Design the YouTube Video Streaming Service

To design a YouTube-like service for Netflix, I first establish requirements: supporting 100 million daily active users with sub-second start times globally. We need to handle massive ingestion spikes during content launches. The architecture starts with an ingestion service where creators upload raw files. These are immediately queued into a distributed task queue like Kafka. Worker nodes consume these tasks, triggering a multi-stage transcoding pipeline. We convert uploads into multiple resolutions (360p to 4K) using codecs like VP9 or AV1 to balance quality and bandwidth. Each variant is segmented into small chunks, typically HLS or DASH format, enabling adaptive bitrate streaming. For storage, we use object storage like S3 for originals and a tiered approach for segments. The critical component is the CDN. We distribute segments to edge nodes worldwide, ensuring users fetch content from the nearest location. To prevent cache misses, we implement intelligent prefetching based on trending data. For discovery, a real-time recommendation engine analyzes watch history to suggest content before playback even begins. Finally, we ensure reliability through redundant transcoding clusters and automatic failover mechanisms, guaranteeing that a single worker failure doesn't impact the user experience.