Got through it but the interviewer kept poking at corner cases I hadn't thought through.
Start by clarifying requirements and constraints, then outline a high-level design covering data model, scheduling mechanism, and delivery guarantees. Dive into the core algorithm for efficient scheduling (e.g., priority queue or time wheel) and discuss scalability, reliability, and trade-offs.
Pro tip: Emphasize idempotency and exactly-once delivery semantics, as Stripe deals with financial transactions where duplicate emails could be costly. Also, discuss how to handle failures and retries with exponential backoff and dead-letter queues.
Ask about scale (emails per second), latency requirements, delivery guarantees (at-least-once, exactly-once), and whether emails can be batched. Clarify if scheduling is one-time or recurring, and if there are priorities.
Outline components: API for scheduling, persistent storage for jobs, scheduler service, worker pool for sending, and monitoring. Discuss data model for scheduled emails (id, recipient, content, send_time, status).
Choose an efficient data structure for retrieving due emails, such as a min-heap (priority queue) or time wheel. Discuss how to handle large volumes and persistence (e.g., using Redis sorted sets or a database with indexing on send_time).
Address horizontal scaling of schedulers and workers, partitioning strategies (e.g., by time or user), and ensuring no single point of failure. Discuss idempotency, retries, and dead-letter queues for failed sends.
Discuss trade-offs between different approaches (e.g., polling vs. event-driven, in-memory vs. persistent). Mention potential extensions like rate limiting, user preferences, and analytics.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.