cross-posted from: https://lemmy.nz/post/28397398
The suspension triggered strong responses across social media and beyond. Hashtags like #CancelDisneyPlus and #CancelHulu trended as users shared screenshots of their canceled subscriptions.
With cancellations surging, many subscribers reported technical issues. On Reddit’s r/Fauxmoi, one post read, “The page to cancel your Hulu/Disney+ subscription keeps crashing.”
If your page is just static, e.g. no login, no interaction, everyone always sees the same thing then it scales easily. Scaling means you copy the site to more servers. Now imagine a user adds a comment. Now you need to add the comment to every copy of your site, so that everyone sees it regardless of which server they use. So a comment creates more work the more servers you use. And this is where scaling becomes a complex science, that you need to manually prepare for as a software developer. You need to figure out what data will be stored where and accessed how.
Caching servers, they self replicate when a change is committed, then send back a signal to main server that task has completed
I am not sure what you are trying to say?
Oh right, I skipped a part. It is not really a dev complexity prep issue. You build the database that serves the comments etc in as of in one place, then you deploy cache servers for scaling. They self replicate, so a comment in California gets commited to the dbase, the server in new York pulls the info over from the Cali change, it sends back that it is synced with the change. And vice versa. The caching servers do the work, not your program.
That entirely depends on your application. What you described is one possible approach, that will only work in specific circumstances.
Besides application specifics, its how the internet works currently to give low latency. AWS, Azure, Linode etc have data centers across the globe to replicate data near where the people are.