replication

Go beyond a single database: learn how read replicas offload query load, how range and hash sharding partition data, why consistent hashing makes rebalancing tractable, and how to pick a shard key that avoids the celebrity problem and cross-shard pain.

How do you scale a database beyond one machine while keeping it reliable? This lesson covers every major replication topology, the quorum math behind leaderless systems, and partitioning strategies from range keys to consistent hashing — including how to avoid hot partitions and handle rebalancing.

Consensus is the hardest fundamental problem in distributed systems — and the one everything else depends on. Understand why FLP makes it theoretically impossible in async systems, how quorums work, and exactly how Raft solves leader election, log replication, and commitment safely.

CAP is the most misquoted theorem in distributed systems. Get the precise statement, learn why PACELC is more useful in practice, and master the consistency spectrum from linearizability down to eventual consistency — with concrete trade-offs for each level.