A mock system design interview designs a TikTok-style short video platform around S3, CDN and a transcoding pipeline.
Queue the upload, acknowledge with 202The upload API returns only an acknowledgement and the queue absorbs bursts, so creators never wait for processing.
Three data types, three storesS3 for video files, a key value store like MongoDB for changeable metadata, MySQL for relational user data.
Estimate cost and storage earlyGKCS' main criticism: the 1.2 TB per day maths arrived late, which made earlier assumptions feel hesitant.
Executive SummaryAI
GKCS gives Yogita Sharma a 45 minute mock system design interview: build something like TikTok or Instagram Reels, covering how short videos are taken in, stored and distributed.
They fix the scale together — 1 billion downloads with one in 100 watching daily gives 10 million daily active viewers, against roughly 100K creators, so the write to read ratio is about 1 by 100 and reads dominate.
Yogita splits storage three ways: video files in Amazon S3 tied to a CDN with buckets replicated per region, video metadata in a flexible key value or NoSQL store like MongoDB, and user data in MySQL for its relational, tried and tested properties.
The ingest engine queues uploads behind a 202 acknowledgement, then runs a pipeline that validates length, filters the video, splits it into chunks of about 10 seconds and converts them in parallel workers into four formats and several resolutions — 200K videos a day at 1 MB each works out to 200 GB, roughly 600 GB with formats and about 1.2 TB per day with resolutions.
In the feedback GKCS praises the decoupling of ingestion rate from processing rate, the replication and the CDN choice, but says cost estimation should have come early and that hesitancy on network protocols (HTTPS versus FTP) is where an interviewer would dig deeper.
Key Quote
“so what we want to do ideally is uh allow videos only of seven seconds”
— GKCS
Key Quote
“so using a combination of s3 plus cdn to serve files like images and videos is actually a good approach to have low latency”
— Yogita Sharma
Key Quote
“All those things can be stored in a key value store because it will be flexible later on in order to change the schema of the whole metadata, the video metadata that we are storing.”