Design a large-scale Caching Platform
Last updated: September 10, 2025
Quick Overview
Design a scalable caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Datadog
September 10, 202540
4
130 solved
Design a scalable caching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at Datadog. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Datadog values engineers who can think about scalability from day one.
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
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
- What would the deployment pipeline look like for this system?
- How would you optimize costs as the system scales?
- How would you handle schema migrations with zero downtime?
- How would you implement rate limiting to protect the system?
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Requirements
- Functional Requirements:
- Support for caching data with a configurable expiration time.
- Provide APIs for set, get, and delete operations on cached items.
- Enable rate limiting for APIs...
Capacity Estimation
To estimate the capacity required:
- Requests per Second (QPS):
- Assume each user can make up to 100 requests per second.
- If we target 100,000 concurrent users, total QPS = 100 * 100,000 = ...
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