Design Airbnb Booking System
Last updated: January 8, 2026
Quick Overview
Design the architecture for Airbnb Booking System. Cover scalability, data storage, caching, and real-time requirements.
Airbnb
System Design
Software Engineer
Airbnb
January 8, 2026Software Engineer
Onsite
System Design
Medium
9
7
2,138 solved
Design the architecture for Airbnb Booking System. Cover scalability, data storage, caching, and real-time requirements.
This ML system design question from Airbnb's Onsite tests your ability to think about ML systems at scale. The interviewer expects discussion of data quality, feature stores, model serving infrastructure, and A/B testing strategy.
What the Interviewer Expects
- Define clear ML objectives with appropriate loss functions and metrics
- Design a comprehensive feature engineering pipeline
- Discuss model selection with trade-offs (complexity vs interpretability vs latency)
- Plan online and offline evaluation strategies including A/B testing
- Address serving infrastructure: batch vs real-time, latency requirements
- Consider data quality, labeling strategy, and feedback loops
Key Topics to Cover
Monitoring and model degradation detection
Online vs offline evaluation
ML objective formulation and metric selection
Model serving and latency optimization
A/B testing and experimentation
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 debug a model that works well offline but poorly online?
- How would you handle a 10x increase in prediction requests?
- What is your model retraining strategy?
- What would you do if model performance degrades over time?
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Requirements
Functional Requirements
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Capacity Estimation
Capacity Estimation
Assuming 5 million active users with an average of 20% concurrently browsing:
- Concurrent Users: 1 million
- Search Queries: Each user issues an average of 5 search qu...
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