How to Crack Any System Design Interview — Full Beginner's Guide
Most candidates fail system design interviews not because they lack knowledge — but because they don't have a clear framework to structure their thinking.
#system-design
Scalability, load balancing, caching, sharding, CAP theorem, monolith versus microservices — the architectural decisions that decide whether your app survives its first growth spurt.
16 posts below, newest first.
Design a Scalable System from Scratch — Full Blueprint (System Design #15)
You've learned the pieces. Now let's put them all together and design a real scalable system from scratch — the way it's done in interviews and in production.
Monolith vs Microservices - Which Architecture Should You Choose? (System
Microservices are everywhere - but are they always the right choice? Spoiler: most teams adopt them too early, and it costs them.
REST vs WebSockets vs SSE - When to Use Each (System Design #13)
Building a chat app? A live dashboard? A REST API? Each needs a completely different communication model - and picking the wrong one is a costly mistake.
Consistent Hashing, Replication & Redundancy - How Distributed Systems Scale
What happens when you add or remove a server from a distributed system? Without consistent hashing, the answer is chaos.
CAP Theorem Explained in 6 Minutes (System Design Interview #11)
CAP Theorem is one of the most misunderstood concepts in distributed systems - and one of the most asked about in FAANG interviews. Let's fix that.
Database Sharding & Indexing - How Big Apps Scale Their Data (System Design #10)
When your database has 500 million rows, queries don't just slow down - they can grind your entire app to a halt. Here's how the biggest systems solve it.
Key-Value, Document, Wide-Column, Graph - 4 NoSQL Types Explained (System
NoSQL is not one thing - it's four completely different data models. Choosing the wrong one is just as bad as choosing SQL when you shouldn't.
SQL vs NoSQL - How to Choose the Right Database (System Design #8)
Picking the wrong database early can haunt your system for years. SQL or NoSQL - here's how to make the right call every time.
FIFO, LIFO, LRU, MRU, LFU - Cache Eviction Policies Explained Simply (System
Your cache is full. Something has to go. But which item do you remove - and does it even matter? The answer can make or break your app's performance.
Write-Through vs Write-Back Cache - Which Should You Use? (System Design #6)
Caching makes systems fast - but it also introduces one of the hardest problems in computer science: keeping your cache and database in sync.
Caching Explained - How Apps Stay Fast Under Heavy Load (System Design #5)
Without caching, even the fastest databases would crumble under real-world traffic. It's one of the most powerful performance tools in any engineer's toolkit.
How Load Balancing Works - Round Robin, Least Connections & More (System
How do systems like Google and Amazon handle millions of users simultaneously without crashing a single server? Load balancing is the answer.
Vertical Scaling vs Horizontal Scaling - What's the Difference? (System Design
Your app is getting more traffic. Do you buy a bigger server - or add more servers? This decision can make or break your system.
Scalability vs Reliability vs Availability - Simply Explained (System Design #2)
What separates a good software system from a bad one? It comes down to 5 key characteristics - and most engineers can't clearly explain all of them.
What Is System Design? A Beginner's Roadmap to Scaling Real Apps
A beginner's roadmap to system design: scalability, availability, load balancing, caching, and monolith vs microservices — with the companion YouTube video.
Related topics
Subjects that frequently appear alongside #system-design. Click through to see every post on each one.
#architecture 16 posts
High-level system architecture — monolith versus microservices, REST versus WebSockets versus SSE, choosing the right database, and shaping software around how it actually has to evolve.
#backend 16 posts
Server-side engineering — databases, APIs, queues, caching, performance, reliability. The unglamorous bits between the keyboard and a system that scales.
#scalability 16 posts
Strategies for making systems handle more load — vertical and horizontal scaling, replication, sharding, caching, load balancing, consistent hashing. The mechanics of growth.
#beginners 1 post
Posts written for people who are new to a topic — minimal jargon, real examples, and the context that more advanced material assumes you already have.