Introduction To System Design

What is System Design?

System Design is the process of defining the architecture, components, modules, interfaces, and data flow of a system to satisfy specified requirements. It's about making high-level decisions that shape how software systems are built, scaled, and maintained.

At its core, system design answers questions like:

• How do we handle millions of users simultaneously?
• How do we ensure data isn't lost when servers fail?
• How do we make the system fast for users across the globe?
• How do we evolve the system as requirements change?

┌─────────────────────────────────────────────────────────────────┐
│                     System Design Spectrum                      │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│   Requirements ──► Architecture ──► Components ──► Data Flow    │
│        │               │                │              │        │
│        ▼               ▼                ▼              ▼        │
│   Functional      High-Level       Databases      APIs &        │
│   Non-functional  Decisions        Caches         Protocols     │
│   Constraints     Trade-offs       Queues         Interfaces    │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

Why Learn System Design?

1. Career Growth

System design interviews are a critical part of senior engineering roles at top tech companies. Understanding these concepts opens doors to Staff, Principal, and Architect positions.

2. Build Better Software

Even if you're not designing systems from scratch, understanding the "why" behind architectural decisions helps you:

• Write code that scales
• Debug distributed systems effectively
• Communicate better with infrastructure teams

3. Develop Engineering Intuition

System design teaches you to think in trade-offs. There's rarely a "perfect" solution—only solutions that are optimal for specific constraints.

What We'll Cover

This documentation is structured to take you from fundamentals to advanced topics:

Fundamentals

Building Blocks

Advanced Concepts

Real-World System Designs

Prerequisites

You don't need to be an expert, but familiarity with these topics will help:

┌─────────────────────────────────────────────────────────────────┐
│                    Recommended Background                       │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  ✓ Basic programming (any language)                             │
│  ✓ Understanding of APIs (REST, HTTP methods)                   │
│  ✓ Familiarity with databases (basic SQL)                       │
│  ✓ Basic networking (IP, ports, DNS)                            │
│  ✓ Command line / terminal basics                               │
│                                                                 │
│  Nice to have:                                                  │
│  ○ Experience with cloud services (AWS, GCP, Azure)             │
│  ○ Worked on production systems                                 │
│  ○ Basic understanding of containers (Docker)                   │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

The System Design Mindset

Approaching system design requires a different mindset than writing code. Here are the key mental models:

1. Think in Trade-offs

There's no perfect solution. Every decision involves trade-offs:

The right answer is always: "It depends on the requirements."

2. Embrace "Good Enough"

Don't over-engineer. A system that handles 10x your current load is often sufficient. You can always iterate.

                    Over-engineering Trap
                    
    Requirements: 1,000 users/day
    
    ❌ Wrong: "Let's build for 1 billion users from day one!"
              Result: 6 months of complexity, no product
    
    ✓ Right:  "Let's build for 100,000 users, with clear
              scaling paths when needed."
              Result: Ship fast, scale when you have the problem

3. Understand the Numbers

Develop intuition for scale. Know these rough orders of magnitude:

4. Start Simple, Add Complexity

Always begin with the simplest architecture that could work:

Evolution of Architecture:

Stage 1: Monolith
┌─────────────────┐
│   Single App    │──► Database
└─────────────────┘

Stage 2: Add Caching
┌─────────────────┐
│   Single App    │──► Cache ──► Database
└─────────────────┘

Stage 3: Scale Horizontally
         ┌─────────┐
         │  App 1  │
┌────┐   ├─────────┤        ┌─────────┐
│ LB │──►│  App 2  │──►Cache│ Database│
└────┘   ├─────────┤        └─────────┘
         │  App 3  │
         └─────────┘

Stage 4: Split Services (only when needed)
... and so on

5. Ask Clarifying Questions

In interviews and real projects, always clarify:

• Functional requirements: What features must the system have?
• Non-functional requirements: Latency, throughput, availability targets?
• Scale: How many users? How much data? Read-heavy or write-heavy?
• Constraints: Budget? Team size? Existing infrastructure?

How to Use This Documentation

For Learning

1. Read sequentially: Start with fundamentals, build up to advanced topics
2. Draw diagrams: Sketch systems as you read—it helps retention
3. Question everything: Ask "why?" for each design decision

For Interview Prep

1. Practice out loud: Explain systems to a rubber duck or friend
2. Time yourself: Practice 45-minute design sessions
3. Review real systems: Read engineering blogs from Netflix, Uber, Meta

For Reference

1. Bookmark building blocks: Quick refreshers during design discussions
2. Use diagrams: Copy ASCII diagrams for your own documentation
3. Check the cheat sheets: Summary tables for quick recall

Key Takeaways

┌─────────────────────────────────────────────────────────────────┐
│                   System Design Principles                      │
├─────────────────────────────────────────────────────────────────┤
│                                                                 │
│  1. There are no perfect solutions, only trade-offs             │
│  2. Requirements drive architecture                             │
│  3. Start simple, add complexity only when needed               │
│  4. Understand the numbers (latency, throughput, scale)         │
│  5. Design for failure—things will break                        │
│  6. Iterate and evolve—you won't get it right the first time    │
│                                                                 │
└─────────────────────────────────────────────────────────────────┘

Next Steps

Ready to dive in? Here's the recommended path:

1. Scaling Basics — Understand how systems grow
2. Databases Deep Dive — The foundation of most systems
3. Caching Strategies — Speed up everything
4. Load Balancing — Distribute the load

Let's build systems that scale!