The API and functional requirements were already written out in the prompt, so I didn't have to spend time scoping.
Start by clarifying requirements and scale, then design a high-level architecture for video generation with a focus on fault tolerance. Emphasize checkpointing, idempotency, and distributed coordination to handle worker failures during long-running jobs.
Pro tip: Demonstrate maturity by discussing trade-offs between checkpoint frequency and overhead, and how to handle partial failures without restarting entire jobs. Mention that you'd monitor failure rates and use exponential backoff for retries.
Ask about expected job duration, video resolution, throughput, and failure rates. Establish SLAs and consistency requirements.
Outline components: job queue, scheduler, worker pool, storage for checkpoints and outputs, and a metadata database. Explain how jobs are split into stages.
Describe checkpointing (e.g., saving model states and intermediate frames), idempotent operations, and worker health monitoring with heartbeats.
Detail how a failed worker's job is detected, reassigned, and resumed from the last checkpoint. Discuss retry policies and dead-letter queues.
Discuss trade-offs: checkpoint frequency vs. overhead, at-least-once vs. exactly-once semantics, and cost of redundancy. Mention optimizations like adaptive checkpointing.
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