5 ms·

Some other data points: * Animoto was running several thousands of machines in 2008 (http://bit.ly/EDLtt http://bit.ly/EDLtt) * Litmus runs 400 servers (http:

by kehunt 16y ago

Some other data points: * Animoto was running several thousands of machines in 2008 (http://bit.ly/EDLtt http://bit.ly/EDLtt) * Litmus runs 400 servers (http://bit.ly/d7Hc7y http://bit.ly/d7Hc7y) * 99Designs runs entirely on EC2 (http://bit.ly/aotKgg http://bit.ly/aotKgg) I've personally had long-running EC2 instances with uptimes in years. You could do it cheaper in terms of hardware, but at the cost of wasting time at the colo while you could be building cool shit.

nethergoat 16y ago
Good start - I wasn't aware of the Litmus environment. The Animoto example is great, I love telling that story to people just starting to look into cloud computing. To add to the large-environment roll call, here are the persistent server counts of some 100% cloud-hosted companies: - Bizo: 100+ instances (I work here) - Reddit: 100(?) instances ("256 Virtual CPUs" http://us.pycon.org/2010/conference/schedule/event/148/ http://us.pycon.org/2010/conference/schedule/event/148/) - HNer jedberg runs this - ShareThis: 250 instances (I worked here) Longest-running instance I've had is at two years and still going strong.
- jedberg 16y ago
  reddit currently has 73 instances with this breakdown: 25 c1.xlarge 26 m1.large 22 m1.xlarge c1.xl are generally app servers, m1.xl are generally databases (either postgres or cassandra) and the m1.l are other stuff.
- grep 16y ago
  Is Reddit profitable?
  - jedberg 16y ago
    We don't discuss that, but Conde isn't a charity. They wouldn't keep us around if it wasn't worthwhile.
jm3 16y ago
[i got permissions from Lachlan Donald at 99 Designs to post his email to me here - jm3] We [at 99 Designs] actually don't have a huge number of instances, although we are steadily adding more and more. We have at present: 2 x Caching Proxies (Large) 8 x App Servers (Large) 3 x DB Servers (High-CPU X-Large) 2 x Workers (Large) We started out with a lot more small instances, but found that the disk performance on the small instances is extremely variable and often terrible. We also use RightScale for management and are at present looking at using server arrays to scale up and down the App Server layer to deal with load spikes. The biggest thing that reduced our need for lots of servers was moving as much functionality to asynchronous tasks as possible, which are queued on each appserver via Beanstalk queues and then consumed by the worker servers. Additionally we have as many pages http cache-able as we can, which are served directly from the squid cache at the front of the app. Hope that helps! Cheers, Lachlan Donald CTO, 99designs

by kehunt 16y ago

nethergoat 16y ago

Good start - I wasn't aware of the Litmus environment. The Animoto example is great, I love telling that story to people just starting to look into cloud computing. To add to the large-environment roll call, here are the persistent server counts of some 100% cloud-hosted companies: - Bizo: 100+ instances (I work here) - Reddit: 100(?) instances ("256 Virtual CPUs" http://us.pycon.org/2010/conference/schedule/event/148/ http://us.pycon.org/2010/conference/schedule/event/148/) - HNer jedberg runs this - ShareThis: 250 instances (I worked here) Longest-running instance I've had is at two years and still going strong.

jedberg 16y ago
reddit currently has 73 instances with this breakdown: 25 c1.xlarge 26 m1.large 22 m1.xlarge c1.xl are generally app servers, m1.xl are generally databases (either postgres or cassandra) and the m1.l are other stuff.
grep 16y ago
Is Reddit profitable?
- jedberg 16y ago
  We don't discuss that, but Conde isn't a charity. They wouldn't keep us around if it wasn't worthwhile.

jm3 16y ago

[i got permissions from Lachlan Donald at 99 Designs to post his email to me here - jm3] We [at 99 Designs] actually don't have a huge number of instances, although we are steadily adding more and more. We have at present: 2 x Caching Proxies (Large) 8 x App Servers (Large) 3 x DB Servers (High-CPU X-Large) 2 x Workers (Large) We started out with a lot more small instances, but found that the disk performance on the small instances is extremely variable and often terrible. We also use RightScale for management and are at present looking at using server arrays to scale up and down the App Server layer to deal with load spikes. The biggest thing that reduced our need for lots of servers was moving as much functionality to asynchronous tasks as possible, which are queued on each appserver via Beanstalk queues and then consumed by the worker servers. Additionally we have as many pages http cache-able as we can, which are served directly from the squid cache at the front of the app. Hope that helps! Cheers, Lachlan Donald CTO, 99designs