The high level design part felt manageable but they very quickly steered toward the ugly stuff.
Start by clarifying requirements and scale, then walk through the end-to-end architecture from request to video delivery, emphasizing the distributed processing pipeline. Dedicate significant time to failure handling, describing detection, recovery, and resilience mechanisms like checkpointing, retries, and graceful degradation.
Pro tip: Frame reliability as a first-class design concern: treat workers as ephemeral and design for failure from the start, using techniques like idempotent operations and checkpointing to enable seamless recovery without recomputing everything.
Ask about expected throughput, latency, video length/resolution, and consistency needs to scope the design. Establish assumptions about scale (e.g., millions of requests per day) and failure tolerance.
Outline the main components: API gateway, request queue, orchestrator, distributed worker pool (GPU/TPU), storage for intermediate artifacts, and CDN for delivery. Explain how a request flows through these components.
Describe the video generation pipeline: text encoding, latent diffusion steps, frame interpolation, upscaling, and encoding. Discuss how work is partitioned (e.g., by frames or diffusion steps) and parallelized across workers.
Explain how to detect worker failures (heartbeats, timeouts), recover (retries, checkpointing, reassignment), and prevent cascading failures (circuit breakers, backpressure). Discuss idempotency and exactly-once semantics.
Discuss trade-offs between latency, cost, and quality; consider spot instances vs. on-demand, preemption handling, and monitoring/alerting. Mention how to scale dynamically and handle heterogeneous hardware.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.