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Dear Stephen,
First of all, I would disagree that amount of followers translates to strain on system. What constitues strain on twitter are two main factors:
1. number of registered users
2. number of messages being exchanged
Twitter, as a messaging system, is dependable on fast read operations, so they need lots of cache, fast middleware and processes working in asynchronous manner. Read more about it here: http://blog.evanweaver.com/articles/2009/03/13/qcon-presentation/
Twitter also recently went from Ruby on back-end to Java and its' framework called Scala. You can find more information here: http://www.artima.com/scalazine/articles/twitter_on_scala.html
This is not the biggest messaging platform in the world, but certainly one of the bigger when you talk about real-time performance. Given the changes twitter recently made to its' software stack, I think for some time being the scaling will be done by simply adding more and faster boxes to server room.
Source(s):
Scaling Twitter Video by Blaine Cook.
Scaling Twitter blog post Patrick Joyce.
Twitter API Traffic is 10x Twitter’s Site.
A Small Talk on Getting Big. Scaling a Rails App & all that Jazz
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Answered Question
M$2
April 17, 2009 06:14 AM
Now that Ashton Kutcher hit the million followers threshold, what sort of stress and strain hits Twitter?
What damage would be caused to Twitter's servers through Ashton Kutcher now having a million followers? What is the stress happening on their servers serving up one tweet to a million people? Could this nuke Twitter?
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| April 17, 2009 06:56 AM | view on twitter |
First of all, I would disagree that amount of followers translates to strain on system. What constitues strain on twitter are two main factors:
1. number of registered users
2. number of messages being exchanged
Twitter, as a messaging system, is dependable on fast read operations, so they need lots of cache, fast middleware and processes working in asynchronous manner. Read more about it here: http://blog.evanweaver.com/articles/2009/03/13/qcon-presentation/
Twitter also recently went from Ruby on back-end to Java and its' framework called Scala. You can find more information here: http://www.artima.com/scalazine/articles/twitter_on_scala.html
This is not the biggest messaging platform in the world, but certainly one of the bigger when you talk about real-time performance. Given the changes twitter recently made to its' software stack, I think for some time being the scaling will be done by simply adding more and faster boxes to server room.
Source(s):
Scaling Twitter Video by Blaine Cook.
Scaling Twitter blog post Patrick Joyce.
Twitter API Traffic is 10x Twitter’s Site.
A Small Talk on Getting Big. Scaling a Rails App & all that Jazz
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Other Answers (2)
April 17, 2009 08:45 AM
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I don't think it will be an issue because it's not like he suddenly got a million followers all at once. His follower number (and that of others) has been over three quarters of a million for awhile now. So, I am sure Twitter can handle it!
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April 17, 2009 12:08 PM
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Nothing compared to when Oprah starts today. My guess is that that will cause more new Twitter users than anything else.
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The only thing that I would add beyond the caching implications is that 140 characters isn't a ton of data.
Also, from what I understand Twitter uses it's own unique blend of techniques that are borrowed from oldskool multicasting. In short, 140 characters is not sent to every user... rather 1 message is available to every user.
The only problem with this level of followers may happen if Ashton undergoes an event that puts an unusual load on the system. For example, lets say that Ashton was involved in a high speed highway getaway after his crazed wife had him locked up in a closet for a week. Well, news like that is going to generate A LOT of interest and as a result, not only could 1 million people be tweeting Ashton to send their best wishes, but quite possibly another million people could suddenly hit his twitter page for updates on the event.
All-in-all, I bet Twitter has some kick-ass network admins that fully understand things like BGP load balancing, caching, etc. A network that is distributed far enough can handle ANY amount of traffic and avoid the dreaded fail whale.