Design a high-throughput Caching System
Last updated: November 1, 2025
Quick Overview
Design a high-throughput caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Reddit
System Design
Software Engineer
Software Engineer
Technical Screen
System Design
Medium
7
12
1,686 solved
Design a high-throughput caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Reddit typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
What the Interviewer Expects
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
Failure handling and fault tolerance
Caching strategies (local, distributed, CDN)
High-level architecture and component design
Message queues and async processing
API design and rate limiting
Requirements gathering and capacity estimation
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you handle schema migrations with zero downtime?
- How would you implement rate limiting to protect the system?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements:
- Cache Management: Ability to store, retrieve, and invalidate cache entries efficiently.
- Data Types: Support for various data types, including text, images, a...
Capacity Estimation
Back-of-Envelope Calculations:
- User Base: Assume Reddit has 500 million active users.
- Request Rate: If each user generates an average of 10 requests per day, that leads to about 5 bill...
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