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

Senior
May 2026

Summary

Microsoft SWE interview with a system design question about building a leaderboard. Pretty standard for this kind of role but there's more to it than you'd think once you start pulling on the thread.

Questions Asked (1)

Q1

Design a leaderboard system.

System DesignTechnical Trade-offsData Modeling
Author's notes

Started with the obvious stuff, a sorted list, some kind of score store, but then you realize you need to answer questions like: how often does it update, is it real-time or periodic, how many users are we talking about.

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AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements, such as scale, update frequency, and ranking rules. Then propose a high-level architecture with a real-time leaderboard using Redis sorted sets and a persistent store for durability, and discuss trade-offs between consistency, latency, and cost.

Pro tip: Demonstrate awareness of Microsoft's emphasis on scalability and reliability by discussing how to handle hot keys and sharding in Redis, and how to ensure fault tolerance with replication and fallback mechanisms.

1. Clarify Requirements

Ask questions to understand the expected scale (e.g., millions of users), update frequency (e.g., real-time vs batch), ranking criteria (e.g., score, time), and any constraints like budget or latency.

2. High-Level Design

Outline the main components: an ingestion service to receive score updates, a real-time leaderboard store (e.g., Redis sorted sets), a persistent database for durability, and an API for querying rankings.

3. Deep Dive into Data Modeling

Explain how to model the leaderboard using Redis sorted sets with scores as weights, and how to handle ties, pagination, and range queries efficiently.

4. Scalability and Trade-offs

Discuss sharding strategies for Redis, caching, read replicas, and trade-offs between consistency (e.g., eventual vs strong) and latency. Address hot keys and how to mitigate them.

5. Fault Tolerance and Monitoring

Describe how to ensure high availability with replication, persistence, and fallback to the database. Mention monitoring, alerting, and handling failures gracefully.

Key Points to Mention

  • Use Redis sorted sets for O(log N) insertions and O(log N + M) range queries.
  • Sharding by user ID or leaderboard ID to distribute load and avoid hot keys.
  • Persistence strategy: periodic snapshots or write-ahead logs to a database like Cosmos DB or SQL.
  • Trade-offs: strong consistency vs eventual consistency, and how to handle stale reads.
  • Pagination and ranking queries: using ZREVRANGE and ZRANK for efficient retrieval.
  • Caching and read replicas to handle high read throughput.

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