Common foundation

Understand how to approach engineering problems before choosing technologies.

Understand what actually happens inside one machine: CPU caches, memory models, OS I/O, and storage media.

Understand how requests enter, travel through and leave a system: L4/L7 load balancing, TLS, and API gateways.

Measure before scaling. Understand the saturation limits, Little’s Law, and the saturation knee of individual servers.

Learn the computational building blocks behind scalable systems: B+ trees, LSM-trees, Bloom filters, consistent hashing, and sketches.

Understand how storage engines persist, buffer, recover, and isolate concurrent transactions: buffer pools, ARIES WAL, and MVCC.

Understand why distribution creates new correctness and reliability problems: network fallacies, physical clock drift, Lamport timestamps, and vector clocks.

Learn the distributed components used to assemble modern applications: gRPC contracts, transactional outbox & CDC, distributed caching, stream watermarks, and cell topologies.

Learn how data and coordination are replicated, ordered, and partitioned across machines: quorums, linearizability, Raft/Paxos/BFT consensus, auto-sharding, and 2PC/Sagas.

Make systems resilient and secure across global regions: circuit breakers, adaptive rate limiting, active-active WAN replication, and Zero-Trust mTLS.

Inspect how production open-source engines implement storage, consensus, stream processing, sharding, and ingress.

Understand how to operate and maintain real systems: OpenTelemetry tracing, incident triage, chaos testing, zero-downtime deployments, eBPF, and FinOps.