Scalability
Scaling strategies and performance optimization.
Vertical Scaling
Increase resources on existing servers:
- More CPU for handling requests
- More memory for caching
- Faster storage for database
- Better network for throughput
Limits: Single server capacity
Horizontal Scaling
Add more servers to cluster:
- Distribute load across servers
- Place servers near users
- Increase redundancy
- No practical limit
Requirements: Database that scales
Database Scaling
MySQL/MariaDB:
- Master-replica replication
- Cluster configurations
- Read replicas for queries
Redis/Valkey:
- Cluster mode
- Sentinel for HA
- Sharding for capacity
Performance Considerations
Latency
Factors:
- Distance between user and server
- Network quality
- Server load
- Database performance
Solutions:
- Place servers near users (zones)
- Use leaf mode for remote users
- Optimize database queries
- Cache frequently accessed data
Throughput
Factors:
- Number of concurrent users
- Space creation rate
- API request volume
- Database capacity
Solutions:
- Horizontal scaling (more servers)
- Database optimization
- Connection pooling
- Rate limiting
Resource Usage
Server resources:
- CPU: Request handling, data processing
- Memory: Caching, active connections
- Storage: Database, logs, temporary files
- Network: Client connections, agent communication
Optimization:
- Right-size server resources
- Monitor resource usage
- Scale before hitting limits
- Regular maintenance