Design a Caching Service
Last updated: February 1, 2026
Quick Overview
Design a distributed caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
HubSpot
System Design
Software Engineer
HubSpot
February 1, 2026Software Engineer
System Design Round
System Design
Medium
45
13
3,627 solved
Design a distributed caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
HubSpot asks this during the System Design Round to assess your architectural thinking. They want to see how you decompose a complex problem, choose appropriate technologies, and reason about failure modes. Strong candidates proactively discuss monitoring, alerting, and operational concerns.
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
High-level architecture and component design
Message queues and async processing
Caching strategies (local, distributed, CDN)
Partitioning and sharding strategies
Failure handling and fault tolerance
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 a 10x increase in traffic overnight?
- How do you ensure data consistency across multiple services?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
Functional Requirements
- Data Storage: The caching service must store key-value pairs of data with an expiration mechanism.
- Read/Write Operations: It should handle millions of read an...
Capacity Estimation
Back-of-Envelope Calculations
- Traffic Estimates: Assume HubSpot has 1 million active users, with an average of 10 requests per user per hour:
- Total requests per hour = 1,000,000 users ...
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