The easiest way to handle backend traffic is to spin up NGINX or let a cloud provider handle the routing. But if you want to understand how a reverse proxy actually manages concurrent requests and node failovers, you have to build one yourself.
I recently engineered a custom, low-level distributed load balancer in C#. Here is the architectural breakdown.
The Architecture:
The system is split into three decoupled modules:
CrudClient: Dispatches CRUD data payloads over TCP sockets.
CrudServer: The central proxy. It listens for incoming connections and distributes traffic.
SubServers: Independent worker nodes processing the actual logic.
The Friction of Raw TCP
Relying purely on TcpListener and TcpClient meant I couldn't rely on HTTP middleware. Every incoming connection on both the proxy and worker nodes had to be handled within an isolated execution thread to prevent blocking behavior. If a node drops, the proxy has to manually intercept the network fault and re-route the transaction.
The Takeaway
Building this forced me to deal with manual thread synchronization and explicit concurrent execution pools. It’s gritty work, but it completely demystifies how large-scale distributed systems manage traffic.
You can check out the full source code and directory structure on my GitHub: https://github.com/hamza-core/Load_Balancer
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