Build a multi-tenant Feature Flag Pipeline
Last updated: July 23, 2025
Quick Overview
Design a multi-tenant feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
HRT
July 23, 202597
3
4,184 solved
Design a multi-tenant feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at HRT. 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. HRT 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 implement rate limiting to protect the system?
- What would the deployment pipeline look like for this system?
- What happens if one of your database nodes goes down?
- How do you ensure data consistency across multiple services?
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Requirements
Functional Requirements
- Multi-Tenant Support: The system should support multiple tenants (clients) without data leakage between them.
- Feature Flag Creation: Users should be able to c...
Capacity Estimation
Back-of-Envelope Calculations
- User Base: Assume HRT has 1 million users, and each user could potentially make 10 requests per second (QPS) for feature flags.
- Total QPS: This results ...
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