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I started with the basic encode/decode flow and felt pretty good about that part.
Start by clarifying requirements and constraints (e.g., scale, read/write ratio, latency, custom aliases, analytics). Then propose a high-level architecture covering API design, data model, and key components like ID generation, storage, and caching. Finally, dive into trade-offs and optimizations for scalability and reliability.
Pro tip: Demonstrate awareness of Microsoft's emphasis on scalability and reliability by discussing how to handle hot keys and global distribution. Also, mention cost considerations and how to leverage cloud services like Azure for deployment.
Ask questions to understand functional and non-functional requirements: expected traffic (e.g., 100M URLs/day), read/write ratio (e.g., 100:1), latency targets, custom aliases, expiration, analytics, and security.
Outline the core components: API gateway, application servers, ID generator, database, cache, and analytics. Sketch the flow for shortening and redirecting URLs.
Discuss ID generation strategies (e.g., base62 encoding of auto-increment IDs, hash-based, or distributed counters), database schema (key-value store like Redis or Cassandra), and caching for hot URLs.
Address partitioning/sharding, replication, load balancing, and handling failures. Discuss how to avoid single points of failure and ensure low-latency redirects globally.
Compare design choices (e.g., SQL vs NoSQL, pre-generation vs on-demand ID generation) and discuss optimizations like CDN, edge caching, and rate limiting.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.