - System architecture