Architect a event-driven Search Engine
Last updated: October 7, 2025
Quick Overview
Design a event-driven search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Doordash
October 7, 202549
11
1,123 solved
Design a event-driven search system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during System Design Round at Doordash. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. Doordash values engineers who can think about scalability from day one.
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
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 monitoring and alerting would you set up on day one?
- How would you migrate from a monolithic to a microservices architecture?
- How do you ensure data consistency across multiple services?
- How would you handle schema migrations with zero downtime?
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Requirements
- Functional Requirements:
- Users should be able to search for restaurants and food items in real-time.
- The system must support filtering options (e.g., cuisine type, price range, ratings)....
Capacity Estimation
- User Base: Assume 1 million active users, with each user performing around 10 searches per day.
- Peak Traffic: During peak hours, we estimate that 20% of users are active, leading to:
- *...
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