Build a high-throughput Feature Flag Pipeline
Last updated: February 24, 2026
Quick Overview
Design a high-throughput feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Brex
February 24, 202610
6
2,999 solved
Design a high-throughput feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Brex 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
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 a region-wide outage?
- How would you handle schema migrations with zero downtime?
- How would you implement rate limiting to protect the system?
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Requirements
- Functional Requirements:
- Ability to create, update, and delete feature flags via a RESTful API.
- Support for targeting specific user segments (e.g., by user ID, geography).
- Real-time ...
Capacity Estimation
Assuming Brex has around 1 million active users and each user makes, on average, 10 requests per day regarding feature flags:
- Daily Requests: 1,000,000 users * 10 requests = 10,000,000 requests/...
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