System Design
How to shape systems that stay fast and available as they grow.
System design is the practice of translating a requirement into an architecture — the components involved, how they communicate, where data lives, and how the whole thing keeps working when something fails.
- Difficulty
- advanced
- Time
- 15+ hours
- Sections written
- 105
Why it matters
- Every non-trivial feature eventually needs a design decision, not just code — and those decisions are expensive to reverse once built.
- Interviews at the senior level test this directly: estimating scale, choosing storage, and reasoning about failure, not writing algorithms.
- A design that ignores failure modes works in a demo and falls over the first time a dependency is slow or unavailable.
- The vocabulary here — latency, throughput, availability, consistency — is what makes a design conversation precise instead of hand-wavy.
Where it is used
- Architecture and design reviews before a feature is built
- System design interviews for mid-to-senior engineering roles
- Incident retrospectives, tracing a failure back to a design gap
- Capacity planning ahead of a launch or a traffic spike
The big picture
- Requirements — functional + non-functional
- leads to Capacity (sized by)
- Capacity — estimate the scale
- leads to Architecture (shapes)
- Architecture — components, APIs, data model
- leads to Failure handling (must survive)
- Failure handling — what breaks, and then what
- leads to Operations (runs as)
- Operations — scaling, cost, observability