🏗️ System Design — From Beginner to Advanced

Learn how the biggest systems in the world are actually built. Clear explanations, real diagrams, and full case studies — for the @codewithmuh YouTube series.

flowchart TD
    Client["Clients (Mobile / Web / Desktop)"] --> DNS["DNS & Anycast Geo-Routing"]
    DNS --> CDN["Edge CDN (Static Assets & Video Chunks)"]
    DNS --> LB["API Gateway & Load Balancer (Rate Limit + TLS)"]
    
    subgraph Services["Core Microservices Cluster"]
        LB --> Auth["Auth Service"]
        LB --> Core["Core Application API"]
        LB --> Search["Search & Recommendation Engine"]
    end
    
    subgraph DataTier["Data & Cache Tier"]
        Core --> Cache[("Distributed Cache (Redis / Memcached)")]
        Core --> SQL[("Primary SQL DB (Postgres / MySQL)")]
        SQL -.-> Replica[("Read Replicas")]
        Core --> Queue[("Message Broker (Kafka / RabbitMQ)")]
        Queue --> Workers["Async Background Workers"]
    end

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📺 What is this?

This repo is the companion to a YouTube series where we learn system design from scratch and then design real products step by step. Every topic is written as a detailed article with diagrams (not just walls of text), and each one maps to a video.

The goal: a complete beginner should be able to follow along, understand why each decision is made, and walk away able to reason about large-scale systems.

🚧 This repo is actively being built. Star ⭐ it and subscribe to follow along.

🧭 How to use this repo

1. Start with the Fundamentals — the vocabulary and building blocks (load balancing, caching, databases, sharding, CAP, queues, …).
2. Then pick a case study below and design a real system end-to-end.
3. Each article follows the same repeatable framework, so the approach becomes second nature.

📚 Learning path

Part 1 — Foundations

• System Design Fundamentals — the framework + every core building block, beginner → advanced.

Part 2 — Case studies (design a real system)

#	System	What you'll learn	Status
1	Cloud Platform (AWS / Google Cloud)	Control plane vs data plane, virtualization, multi-tenancy, IAM	🚧
2	ChatGPT & Claude (AI Assistant)	LLM inference serving, batching, KV cache, token streaming	🚧
3	Instagram	News feed, media storage, fan-out	⬜
4	WhatsApp	Real-time messaging, presence, delivery receipts	⬜
5	Facebook	Social graph, feed ranking, notifications	⬜
6	TikTok	Recommendation feed, video delivery at scale	⬜
7	YouTube	Video upload/transcode, streaming, CDN	⬜
8	Twitter / X	Timeline, fan-out on write vs read	⬜
9	Uber	Geospatial matching, real-time location	⬜
10	Netflix	Adaptive streaming, CDN, recommendations	⬜

✅ Published · 🚧 In progress · ⬜ Planned

🖊️ How the diagrams work

We use a layered approach so diagrams are both version-controlled and beautiful on video:

• Mermaid — rendered natively inside GitHub for inline flowcharts & sequence diagrams (no image hosting needed).
• Excalidraw — for the polished, hand-drawn architecture diagrams (source .excalidraw files live in assets/excalidraw/, exported PNG/SVG in assets/images/).

See TOOLS.md for the full recommended toolchain — including how to add cloud/logo icons in Excalidraw and the article → YouTube video workflow.

📐 Writing a new article

Copy templates/ARTICLE_TEMPLATE.md into a new case-study folder and fill it in. Every system-design problem uses the same framework:

Requirements → Capacity estimation → API design → Data model → High-level design → Deep dives → Bottlenecks & trade-offs

🤝 Contributing

See CONTRIBUTING.md. Issues, corrections, and diagram improvements are welcome.

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Made with ❤️ for learners · YouTube @codewithmuh