System Design Tutorial

Learn how large-scale systems are actually built — scalability, caching, queues, and real case studies.

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What you'll learn

1. System Design Basics

Scalability, availability and reliability — the core vocabulary every system design conversation starts with.

2. CAP Theorem & PACELC

Why distributed systems must trade off consistency and availability, and what PACELC adds to the picture.

3. Load Balancing, Reverse Proxies & Caching

Distributing traffic across servers, and speeding up reads with caches and CDNs.

4. Database Scaling: Sharding & Replication

Indexing, read replicas, sharding strategies, and the trade-offs of each.

5. Message Queues & Event-Driven Architecture

Decoupling services with queues like Kafka and RabbitMQ, and designing around events.

6. Microservices vs Monolith

API gateways, rate limiting, circuit breakers, and when microservices are (and aren't) worth the cost.

7. Distributed Consensus: Raft & Paxos

How distributed nodes agree despite failures — Raft leader election and log replication, Paxos in brief, and where this shows up in etcd and ZooKeeper.

8. Case Study: Designing a URL Shortener

A full worked example — requirements, capacity estimation, data model, and architecture.

9. Case Study: Designing a Video Streaming Service

A full worked example for a Netflix/YouTube-style service — upload and transcoding pipeline, CDN delivery, and metadata database choices.