Subjects

System Design Basics

Learn the fundamental principles behind building large-scale, reliable systems: scalability, availability, latency, and the key trade-offs that drive real-world architecture decisions.

Concurrency vs Parallelism

Untangle four words engineers constantly confuse: concurrency, parallelism, threads, and processes. Learn what runs truly simultaneously versus what merely interleaves, why Python's async model is single-threaded, and how getting this wrong causes real production bugs like sharing one database session across coroutines.

Load Balancing

Understand how load balancers work, the algorithms they use (round-robin, least-connections, IP hash), Layer 4 vs Layer 7 differences, and how to design systems that stay healthy when servers fail.

Consistent Hashing

Understand the hash ring, virtual nodes, and why consistent hashing is the foundation of distributed caches (Redis Cluster, Memcached), distributed databases (Cassandra, DynamoDB), and CDN request routing.

The CAP Theorem

Understand why distributed systems can only guarantee two of Consistency, Availability, and Partition Tolerance — and how real-world databases (Cassandra, Zookeeper, DynamoDB, Postgres) navigate this fundamental constraint.