Start by clarifying requirements (file sizes, connection reliability, scale, latency, consistency) and then walk through the design in a structured way: APIs, data model, storage, processing pipeline, and failure handling. Emphasize trade-offs and justify choices based on the constraints.
Pro tip: Highlight the importance of resumable uploads and idempotency to handle unstable connections and avoid duplicate processing. Also, discuss how to leverage cloud services (e.g., S3 multipart upload) while addressing potential vendor lock-in and cost considerations.
Ask questions to understand scale (e.g., uploads per second, total storage), file size distribution, connection reliability, latency expectations, and consistency requirements. This ensures the design meets actual needs.
Define RESTful APIs for initiating uploads, uploading chunks, completing uploads, and checking status. Design a data model for upload sessions, video metadata, and processing jobs, considering idempotency and resumability.
Select storage solutions (e.g., object storage for raw files, CDN for delivery) and design a processing pipeline (e.g., transcoding, thumbnails) using queues and workers. Discuss trade-offs between managed services and self-hosted.
Describe strategies for handling network failures (resumable uploads, retries with exponential backoff), data integrity (checksums), and idempotent processing. Include monitoring and alerting for failures.
Explain how the design scales horizontally, handles peak loads, and optimizes cost. Compare alternatives (e.g., chunked vs. multipart uploads) and justify decisions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.