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System Design
GitHub - Coder-World04/Complete-System-Design https://github.com/Coder-World04/Complete-System-Design
A comprehensive GitHub repository covering system design concepts end-to-end: distributed systems fundamentals, CAP theorem, database selection, caching strategies, load balancing, message queues, and interview-ready design walkthroughs for common systems like URL shorteners and social feeds. [→ data-engineering; algorithms-data-structures]
GitHub - Coder-World04/Tech-Interview-Important-Topics-and-Techniques https://github.com/Coder-World04/Tech-Interview-Important-Topics-and-Techniques
A companion repository covering both algorithmic and system design interview topics — data structures, complexity, and distributed system patterns — useful for candidates preparing for L5/L6-level interviews. [→ algorithms-data-structures; data-engineering]
Neo Kim (@systemdesign42): I spent 5+ hours studying how Instagram scaled to 2.5 billion users. https://x.com/systemdesign42/status/1800491019663970354
A detailed tweet thread by system design educator Neo Kim dissecting Instagram’s scaling story: horizontal sharding, cassandra for metadata, S3 for media, CDN strategy, and how they maintained reliability across 2.5 billion monthly users. A dense, high-signal system design reference. [→ data-engineering]
1: TinyURL + PasteBin — Systems Design Interview Questions With Ex-Google SWE 38 minutes https://youtu.be/5V6Lam8GZo4
A 38-minute YouTube video by a former Google SWE walking through URL shortener and paste-bin design interviews: database choice, base62 encoding, caching, and scalability at load. Good entry-level system design walkthrough with clear trade-off reasoning. [→ data-engineering; algorithms-data-structures]
Mike (@cambridgemike): Rearchitecting core services at X https://x.com/cambridgemike/status/1835774409786986572
Thread by Mike (@cambridgemike) on the technical rearchitecture of X (formerly Twitter) post-acquisition: decomposing the monolith, cutting infrastructure costs dramatically, and restructuring services. Provides an insider perspective on large-scale legacy system migration. [→ data-engineering; infrastructure-devops]