Design a Scalable Like Counter
Company: Roblox
Role: Software Engineer
Category: System Design
Difficulty: medium
Interview Round: Onsite
Design a large-scale service that stores and serves like counts for content items.
Requirements:
- Users can like and unlike an item.
- Product pages must display the current like count with low latency.
- The system should handle very high write volume, potentially billions of like events per day.
- Duplicate requests and retries must not corrupt the count.
- The design should separate the source-of-truth interaction data from a read-optimized counter store.
- Changes should be propagated between stores using a change-data-capture or event-streaming approach.
- The system should handle hot items, recovery, backfills, and consistency trade-offs.
Describe the APIs, data model, write path, read path, storage choices, scaling strategy, and failure handling.
Quick Answer: This question evaluates a candidate's competence in large-scale system design, covering scalability, high-throughput write handling, read-optimized counter stores, change-data-capture/event streaming, idempotency and duplicate suppression, API and data model design, and failure/recovery strategies.