Draft coverage
This scenario is in the knowledge catalog, but its derived intelligence is not fully modeled yet. Topology relationships are missing. Advisor strengths are not authored. Treat the reference content as useful background, not a complete architecture review.
Summary
A video and audio streaming architecture where content ingestion triggers an async multi-variant transcoding pipeline, CDN delivery handles 95%+ of playback traffic, and Cassandra absorbs the write volume of per-user viewing history. Kafka decouples upload events from transcoding workers; MinIO stores raw and encoded assets; Redis maintains playback session state and view counters. The architecture must handle upload spikes without blocking delivery, and cache cold starts without cascading database load.
Problem Statement
Video platforms have a fundamentally asymmetric I/O profile: writes happen at upload time (large sequential blobs, one writer per upload) but reads happen at playback time (small random segments, millions of concurrent readers). A transcoding pipeline that saturates on upload spikes will delay content availability. A CDN that serves 95% of traffic hides the backend until a cache miss or content update propagates: at that moment, origin servers must absorb a thundering herd without collapsing. Viewing history is write-heavy and time-ordered, making it a poor fit for PostgreSQL at scale, but it must be queryable for recommendations and compliance. The operational challenge is managing these three distinct I/O profiles (upload burst, playback steady-state, history write volume) under a single deployment.
Complexity
high
Maturity
Experienced Backend Team
Patterns
6 patterns
Modeling
draft