A structured framework for system design interviews at senior and staff engineer levels, with example problems and scoring criteria.
Interviewers are evaluating:
1. Structured thinking -- do you approach open-ended problems methodically?
2. Trade-off reasoning -- do you know why you'd choose Postgres over Cassandra?
3. Scale awareness -- do you understand the difference between 1K and 10M users?
4. Communication -- can you lead a technical discussion clearly?
Functional: What does the system do?
Non-functional: Scale, latency, availability, consistency?
List 3-5 core API endpoints.
Draw the main components: clients, load balancers, API gateway, services, databases, caches.
Common deep dives: database schema, cache invalidation strategy, message queue design, sharding strategy.
Metrics (latency P99, error rate), alerts, logging, distributed tracing.
| Problem | Key Concepts |
|---|---|
| Design URL Shortener | Hashing, redirect, analytics |
| Design Twitter/Instagram Feed | Fan-out, cache, CDN |
| Design WhatsApp | WebSockets, message queuing, delivery receipts |
| Design YouTube | Video transcoding, CDN, object storage |
| Design Uber/Swiggy | Geospatial indexing, real-time matching |
| Design a Rate Limiter | Token bucket, Redis, distributed coordination |
| Design a Distributed Cache | Consistent hashing, eviction policies |
Storage: SQL (ACID, indexing, sharding) vs. NoSQL (eventual consistency, document, wide-column)
Caching: Redis, Memcached; cache-aside vs. write-through; TTL and invalidation
Messaging: Kafka, SQS; pub/sub vs. point-to-point; consumer groups
Consistency: CAP theorem, eventual consistency, quorum reads/writes
L5: Correct architecture with known trade-offs explained.
L6: Proactively identifies failure modes, anticipates interviewer follow-ups, and leads the discussion.
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