Design a content processing service
MetaSoftware Engineer · Onsite
Last updated
This question evaluates understanding of designing scalable, reliable content-processing systems that handle high-throughput ingestion, ML-based classification and rule evaluation, priority/backpressure mechanisms, storage and API design, experimentation hooks, and operational concerns like observability and cost.
An interview unexpectedly pivots from coding to system design. Design a high-throughput content processing service for a large-scale media app: (
- Ingest 10M items/day with bursty traffic; (
- Apply ML classification and rules in a near-real-time pipeline with priority queues and backpressure; (
- Choose storage for media and metadata; (
- Expose APIs for upload, review, and appeals; (
- Add A/B testing hooks and offline evaluation; (
- Ensure scalability, fault tolerance, and cost efficiency. Provide a diagram and justify trade-offs.
Solution walkthrough is for members
Get the full walkthrough with reference code and complexity analysis, plus Kitty Coach at 300 messages a day. Hints, the code runner and community answers stay free.