Build a low-latency Data Pipeline Pipeline
Last updated: October 19, 2025
Quick Overview
Design a low-latency data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Lyft
October 19, 202515
15
3,210 solved
Design a low-latency data pipeline 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 Lyft. 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. Lyft 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
- How would you handle schema migrations with zero downtime?
- What happens if one of your database nodes goes down?
- How would you handle a region-wide outage?
- How would you optimize costs as the system scales?
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Requirements
Functional Requirements
- Data Ingestion: The system should handle millions of data requests per second from various Lyft services (e.g., ride requests, driver updates, user interactions). 2....
Capacity Estimation
To estimate capacity, let's assume:
- User Base: 10 million active users.
- Requests per User: Each user generates about 2 requests per minute on average.
- Total Requests: 10 million user...
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