System design interviews are where companies test whether you can build software that survives the real world.

Not “can you write code,” but: can you design a service that stays fast when traffic spikes, keeps working when servers fail, stores data safely, and still feels simple to evolve six months later?

System design interviews are different from coding interviews. There's no single correct answer. No test cases to pass. Instead, you're evaluated on how you think about building large-scale systems.

In this chapter, I'll explain:

1. What is a System Design Interview?

A system design interview is a technical interview where you're asked to design the architecture of a large-scale software system. Think "Design Instagram" or "Design a rate limiter."

In a coding round, you're given a well-defined problem with clear inputs, outputs, and constraints. You write code, run it against test cases, and either pass or fail. It's binary.

System design is messier. The problem is intentionally vague. The constraints are whatever you and the interviewer decide they should be. There's no code to run. Instead, you're drawing boxes and arrows on a whiteboard while explaining your thought process out loud.

These interviews typically last 45-60 minutes and involve designing systems like:

The goal is not to design a production-ready system in 45 minutes. That's impossible. The goal is to demonstrate that you can think through complex problems, make reasonable trade-offs, and communicate your ideas clearly.

2. Why Do Companies Conduct System Design Interviews?

Coding interviews answer one question: can this person write correct code? That's necessary, but it's not sufficient. Building software at scale requires a completely different set of skills.

The Gap Between Code and Systems

Consider what happens when you write a function that works perfectly on your laptop. Now imagine that function needs to:

Suddenly, the algorithm isn't the hard part anymore. The hard part is everything around it: how data flows through the system, where bottlenecks will appear, what happens when things fail.

System design interviews exist to filter for engineers who can think beyond the function level.

How Expectations Change with Seniority

The weight given to system design increases dramatically as you move up the ladder.

This makes sense when you think about what each level does day-to-day. Junior engineers implement features that someone else designed. Senior engineers design those features.

Staff engineers design systems that span multiple teams. At each level, the scope of your design responsibility expands.

What Companies Learn About You

Beyond technical knowledge, system design interviews expose how you think and work:

Technical breadth: Do you know when to use a message queue? Can you explain the trade-offs between SQL and NoSQL? Understanding the tools available is the baseline.

Problem decomposition: Can you take a vague problem like "design Twitter" and break it into concrete, solvable pieces? This skill transfers directly to real engineering work.

Trade-off reasoning: Every design decision has costs and benefits. Candidates who say "we should use Redis" without explaining why, or acknowledging what they're giving up, raise red flags.

Communication clarity: In the real world, you'll spend more time explaining your designs to others than implementing them. The interview tests whether you can bring people along with your thinking.

Experience signals: When a candidate casually mentions that eventual consistency was fine for their use case because user expectations allowed a 30-second delay, that's the kind of practical wisdom that only comes from building real systems.

3. What Do Interviewers Look For?

System design interviews are subjective. Different interviewers may value different things. But there are common evaluation criteria.

1. Requirements Gathering

The first few minutes of your interview reveal more than you might think. When I give a candidate a problem like "Design a URL shortener," I'm watching to see if they immediately start drawing boxes or if they pause to ask questions.

The candidates who jump straight into designing almost always struggle later. They design a system for the wrong scale, miss critical requirements, or solve a problem the interviewer didn't ask for.

Strong candidates treat the first 5-10 minutes as a conversation:

These questions aren't just gathering information. They signal that you understand how requirements shape design. A system for 1,000 URLs per day looks nothing like one for 100 million.

2. High-Level Design

Once requirements are clear, you need to sketch the major components and how they connect.

This is where interviewers assess your architectural intuition. Can you identify the core components a system needs? Do you understand how data flows from a user's request to a database and back?

A typical high-level design includes:

The goal isn't to include every possible component. It's to include the right components for your specific requirements and be able to explain why each one is there.

3. Deep Dives

After the high-level design, the interviewer picks a component and asks you to go deeper. This is where the interview gets interesting.

Anyone can draw a box labeled "Database." The deep dive reveals whether you actually understand how databases work. Can you explain why you chose PostgreSQL over MongoDB for this use case? What happens when your single database can't handle the load? How would you shard it?

Common deep dive topics:

The interviewer isn't looking for textbook answers. They're looking for practical understanding. When you say "we'll add a cache," do you know what cache eviction policy to use? Do you understand the trade-offs between write-through and write-behind caching?

4. Trade-off Analysis

This is often what separates good candidates from great ones. Every design decision involves trade-offs, and interviewers want to see that you understand them.

When a candidate says "we should use a NoSQL database," the next question is always "why?" The right answer isn't "because NoSQL is better." The right answer explains the specific trade-off: "We're prioritizing write throughput and horizontal scalability over strong consistency, which is acceptable for this use case because users can tolerate seeing slightly stale data."

5. Communication

Technical knowledge matters, but so does how you convey it. The interview simulates a design discussion with a colleague. Can you explain your thinking in a way that's easy to follow?

Strong communicators: