System Design: 30 Core Concepts
Master the exact building blocks required for highly scalable, reliable, and fault-tolerant distributed applications. Persisted dual-language implementations in Python & JS.
🌐 Networking & Protocols
Understand socket layers, ports, load balancing strategies, proxy types, HTTP/S boundaries, and full duplex transport channels.
💾 Storage & Database Internals
Demystify replication, sharding mechanisms, indexing algorithms (B-Trees), denormalization, blob caches, and PACELC theory.
⚡ Scale & Reliability
Implement real consistent hashing rings, token bucket rate limiters, Kafka log offset buffers, microservice circuit breakers, and idempotency states.
The Distributed System Cheat Sheet
1. Decouple via Queues: Never call heavy downstream tasks synchronously. Use async broker buffers to survive massive traffic spikes.
2. Index Wisely: B-Trees accelerate sorting and range searches, but slow down writes. Point reads are accelerated via Hash Tables.
3. Partition Everywhere: Distribute dataset rows using consistent hash rings to support infinite horizontal growth without high migration overhead.
4. Fail Gracefully: Wrap microservice HTTP clients in robust circuit breakers with timeouts to prevent cascading network locks.