Series · roadmap stage 12/13
The System Design Series
Ten lessons in order, from the mental model to a capstone checklist. Every lesson is structured by us and grounded in a real, cited source from the registry — no invented commands.
10 of 10 lessons published
- Lesson 1 Hold the system design mental model — data systems as tradeoffs
Before any diagram, data systems are tradeoffs, not products. This lesson fixes the vocabulary — reliability, scalability, maintainability, and the six canonical mechanisms behind them — and shows how the canonical chapters map onto systems
- Lesson 2 Run the back-of-envelope drill — numbers before architecture
Estimation is the warm-up act of every design conversation: QPS, storage per day, retention, peak factor, all written down before a single box is drawn. This lesson drills the powers-of-two arithmetic and shows how to ground the numbers in
- Lesson 3 Choose storage engines on tradeoffs — reads, writes, and consistency
Storage choice is where a design's promises become real: the engine you pick decides what replication buys, what partitioning costs, and which consistency semantics your merges get. This lesson builds a decision habit around the DDIA mechan
- Lesson 4 Speak the scaling vocabulary — load balancing, caching, sharding
Scale arguments go wrong when the words do: horizontal versus vertical, cache-aside versus write-through, shard by range versus hash. This lesson fixes the Primer's vocabulary and lines it up with DDIA's partitioning and replication so one
- Lesson 5 Define reliability in numbers — SLIs, SLOs, and error budgets
A design without reliability numbers is a wish. This lesson borrows the SRE toolkit — SLIs, SLOs, error budgets, incident management, postmortems, and capacity planning — and points it at data platforms, where freshness and completeness are
- Lesson 6 Design resilient pipelines — retry, circuit breaker, bulkhead
Failures are inputs, not exceptions. Microsoft's pattern catalogue gives each failure shape a name and a solution — retry, circuit breaker, compensating transaction, bulkhead — and each pattern page carries the considerations that decide wh
- Lesson 7 Read reference architectures like an engineer — AWS as precedent
Reference architectures are precedent, not homework. This lesson teaches a reading method: name the moving parts, find the pillar each choice defends, spot the serverless data lake pattern, and re-state the diagram in DDIA vocabulary so ven
- Lesson 8 Production gotchas — premature scaling and the missing capacity plan
The two self-inflicted design failures: complexity bought before load requires it, and capacity treated as an afterthought until the pager goes off. This lesson puts the SRE discipline of capacity planning next to the pattern catalogue's wa
- Lesson 9 Interview walkthrough — design a data platform end-to-end
The full arc in one 45-minute shape: requirements, back-of-envelope numbers, the storage and scaling argument, reliability as SLIs and budgets, and a deployed precedent to close. Every claim traces to one of the five sources, so nothing in
- Lesson 10 Capstone checklist — a design is done when these all hold
Nine lessons compress into one checklist: tradeoffs named, numbers written, storage chosen by mechanism, scaling lever identified, budget defined, failure patterns assigned, precedent cited. Run it on your next design and on the platform yo