Roadmap · stage 12/13

System Design

Stage 12 of 13 · 15 resources · 1 categories

What this stage is

System Design is stage 12 of 13 in the DE//AGENT roadmap. It currently holds 15 resources: 10 tutorials, 5 references across 1 category.

Sizing, tradeoffs and communicating an architecture.

Gate: You can whiteboard and defend a data architecture. The stage deliverable: ref-ddia.

Gates are self-assessed — the roadmap does not track your progress; it tells you what to be able to do before moving on.

Sorted by composite score — provenance, completeness and trust, per the scoring model:

Resource	Type	Difficulty	Verification	Score
Hold the system design mental model — data systems as tradeoffs	Tutorial	beginner	community	34.15
Run the back-of-envelope drill — numbers before architecture	Tutorial	beginner	community	34.15
Choose storage engines on tradeoffs — reads, writes, and consistency	Tutorial	intermediate	community	34.15
Define reliability in numbers — SLIs, SLOs, and error budgets	Tutorial	intermediate	community	34.15
Design resilient pipelines — retry, circuit breaker, bulkhead	Tutorial	intermediate	community	34.15
Read reference architectures like an engineer — AWS as precedent	Tutorial	intermediate	community	34.15
Speak the scaling vocabulary — load balancing, caching, sharding	Tutorial	intermediate	community	34.15
Capstone checklist — a design is done when these all hold	Tutorial	advanced	community	34.15
Interview walkthrough — design a data platform end-to-end	Tutorial	advanced	community	34.15
Production gotchas — premature scaling and the missing capacity plan	Tutorial	advanced	community	34.15
AWS Architecture Center	Reference	—	community	27.7
Azure Cloud Design Patterns	Reference	—	community	27.7
Google SRE Books	Reference	—	community	27.7
The System Design Primer	Reference	—	community	27.7
Designing Data-Intensive Applications (O'Reilly)	Reference	—	community	26.7

Frame any data system as a tradeoff among reliability, scalability, and maintainability
Name the six mechanisms DDIA teaches and map each one to a system you operate
Argue a design decision in tradeoff language instead of tool-brand language
Estimate QPS, storage per day, and retention footprint from a workload description
Apply peak-versus-average factors instead of quoting averages alone
Ground an estimate in a real deployed reference architecture
Argue a storage choice from replication, partitioning, and consistency needs
Explain what each consistency semantic means for a merge-based pipeline