Start by clarifying requirements and constraints, then design a high-level architecture that separates ingestion, processing, and detection layers. Focus on how to partition data to satisfy the two algorithm types: one keyed by trader and one keyed by exchange, ensuring independent scaling and high availability. Discuss trade-offs between consistency, latency, and throughput, and propose a concrete technology stack.
Pro tip: Emphasize that the partitioning strategy is the core challenge: use a message queue with key-based routing (e.g., Kafka) to ensure orders for a given trader or exchange go to the same partition, and design stateless processing instances that can scale horizontally. Also, mention the need for a distributed state store for algorithms that require maintaining state across orders.
Ask about expected throughput (orders per second), latency requirements, data retention, and consistency needs. Confirm that the two algorithm types must be independently scalable and that strong availability is critical.
Propose a layered architecture: ingestion layer (API gateway, load balancers), message queue (e.g., Kafka) for buffering and routing, processing layer (stateless workers for each algorithm type), and storage layer (for state and results). Ensure each layer can scale independently.
Design partitioning to satisfy algorithm requirements: for trader-based algorithms, partition by trader ID; for exchange-based algorithms, partition by exchange ID. Use a message queue with key-based partitioning to route messages to the correct consumer group. Ensure that each partition is processed by a single instance to maintain state consistency.
Explain how to scale each algorithm type independently by adding more consumers/partitions. For high availability, use replication for the message queue and state store, deploy across multiple availability zones, and implement failover mechanisms. Discuss trade-offs between consistency and availability (e.g., CAP theorem).
Choose a distributed state store (e.g., Redis, Cassandra, or a custom in-memory store with replication) for algorithms that need to maintain state across orders. For trader-based algorithms, state can be sharded by trader ID; for exchange-based, by exchange ID. Ensure durability and low-latency access.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.