I've seen this question floated around so many times that I thought I was prepared.
Start by clarifying requirements and scale (e.g., read/write ratio, latency, availability) to scope the design. Then propose a high-level architecture covering API, data model, and key generation, and dive deep into trade-offs for ID generation and storage. Finally, discuss scaling, caching, and analytics.
Pro tip: Amazon values customer obsession and operational excellence, so emphasize how your design ensures low latency and high availability, and mention monitoring and metrics for continuous improvement.
Ask questions to understand functional and non-functional requirements, such as expected traffic, read/write ratio, latency, and durability. This ensures you design for the right scale and constraints.
Outline the core components: API endpoints (shorten, redirect), a database to store mappings, and a key generation service. Sketch the flow from user request to response.
Discuss approaches for generating short keys (e.g., base62 encoding of auto-increment ID, hash-based, or pre-generated keys). Compare trade-offs like collision handling, predictability, and scalability.
Choose a database (SQL vs NoSQL) based on access patterns and scale. Define the schema (short key, long URL, metadata) and discuss indexing, partitioning, and replication.
Address caching (e.g., Redis for hot URLs), load balancing, and horizontal scaling. Discuss analytics, rate limiting, and handling expired links.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.