Build a multi-tenant Feature Flag Pipeline
Last updated: August 30, 2025
Quick Overview
Design a multi-tenant feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Tesla
August 30, 20250
5
1,481 solved
Design a multi-tenant feature flag system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
System design interviews at Tesla 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
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?
- How would you handle a 10x increase in traffic overnight?
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Requirements
Functional Requirements
- Multi-Tenant Support: The system must allow multiple teams to create and manage their own feature flags independently.
- Feature Flag Management: Users should be ...
Capacity Estimation
Assuming Tesla has approximately 100,000 active users across 10 different teams using the feature flag system. If each user checks their feature flags 10 times a day, we anticipate:
- **Total Requests...
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