Click-Trades and Risk Gateways

Designing a rate limiter for trading risk checks

This is a medium-difficulty systems design and implementation problem common at quantitative trading firms. It tests whether you can build a flexible, efficient component that enforces multiple rate-limiting policies simultaneously—a real concern in exchange gateways where protecting against order floods is critical.

The problem requires you to implement three distinct rate-limiting algorithms (fixed window, sliding window, and token bucket), each with different time and space trade-offs. Success means choosing appropriate data structures, managing state cleanly across multiple windows, and ensuring your implementation is thread-safe if the interviewer presses on concurrency. You'll need to reason about which algorithm suits which constraint, handle edge cases around window boundaries, and avoid unnecessary memory overhead.

• Data structure choice (queues, timestamps, counters) and their complexity
• Time window management and boundary conditions
• Token bucket mechanics and refill scheduling
• Multi-algorithm composition and state isolation
• Practical concerns: clock skew, wall-clock time, cleanup of stale data

Interviewers typically expect working code in C++ or Python, with clear separation between the three strategies and a main rate limiter that enforces all of them. Follow-ups often explore latency profiles, memory usage under load, and how the design scales to thousands of concurrent traders.