Scaling Up without Breaking the Bank › Load Balancing Across Multiple Servers

Thread pools work well for moderate scaling, but what if you need to handle hundreds or thousands of concurrent users? At that point, a single server isn't enough. You need to distribute requests across multiple servers.

This is where load balancers come in. A load balancer sits in front of your agent instances and distributes incoming requests across them. If one server gets overloaded, the load balancer routes new requests to less busy servers.

Here's a simple architecture:

User Requests
     ↓
Load Balancer
     ↓
┌────┴────┬────────┬────────┐
↓         ↓        ↓        ↓
Agent     Agent    Agent    Agent
Instance  Instance Instance Instance
1         2        3        4

Each agent instance runs independently. The load balancer decides which instance handles each request. If Instance 1 is busy, the request goes to Instance 2.

Most cloud platforms provide load balancing services. On AWS, you'd use Elastic Load Balancing. On Google Cloud, it's Cloud Load Balancing. These services handle the complexity of routing requests and monitoring instance health.

For our purposes, the key insight is this: horizontal scaling lets you handle more load by adding more instances. Start with one instance and a thread pool. As usage grows, add more instances behind a load balancer.