Design a Rate Limiting for LinkedIn
Last updated: October 16, 2025
Quick Overview
Design a event-driven rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
LinkedIn
System Design
Machine Learning Engineer
Machine Learning Engineer
Technical Screen
System Design
Hard
2
12
3,017 solved
Design a event-driven rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
LinkedIn asks this during the Technical Screen 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
- Drive the design discussion proactively with minimal interviewer guidance
- Perform detailed capacity estimation and use it to inform design decisions
- Design for global scale with multi-region deployment and data consistency
- Deep dive into 2-3 critical components with implementation-level detail
- Address complex trade-offs: CAP theorem, eventual consistency, conflict resolution
- Discuss operational excellence: deployment strategy, chaos engineering, SLOs/SLIs
- Propose a phased rollout plan from MVP to full-scale system
Key Topics to Cover
High-level architecture and component design
Database selection and data modeling
Monitoring, logging, and alerting
Partitioning and sharding strategies
Caching strategies (local, distributed, CDN)
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?
- What happens if one of your database nodes goes down?
- How would you optimize costs as the system scales?
- How would you handle a region-wide outage?
Practice a Similar Problem on Codemia
Solve a related problem with our interactive workspace, get AI feedback, and view detailed solutions.
Solve on CodemiaSample Answer
Requirements
- Functional Requirements:
- Request Tracking: Capture user requests with unique identifiers (e.g., user ID, endpoint) and timestamp.
- Rate Limiting Logic: Implement different r...
Capacity Estimation
- User Base: LinkedIn has approximately 900 million users.
- Request Distribution: Assume 1% of users make requests simultaneously, leading to 9 million requests per second.
- *Peak Load...
Submit Your Answer
Markdown supported