Each growth phase requires a different approach. Don’t over-engineer prematurely.
Phase 1: 0-1K Users¶
- Single server (VPS)
- Monolith
- SQLite or PostgreSQL on the same server
- Deploy: git pull
Phase 2: 1K-10K¶
- Separate database to its own server
- CDN for static files
- Redis for sessions and cache
- Basic monitoring
Phase 3: 10K-100K¶
- Load balancer + 2-3 app servers
- Database read replica
- Background jobs (queue)
- Full monitoring + alerting
- CI/CD pipeline
Phase 4: 100K-1M¶
- Kubernetes / managed containers
- Database sharding or managed DB
- Message queue (Kafka/RabbitMQ)
- Microservices (carefully)
- Multi-AZ deployment
- CDN + edge caching
Phase 5: 1M+¶
- Multi-region
- Global load balancing
- CQRS/Event sourcing
- Dedicated teams per service
- Custom solutions for specific bottlenecks
Universal Rules¶
- Cache is your most powerful weapon
- Database is usually the bottleneck
- Measure before optimizing
- Scale horizontally, not vertically
- Every optimization adds complexity
Key¶
Scale when you must, not in advance. Premature optimization is the root of all evil.
scalingarchitectureperformance