This one took me a while to fully internalize.
Start by clarifying requirements and constraints, then outline a high-level architecture with core components (subscription manager, news ingester, publisher). Dive into data structures and algorithms for efficient matching and delivery, and discuss trade-offs around consistency, scalability, and latency.
Pro tip: Emphasize idempotency and failure recovery in publish cycles, as real-world systems must handle partial failures and retries without duplicate deliveries. Also, proactively discuss how you would test and monitor the system to ensure reliability.
Ask questions to understand scale (number of subscribers, news volume), delivery guarantees (at-least-once, exactly-once), latency expectations, and consistency needs. Confirm functional requirements: add/remove subscriptions, ingest news, publish cycles with per-cycle limits.
Define entities: Subscriber, Subscription (topic, limit), NewsItem (topics, content). Choose data stores: e.g., a relational DB for subscriptions and a document store or queue for news. Outline services: SubscriptionService, NewsIngestionService, PublisherService.
For each cycle, fetch eligible news (matching subscriber topics, not yet delivered, within per-cycle limit). Use efficient indexing (e.g., inverted index on topics) to find matching subscribers. Implement delivery with idempotency keys and track delivery status.
Discuss partitioning (e.g., by subscriber or topic), caching, and asynchronous processing. Handle failures with retries, dead-letter queues, and idempotent operations. Consider rate limiting and backpressure.
Compare SQL vs NoSQL, push vs pull delivery, batch vs real-time. Mention monitoring, metrics, and potential optimizations like precomputed digests or machine learning for relevance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.