Master Engineering
Concepts

Database Indexing

Learn how B-tree and hash indexes work internally, how the query planner uses them, when to create composite and covering indexes, and how to diagnose slow queries using EXPLAIN ANALYZE.

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.

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.

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.

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.

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.