Architect a event-driven Rate Limiting Engine

Last updated: April 6, 2026

Quick Overview

Design a event-driven rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Expedia
System Design
Software Engineer
Expedia
April 6, 2026
Software Engineer
System Design Round
System Design
Easy

10

7

2,400 solved


Design a event-driven rate limiting system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Expedia asks this during the System Design Round to assess your understanding of the full ML lifecycle. They want to see how you translate a business problem into an ML objective, design the feature pipeline, and plan for model monitoring and retraining.

What the Interviewer Expects
  • Map the business problem to a concrete ML objective
  • Propose reasonable features and a baseline model
  • Discuss basic model evaluation metrics
  • Outline a simple serving architecture
Key Topics to Cover
Online vs offline evaluation
Training pipeline and infrastructure
Model serving and latency optimization
ML objective formulation and metric selection
Model selection and architecture
Monitoring and model degradation detection
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
  • What would you do if model performance degrades over time?
  • How would you run A/B tests on different model versions?
  • How would you debug a model that works well offline but poorly online?
  • How would you handle the cold start problem?
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Sample Answer
Requirements Clarification

Before diving into the architecture, clarify the scope with the interviewer. For event-driven Rate Limiting Engine, key functional requirements includ...

Capacity Estimation

Estimate the scale to drive design decisions. Assume 100M DAU with an average of 10 actions per user per day = 1B requests/day ~ 12K QPS average, ~36K...


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