System Design Mock Interview for APIs, Scale, and Tradeoffs

Practice architecture with structure

The mock keeps the candidate focused on requirements, APIs, data, services, scale, and failure cases.

Improve explanation quality

System design interviews are judged on communication and tradeoffs, so feedback focuses on clarity as much as diagrams.

How do you design a URL shortener in an interview?

Start with requirements: create a short code for a long URL, redirect quickly, handle high read volume. Define the API (POST /shorten, GET /{code}). For the data model, store code, long URL, owner, and created-at, keyed by a base62 code generated from a counter or hash. Reads dominate, so cache hot codes and put the redirect path behind a CDN. This single example covers API design, data modelling, read/write skew, and caching in one story.

How do you design a rate limiter?

Clarify the limit (for example 100 requests per minute per user) and where it lives (gateway vs service). The token-bucket algorithm refills tokens at a fixed rate and rejects when empty; the sliding-window-counter variant is more accurate at boundaries. Store counters in Redis with a TTL so they expire automatically. Naming the algorithm and the storage tradeoff is exactly the depth interviewers reward.

What order should you follow in a system design interview?

A reliable order is: clarify requirements and constraints, estimate scale, define the API, design the data model, draw the high-level architecture, then go deep on one or two components and their tradeoffs. Interviewers grade structure heavily, and jumping straight to boxes and arrows without requirements is the most common reason strong engineers still fail this round.

How do you do back-of-the-envelope capacity estimation?

You do not need exact numbers, you need defensible ones. Convert daily active users and actions per user into requests per second, then into storage and bandwidth. For example, 10 million writes a day is roughly 115 writes per second average, with peaks several times higher. Showing you can size the system tells the interviewer your design is grounded, not hand-waved.

Tradeoffs you should name out loud

Senior signal comes from naming tradeoffs before the interviewer asks. SQL versus NoSQL, strong versus eventual consistency, sync versus async processing, and cache invalidation are the recurring forks. There is rarely a single right answer; the score comes from justifying your choice against the stated requirements.

Role-aware system design

Backend and full-stack candidates get classic service-and-scale prompts, data engineers get pipeline, warehouse, and streaming designs, and platform or cloud roles get reliability and infrastructure questions. PrepNPlaced can steer the mock toward the flavour your interview will actually use so the practice transfers directly.

Is this only for senior engineers?

No. It can help backend, full-stack, data, cloud, and experienced candidates practice the level expected for their role.

Does it cover databases and scaling?

Yes. The practice flow can cover data models, indexing, cache, queues, consistency, and reliability.

Can I practice explaining my architecture?

Yes. The mock focuses on explanation quality, tradeoffs, and interviewer-style follow-ups.