Architect a multi-tenant Search Engine
Last updated: September 2, 2025
Quick Overview
Design a multi-tenant search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Amazon
System Design
Machine Learning Engineer
Amazon
September 2, 2025Machine Learning Engineer
System Design Round
System Design
Medium
14
14
1,693 solved
Design a multi-tenant search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Amazon asks this during the System Design Round 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
- 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
High-level architecture and component design
Database selection and data modeling
Caching strategies (local, distributed, CDN)
Monitoring, logging, and alerting
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 migrate from a monolithic to a microservices architecture?
- How would you handle a region-wide outage?
- How would you handle schema migrations with zero downtime?
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Requirements
- Functional Requirements:
- Support multi-tenancy allowing multiple users (tenants) to perform searches independently.
- Provide real-time search capabilities with auto-suggest and filtering ...
Capacity Estimation
- Estimated QPS (Queries Per Second):
- Assume 10 million searches per day, which translates to approximately 115 QPS (10M/86400 seconds).
- Peak hours may require handling up to 5x this load,...
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