Topic
System Design
Practice requirements, topology, bottlenecks, tradeoffs, failure modes, and operational constraints as a design loop.
10 Concepts159 Articles48h 32m
Overview
Practice requirements, topology, bottlenecks, tradeoffs, failure modes, and operational constraints as a design loop.
How this topic helps
Distributed Systems
Architecture
Interview Prep
Databases
Learning Path in this Topic
Series that contain articles from System Design. Select a path to filter the article list.
Articles
159 matched articles
Article 1System Design HLD Example: URL Shortener (TinyURL and Bitly)TLDR: A URL shortener is a read-heavy system (100:1 ratio) that maps long URLs to short, unique aliases. The core scaling challenge is generating unique IDs without database contention—solved using a 19 min
Article 2System Design HLD Example: Video Streaming (YouTube/Netflix)TLDR: A video streaming platform is a two-sided architectural beast: a batch-oriented transcoding pipeline that converts raw uploads into multi-resolution segments, and a real-time global delivery net17 minArticle 3System Design HLD Example: Ride-Sharing (Uber/Lyft)TLDR: A ride-sharing platform is a high-velocity geospatial matching engine. Drivers stream GPS coordinates every 5 seconds into a Redis Geospatial Index. When a rider requests a trip, the Matching Se16 minArticle 4System Design HLD Example: Proximity Service (Yelp/Google Places)TLDR: A proximity service (Yelp/Google Places) solves the 2D search problem by encoding locations into Geohash strings, which are indexed in a standard B-tree. To guarantee results near grid boundarie17 minArticle 5System Design HLD Example: Real-Time LeaderboardTLDR: Real-time leaderboards for 10M+ active users require an in-memory ranking engine. Redis Sorted Sets (ZSET) are the industry standard, providing \(O(\log N)\) updates and rank lookups via an inte16 minArticle 6System Design HLD Example: Hotel Booking System (Airbnb)TLDR: A robust hotel booking system must guarantee atomicity in inventory subtraction. The core trade-off is Consistency vs. Availability: we prioritize strong consistency for the booking path (Postgr15 minPage 1 of 27