Design Search Infrastructure for mobile apps
Last updated: April 26, 2026
Quick Overview
Design a low-latency search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Airbnb
System Design
Software Engineer
Airbnb
April 26, 2026Software Engineer
Technical Screen
System Design
Easy
137
12
508 solved
Design a low-latency search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Airbnb 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
- Clearly define functional and non-functional requirements
- Propose a reasonable high-level architecture with core components
- Choose appropriate data storage solutions with basic justification
- Discuss basic scaling strategies (horizontal scaling, caching)
- Identify potential bottlenecks and suggest simple solutions
Key Topics to Cover
Failure handling and fault tolerance
Security and authentication
Requirements gathering and capacity estimation
High-level architecture and component design
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 happens if one of your database nodes goes down?
- What would the deployment pipeline look like for this system?
- How would you migrate from a monolithic to a microservices architecture?
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Requirements
Functional Requirements
- Search Listings: Users should be able to search for listings based on location, date, price range, and amenities.
- Autocomplete Suggestions: As users type in t...
Capacity Estimation
Back-of-Envelope Calculations
- Daily Search Queries: Assuming 10 million search queries per day, that's approximately 115 queries per second (10,000,000 / 86,400 seconds).
- Data Size: If...
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