Update 2: customer support is handled in real-time using Campfire.
Update: highly useful information on creating a customer billing system.

In the giving spirit of Christmas the folks at 37signals have shared a bit about how their system works. 37signals is most famous for loosing Ruby on Rails into the world and they've use RoR to make their very popular Basecamp, Highrise, Backpack, and Campfire products. RoR takes a lot of heat for being a performance dog, but 37signals seems to handle a lot of traffic with relatively normal sounding resources. This is just an initial data dump, they promise to add more details later. As they add more I'll update it here.

This is a wonderfully informative Amazon update based on Joachim Rohde's discovery of an interview with Amazon's CTO. You'll learn about how Amazon organizes their teams around services, the CAP theorem of building scalable systems, how they deploy software, and a lot more. Many new additions from the ACM Queue article have also been included.

Amazon grew from a tiny online bookstore to one of the largest stores on earth. They did it while pioneering new and interesting ways to rate, review, and recommend products. Greg Linden shared is version of Amazon's birth pangs in a series of blog articles

Once upon a time we scaled databases by buying ever bigger, faster, and more expensive machines. While this arrangement is great for big iron profit margins, it doesn't work so well for the bank accounts of our heroic system builders who need to scale well past what they can afford to spend on giant database servers. In a extraordinary two article series, Dathan Pattishall, explains his motivation for a revolutionary new database architecture--sharding--that he began thinking about even before he worked at Friendster, and fully implemented at Flickr. Flickr now handles more than 1 billion transactions per day, responding in less then a few seconds and can scale linearly at a low cost.

What is sharding and how has it come to be the answer to large website scaling problems?

Can you really create an infinitely scalable infrastructure for less than $100 using Amazon's storage, grid, and queuing services platform? It appears so, at least for the right application. Amazon beams a spot light on the future battle of the roll-your-own versus the connect-the-dots approach to building next generation websites using core external services. Their argument is strong. Using Amazon's platform you can quickly build an infrastructure that would otherwise take an eternity to make, a pile of money to create, and an unbounded mass of people to implement and maintain. Yet Amazon doesn't provide SLAs, so you can you really trust them with your crown jewels? Facebook recently leap frogged Amazon's vision with an even more comprehensive set of services. The battle for the future is on.

Update: Digg now receives 230 million plus page views per month and 26 million unique visitors - traffic that necessitated major internal upgrades.

Traffic generated by Digg's over 1.2 million famously info-hungry users can crash an unsuspecting website head-on into its CPU, memory, and bandwidth limits. How does Digg handle all this load?

Update: eBay Serves 5 Billion API Calls Each Month. Aren't we seeing more and more traffic driven by mashups composed on top of open APIs? APIs are no longer a bolt on, they are your application. Architecturally that argues for implementing your own application around the same APIs developers and users employ.

Who hasn't wondered how eBay does their business? As one of the largest most loaded websites in the world, it can't be easy. And the subtitle of the presentation hints at how creating such a monster system requires true engineering: Striking a balance between site stability, feature velocity, performance, and cost.

You may not be able to emulate how eBay scales their system, but the issues and possible solutions are worth learning from.

A man had a dream. His dream was to blend a bunch of RSS/Atom/RDF feeds into a single feed. The man is Beau Lebens of Feedville and like most dreamers he was a little short on coin. So he took refuge in the home of a cheap hosting provider and Beau realized his dream, creating FEEDblendr. But FEEDblendr chewed up so much CPU creating blended feeds that the cheap hosting provider ordered Beau to find another home. Where was Beau to go? He eventually found a new home in the virtual machine room of Amazon's EC2. This is the story of how Beau was finally able to create his one feeds safe within the cradle of affordable CPU cycles.

FeedBurner is a news feed management provider launched in 2004. FeedBurner provides custom RSS feeds and management tools to bloggers, podcasters, and other web-based content publishers. Services provided to publishers include traffic analysis and an optional advertising system.

Update: Flickr hits 2 Billion photos served. That's a lot of hamburgers.

Flickr is both my favorite bird and the web's leading photo sharing site. Flickr has an amazing challenge, they must handle a vast sea of ever expanding new content, ever increasing legions of users, and a constant stream of new features, all while providing excellent performance. How do they do it?

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 second and a stunning 300 million page views a month. They did all this using Ruby on Rails, two part time developers, a cluster of a dozen machines, and a fairly standard architecture. How did Friends for Sale scale to sell all those beautiful people? And how much do you think your friends are worth on the open market?

Friendster is one of the largest social network sites on the web. it emphasizes genuine friendships and the discovery of new people through friends.

Update: Greg Linden points to a new Google article MapReduce: simplified data processing on large clusters. Some interesting stats: 100k MapReduce jobs are executed each day; more than 20 petabytes of data are processed per day; more than 10k MapReduce programs have been implemented; machines are dual processor with gigabit ethernet and 4-8 GB of memory.

Google is the King of scalability. Everyone knows Google for their large, sophisticated, and fast searching, but they don't just shine in search. Their platform approach to building scalable applications allows them to roll out internet scale applications at an alarmingly high competition crushing rate. Their goal is always to build a higher performing higher scaling infrastructure to support their products. How do they do that?

Google Talk is Google's instant communications service. Interestingly the IM messages aren't the major architectural challenge, handling user presence indications dominate the design. They also have the challenge of handling small low latency messages and integrating with many other systems. How do they do it?

Adam Wiggins of Heroku presented at the lollapalooza that was theCloud Computing Demo Night. The idea behind Heroku is that you upload a Rails application into Heroku and it automatically deploys into EC2 and it automatically scales using behind the scenes magic. They call this "liquid scaling." You just dump your code and go. You don't have to think about SVN, databases, mongrels, load balancing, or hosting. You just concentrate on building your application. Heroku's unique feature is their web based development environment that lets you develop applications completely from their control panel. Or you can stick with your own development environment and use their API and Git to move code in and out of their system.

For website developers this is as high up the stack as it gets. With Heroku we lose that "build your first lightsaber" moment marking the transition out of apprenticeship and into mastery. Upload your code and go isn't exactly a heroes journey, but it is damn effective.

I must confess to having an inherent love of Heroku's idea because I had a similar notion many moons ago, but the trendy language of the time was Perl instead of Rails. At the time though it just didn't make sense. The economics of creating your own "cloud" for such a different model wasn't there. It's amazing the niches utility computing will seed, fertilize, and help grow. Even today when using Eclipse I really wish it was hosted in the cloud and I didn't have to deal with all its deployment headaches. Firefox based interfaces are pretty impressive these days. Why not?

Adam views their stack as:

How do you query hundreds of gigabytes of new data each day streaming in from over 600 hyperactive servers? If you think this sounds like the perfect battle ground for a head-to-head skirmish in the great MapReduce Versus Database War, you would be correct.

Bill Boebel, CTO of Mailtrust (Rackspace's mail division), has generously provided a fascinating account of how they evolved their log processing system from an early amoeba'ic text file stored on each machine approach, to a Neandertholic relational database solution that just couldn't compete, and finally to a Homo sapien'ic Hadoop based solution that works wisely for them and has virtually unlimited scalability potential.

Shanti Braford details how his Ruby on Rails based website survived a 24 hour 550,000+ pageview digg attack. His post cleanly lays out all the juicy setup details, so there's not much I can add.

Hosting costs $370 a month for 1 web server, 1 database server, and sufficient bandwidth. The site is built on RoR, nginx, MySQL, and 7 mongrel servers. He thinks Rails 2.0 has improved performance and credits database avoidance and fragment caching for much of the performance boost.

Keep in mind his system is relatively static, but it's a very interesting and useful experience report.

Colm MacCarthaigh, Network Architect at Joost, gave this presentation at the UK Network Operators' Forum Meeting in Manchester on April 3rd, 2007.

Pownce is a new social messaging application competing micromessage to micromessage with the likes of Twitter and Jaiku. Still in closed beta, Pownce has generously shared some of what they've learned so far. Like going to a barrel tasting of a young wine and then tasting the same wine after some aging, I think what will be really interesting is to follow Pownce and compare the Pownce of today with the Pownce of tomorrow, after a few years spent in the barrel. What lessons lie in wait for Pownce as they grow?

A fascinating and detailed story of how LiveJournal evolved their system to scale. LiveJournal was an early player in the free blog service race and faced issues from quickly adding a large number of users. Blog posts come fast and furious which causes a lot of writes and writes are particularly hard to scale. Understanding how LiveJournal faced their scaling problems will help any aspiring website builder.

Update: A fun exploration of applied searching in How to search for the word "pen1s" in 185 emails every second. When indexOf doesn't cut it you just trie harder.

Has a drunken friend ever inspired you to create a first of its kind internet service that is loved by millions, deemed subversive by thousands, all while handling over 1.2 billion emails a year on one rickity old server? That's how Paul Tyma came to build Mailinator.

Mailinator is a free no-setup web service for thwarting evil spammers by creating throw-away registration email addresses. If you don't give web sites you real email address they can't spam you. They spam Mailinator instead :-)

I love design with a point-of-view and Mailinator has a big giant harry one: performance first, second, and last. Why? Because Mailinator is free and that allows Paul to showcase his different perspective on design. While competitors buy big Iron to handle load, Paul uses a big idea instead: pick the right problem and create a design to fit the problem. No more. No less. The result is a perfect system architecture sonnet, beauty within the constraints of form.

How does Mailinator carry out its work as a spam busting super hero?

Mixi is a fast growing social networking site in Japan. They provide services like: diary, community, message, review, and photo album. Having a lot in common with LiveJournal they also developed many of the same approaches. Their write up on how they scaled their system is easily one of the best out there.