RoR
This a follow-up post to an earlier post on the Scaling Rails Screencast Series by Gregg Pollack, when there were only 13 screencasts, now there are 21. Eight more have been added on topics like load testing and database scaling. This series is of surprisingly high quality. While I didn&
Strategy
Update: Asynchronous HTTP cache validations. A proposed HTTP caching extension: if your application can afford to show slightly out of date content, then stale-while-revalidate can guarantee that the user will always be served directly from the cache, hence guaranteeing a consistent response-time user-experience. Caching is like aspirin for headaches. Head
Example
Update 7: Basecamp, now with more vroom. Basecamp application servers running Ruby code were upgraded and virtualization was removed. The result: A 66 % reduction in the response time while handling multiples of the traffic is beyond what I expected. They still use virtualization (Linux KVM), just less of it now.
Example
Update 6: Some interesting changes from Twitter's Evan Weaver: everything in RAM now, database is a backup; peaks at 300 tweets/second; every tweet followed by average 126 people; vector cache of tweet IDs; row cache; fragment cache; page cache; keep separate caches; GC makes Ruby optimization resistant
Product
Update 4: Heroku versus GAE & GAE/J Update 3: Heroku has gone live!. Congratulations to the team. It's difficult right now to get a feeling for the relative cost and reliability of Heroku, but it's an impressive accomplishment and a viable option for people looking
RoR
This is the intriguing quote by Bill Venners in an interview with Twitter's Alex Payne on Twitter's heretical switch from a pure Ruby stack to a Ruby on Rails stack on the front-end and JVM/Scala on the back-end: So performance was also one of the
RoR
Gregg Pollack has made 13 screen casts on how to scale rails: Episode #1 - Page Responsiveness Episode #2 - Page Caching Episode #3 - Cache Expiration Episode #4 - New Relic RPM Episode #5 - Advanced Page Caching Episode #6 - Action Caching Episode #7 - Fragment Caching Episode
Strategy
Garry Tan, cofounder of Posterous, lists 12 lessons for scaling that apply to more than just Rails. Use cloud storage for static files. Use HTTP Cache Control to tell the browser what it can cache. Use Sphinx for text search. Use InnoDB for more crash resistant and faster writes. Don&
Java
How do you evaluate and decide which web technologies (and there are myriads out there) to use for your new web application, which one potentially gives you the best performance, which one will likely give you the shortest time-to-market? The Apache incubator project Olio might help. Olio is a is
RoR
By George Palmer of 3dogsbark.com. Covers: * How you start out: shared hosting, web server DB on same machine. Move two 2 machines. Minimal code changes. * Scaling the database. Add read slaves on their own machines. Then master-master setup. Still minimal code changes. * Scaling the web server. Load balance against
Example
Several months ago I attended a Joyent presentation where the spokesman hinted that Joyent had the chops to support a one billion page per month Facebook Ruby on Rails application. Even under a few seconds of merciless grilling he would not give up the name of the application. Now we
Example
Update: Jake in Does Django really scale better than Rails? thinks apps like FFS shouldn't need so much hardware to scale. In a short three months Friends for Sale (think Hot-or-Not with a market economy) grew to become a top 10 Facebook application handling 200 gorgeous requests per