Architect a geo-distributed Ride Matching Engine
Last updated: October 16, 2025
Quick Overview
Design a geo-distributed ride matching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Mastercard
System Design
Software Engineer
Mastercard
October 16, 2025Software Engineer
Onsite
System Design
Easy
9
13
1,498 solved
Design a geo-distributed ride matching system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Mastercard typically last 45-60 minutes. You are expected to drive the conversation, starting from requirements gathering through to a detailed architecture. The interviewer will evaluate your ability to handle ambiguity and make practical engineering decisions.
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
Message queues and async processing
Database selection and data modeling
Consistency models and replication
High-level architecture and component design
API design and rate limiting
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 implement rate limiting to protect the system?
- How would you handle a 10x increase in traffic overnight?
- How do you ensure data consistency across multiple services?
- What would the deployment pipeline look like for this system?
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Requirements
- Functional Requirements:
- Match riders with drivers in real-time based on proximity and preferences.
- Support for multiple types of rides (e.g., carpool, luxury, etc.).
- Provid...
Capacity Estimation
- User Base: Assume 1 million active users, each generating an average of 10 ride requests per day.
- Total Requests: 1 million users * 10 requests = 10 million requests per day, approximate...
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