This was squarely in my wheelhouse so I didn't freeze or fumble.
Start by clarifying requirements and scale (10M jobs, internal use) to define functional and non-functional needs. Then propose a high-level architecture using a distributed job queue and workers, and dive into data modeling, scheduling, and trade-offs. Emphasize simplicity, reliability, and operational maturity for an internal system.
Pro tip: For internal systems, prioritize operational simplicity and reliability over extreme scalability; leverage existing infrastructure (e.g., Airbnb's own tools) and discuss failure handling and monitoring early.
Ask about job types (batch, recurring, one-off), latency, throughput, priority, dependencies, and failure handling. Confirm scale: 10M jobs total or per day? Internal use implies moderate scale and simpler auth.
Propose a distributed system with a job queue (e.g., Kafka, Redis, or SQS), a scheduler service, and worker pool. Consider a database for job metadata and state, and a coordinator for scheduling.
Design schemas for jobs, schedules, and execution history. Choose appropriate databases (e.g., relational for metadata, NoSQL for logs) and discuss indexing for efficient querying of due jobs.
Explain how jobs are scheduled (e.g., cron, delayed queues), picked up by workers, and executed with retries and idempotency. Discuss concurrency control and rate limiting.
Cover failure detection, retries with backoff, dead-letter queues, and alerting. Discuss metrics (job success rate, latency) and logging for debugging.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.