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Microsoft·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Apr 2026

Summary

Microsoft system design round, one question, no fluff. They wanted a full URL shortener walkthrough and I underestimated how deep they'd want to go on the architecture side.

Questions Asked (1)

Q1

How would you design and launch a TinyURL-like URL shortening product?

System DesignTechnical Trade-offsProduct Strategy
Author's notes

Started with the obvious stuff, hashing, redirects, a basic key-value store.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then walk through the high-level system design covering key components like API, database, and caching. Discuss trade-offs in design choices and touch on scalability, reliability, and product considerations such as analytics and custom aliases.

Pro tip: Demonstrate awareness of Microsoft's emphasis on scalable, secure, and compliant systems by mentioning Azure services (e.g., Azure Cosmos DB, Azure Cache for Redis) and discussing how to handle multi-tenancy and data privacy.

1. Clarify Requirements

Ask questions to understand expected scale, read/write ratio, latency requirements, and features like custom aliases, expiration, and analytics.

2. High-Level Design

Outline the core components: API gateway, URL shortening service, database for mappings, cache for hot URLs, and analytics pipeline.

3. Deep Dive into Key Components

Explain the algorithm for generating short codes (e.g., base62 encoding of a counter or hash), database schema, and caching strategy.

4. Address Scalability and Reliability

Discuss partitioning, replication, load balancing, and how to handle failures and ensure high availability.

5. Product and Launch Strategy

Cover features like custom aliases, analytics, rate limiting, and a phased rollout plan with monitoring and feedback loops.

Key Points to Mention

  • Choice of short code generation: base62 encoding of a distributed counter vs. hash-based approach, and collision handling.
  • Database selection: SQL vs. NoSQL, considering read-heavy workload and need for low latency.
  • Caching strategy: using Redis or similar to cache popular URLs and reduce database load.
  • Scalability: horizontal scaling, sharding, and using a CDN for redirects.
  • Security and abuse prevention: rate limiting, spam detection, and safe redirects.
  • Analytics: tracking click counts and referrers without impacting performance.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.