Cloud infrastructure fundamentally changes how applications are designed and deployed. Instead of provisioning for peak load, architects can design systems that scale horizontally, adding and removing capacity in response to real-time demand. This elasticity reduces costs while improving availability.
Horizontal Scaling Patterns
Stateless application tiers are the foundation of horizontal scaling. By storing session data in a shared cache or database rather than local memory, any instance can handle any request. Place a load balancer in front of your application tier and configure health checks to automatically remove unhealthy instances from the pool.
Database scaling requires a different approach. Read replicas can distribute read traffic across multiple instances, while write scaling typically requires sharding or moving to a distributed database system. Implement connection pooling at the application layer to manage database connections efficiently and prevent connection exhaustion under load.
Auto-scaling policies should be based on metrics that correlate with user experience, such as request latency or queue depth, rather than raw CPU utilization. Set scale-out thresholds aggressively and scale-in thresholds conservatively to avoid oscillation. Always test your scaling policies under simulated load before relying on them in production.