System Design
Scaling, caching, consistency, consensus, case studies.
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- Scaling FundamentalsHandle more load with scaling, load balancing, caching, and CDNs — the building blocks of big systems.medium
- Data at ScaleReplication, sharding, the CAP theorem, and choosing consistency vs availability.hard
- Consensus & CoordinationHow a cluster agrees on one truth despite failures — replicated logs, leaders, and quorums.hard
- Case Study: URL ShortenerPut the pieces together — design a URL shortener from requirements to scale.medium
- Case Study: Rate LimiterProtect your services from abuse — design a scalable rate limiter using Token Bucket or Leaky Bucket algorithms.medium
- Message Queues & Async ProcessingDecouple producers from consumers with queues and pub/sub, smooth bursts with buffering, and handle backpressure.medium
- API DesignDesign clean HTTP/REST APIs — resources, verbs, status codes, pagination, idempotency, versioning — and when to reach for gRPC or GraphQL.medium
- Monoliths & MicroservicesSplit a system into services along clean boundaries — weighing independent deploys against distributed complexity.medium
- Caching StrategiesCache-aside, read-through, write-through, write-back — plus TTL, eviction (LRU/LFU), and the hard problem of invalidation.medium