Surge Pricing and Dynamic Pricing System Design Questions
Design considerations for building a scalable, low-latency surge pricing engine and dynamic pricing system within a distributed architecture. Covers data modeling for pricing rules, real-time computation, demand/supply signal integration, multi-region consistency, latency and throughput requirements, caching and cache invalidation strategies, event-driven and microservices approaches, fault tolerance, data synchronization with inventory and orders, feature flags and A/B testing, deployment strategies, monitoring, and reliability concerns.
MediumSystem Design
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Design a distributed rule-evaluation cache that ensures low-latency lookups for computed prices and ensures coherent updates across regions within 5 seconds of a rule change. Describe data flow, storage, invalidation events, and network topology.
HardTechnical
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Design an experiment to evaluate two alternative surge multipliers algorithms under live traffic with minimal revenue risk. Define hypothesis, traffic allocation plan, stopping rules, and how to attribute causality to changes in conversion and revenue.
HardSystem Design
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The customer wants guarantees that pricing changes won't cause cascading failures in downstream billing and fraud systems. Propose architectural isolation patterns, circuit-breakers, and transactional boundaries that prevent a pricing anomaly from corrupting orders or billing.
MediumSystem Design
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You're designing a high-throughput pricing evaluation pipeline that processes streaming events and computes prices for 1M events/second globally. Outline the stream-processing architecture (including ingestion, state stores, windowing), state partitioning strategy, and choices to ensure low-latency per-event processing.
EasyTechnical
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Design a simple API contract (REST or gRPC) for a 'GetPrice' endpoint used by mobile apps to fetch a dynamic price for product X. Define request fields (region, timestamp, user-context), response fields, error codes, and strategies to keep response < 50ms.
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