I know memory is fairly cheap but e.g. there are millions of new videos on youtube everyday, each probably few hundred MBs to few GBs. It all has to take enormous amount of space. Not to mention backups.
I know memory is fairly cheap but e.g. there are millions of new videos on youtube everyday, each probably few hundred MBs to few GBs. It all has to take enormous amount of space. Not to mention backups.
I believe they store and that’s why it processes lowest res first and works up
It’s transposed on the fly, this is a fairly simple lambda function in AWS so whatever the GCP equivalent is. You can’t up sample potato spec, the reason it looks like shit is due to bandwidth and the service determining a lower speed than is available.
Are you suggesting they don’t store different versions? This suggests they do.
At a certain point the cost of compute is going to be cheaper than the cost of storage.
Do you have a source? My instinct is the opposite. Compute scales with users but storage scales with videos
No source but I imagine the amount of videos must be outpacing the amount of users. Users come and go but every uploaded video stays forever.
I think you might be underestimating how many users YouTube has! According to this, 720,000 hours per day are uploaded versus 1,000,000,000 hours are watched per day!
No assumptions about specific usage. Just that at a certain point or in certain scenarios (that I’m sure YouTube’s engineers fully understand), there’s a point where one becomes more cost effective than the other.
Those are pretty incredible numbers though, wow. The scale of that usage is insane.
Consider two cases:
Design a system that optimizes for total cost.
Yeah I replied below with actual numbers