The Art of Building Systems: Core Principles of System Design

by Nilesh Hazra

A few years ago, I was working with a small team on a product that was growing faster than we expected. In the early days, things were simple: one server, one database, and a handful of happy users. Life was good. But as the number of users grew, our system started to feel like an old scooter carrying too many passengers. It wobbled, it slowed down, and sometimes, it just broke down in the middle of the road.

That’s when I first learned the true importance of system design principles. Designing systems is not just about writing code—it’s about building something that can survive, adapt, and grow gracefully over time.

Let me take you through a few core principles of system design, told in a way that might feel familiar if you’ve ever tried to keep something running while it was under pressure.

1. Scalability – Building for Tomorrow, Not Just Today

Imagine you’re running a small tea stall in your neighborhood. In the beginning, ten customers a day is manageable. But what if tomorrow, a hundred people line up? If you still have just one kettle and one helper, chaos will follow.

Systems are like that tea stall. They need to be designed so that when demand increases, you can add more kettles and more helpers without rewriting the whole recipe. In tech terms: horizontal scaling (adding more machines) is usually better than trying to make one giant kettle (vertical scaling).

2. Reliability – Because Things Will Break

No matter how careful you are, systems fail. Hard drives crash, networks go down, bugs sneak in. Good system design accepts this as a fact of life.

Think of it like electricity. You don’t rely on a single power plant—you have a whole grid. If one line fails, another picks up the load. Similarly, in system design, we use replication, failover, and redundancy so the system keeps working even if one part collapses.

3. Simplicity – Complexity Is a Silent Killer

When we first faced system issues, our instinct was to add more tools, more scripts, more patches. It felt clever at the time, but in reality, we built a fragile tower of Jenga blocks. One wrong move and everything tumbled.

A wise senior once told me:

“If you can’t explain your system on a whiteboard in 5 minutes, it’s too complex.”

Simple systems are easier to maintain, scale, and debug. Complexity might look impressive, but simplicity is what survives.

4. Observability – Don’t Fly Blind

Imagine driving a car with no fuel gauge, no speedometer, and no warning lights. You wouldn’t know when you’re about to run out of fuel or if your engine is overheating—until it’s too late.

Systems without logs, metrics, and monitoring are exactly like that. You need observability: the ability to see what’s happening under the hood in real time. Only then can you react before small issues turn into disasters.

5. Trade-offs – You Can’t Have It All

This is the hardest lesson. In system design, every choice comes with a cost. Do you want faster performance? You may sacrifice storage space. Do you want tighter consistency? You may have to give up availability in certain conditions (yes, hello CAP theorem).

Just like in life, system design is about making smart trade-offs based on priorities. The key is to know what matters most for your users right now.

The Key Learning

System design is not about creating a perfect machine. It’s about creating a resilient one. A system that grows with its users, recovers when it falls, stays simple enough to manage, tells you when it’s in pain, and makes thoughtful trade-offs along the way.

Next time you think about system design, don’t picture code or servers. Picture that tea stall. Will it survive the morning rush? Will it serve hot tea when people need it most? That’s the art of system design.

Takeaway:

Good system design is less about technology and more about mindset. Build for growth, expect failures, keep it simple, monitor everything, and embrace trade-offs. Do this, and your system won’t just work—it will thrive.

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Have comments or questions? Join the discussion on the original GitHub Issue.