Greenstone Carbon Management - Services & Solutions - Functional Architecture

The application is built on modular architecture, which is fully scalable and loosely coupled. The architecture allows integration with 3rd party software tools using industry standard processes and managed interfaces. Since this is a web based ASP solution, hence requires no software implementation and maintenance which reduces the overall cost and Go-live time.
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Highscalability.com - eBay Architecture

Update 2: EBay's Randy Shoup spills the secrets of how to service hundreds of millions of users and over two billion page views a day in Scalability Best Practices: Lessons from eBay on InfoQ. The practices: Partition by Function, Split Horizontally, Avoid Distributed Transactions, Decouple Functions Asynchronously, Move Processing To Asynchronous Flows, Virtualize At All Levels, Cache Appropriately.
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.
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Eclipsesource.com - Persistent Trees in git, Clojure and CouchDB

This is a tale of three images. I found these images while investigating the internals of several different applications. There are some really neat software projects emerging at the moment, and as a developer I always find it interesting to take a look at the implementation details, because there is often a lot to be learned. It’s not always something you might need right now, but maybe a few years down the line you may be confronted with a similar problem. Plus – in my opinion – knowing a bit about the internals of a program helps reasoning about its behaviour.
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Facebook Architecture

Facbook Engineering Notes

High Performance at Massive Scale – Lessons learned at Facebook

Jeff Rothschild, Vice President of Technology at Facebook gave a great presentation at UC San Diego on our favorite subject: "High Performance at Massive Scale – Lessons learned at Facebook". The abstract for the talk is:
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Facebook's Memcached Multiget Hole: More machines != More Capacity

When you are on the bleeding edge of scale like Facebook is, you run into some interesting problems. As of 2008 Facebook had over 800 memcached servers supplying over 28 terabytes of cache. With those staggering numbers it's a fair bet to think they've seen their share of Dr. House worthy memcached problems.
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Why are Facebook, Digg, and Twitter so hard to scale?

Real-time social graphs (connectivity between people, places, and things). That's why scaling Facebook is hard says Jeff Rothschild, Vice President of Technology at Facebook. Social networking sites like Facebook, Digg, and Twitter are simply harder than traditional websites to scale. Why is that? Why would social networking sites be any more difficult to scale than traditional web sites? Let's find out.
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Product: Facebook's Cassandra - A Massive Distributed Store

Update 2: Presentation from the NoSQL conference: slides, video.
Update: Why you won't be building your killer app on a distributed hash table by Jonathan Ellis. Why I think Cassandra is the most promising of the open-source distributed databases --you get a relatively rich data model and a distribution model that supports efficient range queries. These are not things that can be grafted on top of a simpler DHT foundation, so Cassandra will be useful for a wider variety of applications.
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Hive - A Petabyte Scale Data Warehouse using Hadoop

This post about using Hive and Hadoop for analytics comes straight from Facebook engineers.

Scalable analysis on large data sets has been core to the functions of a number of teams at Facebook - both engineering and non-engineering. Apart from ad hoc analysis and business intelligence applications used by analysts across the company, a number of Facebook products are also based on analytics.
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Facebook, Hadoop, and Hive

Facebook has the second largest installation of Hadoop (a software platform that lets one easily write and run applications that process vast amounts of data), Yahoo being the first.
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Strategy: Facebook Tweaks to Handle 6 Time as Many Memcached Requests

Our latest strategy is taken from a great post by Paul Saab of Facebook, detailing how with changes Facebook has made to memcached they have:
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Product: Scribe - Facebook's Scalable Logging System


In Log Everything All the Time I advocate applications shouldn't bother logging at all. Why waste all that time and code? No, wait, that's not right. I preach logging everything all the time. Doh. Facebook obviously feels similarly which is why they opened sourced Scribe, their internal logging system, capable of logging 10s of billions of messages per day. These messages include access logs, performance statistics, actions that went to News Feed, and many others.
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Some Facebook Secrets to Better Operations

Kim Nash in an interview with Jonathan Heiliger, Facebook VP of technical operations, provides some juicy details on how Facebook handles operations. Operations is one of those departments everyone runs differently as it is usually an ontogeny recapitulates phylogeny situation. With 2,000 databases, 25 terabytes of cache, 90 million active users, and 10,000 servers you know Facebook has some serious operational issues. What are some of Facebook's secrets to better operations?
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Highscalability.com - Stack Overflow Architecture

Update: Startup – ASP.NET MVC, Cloud Scale & Deployment shows an interesting alternative approach for a Windows stack using ServerPath/GoGrid for a dedicated database machine, elastic VMs for the front end, and a free load balancer.

Stack Overflow is a much loved programmer question and answer site written by two guys nobody has ever heard of before. Well, not exactly. The site was created by top programmer and blog stars Jeff Atwood and Joel Spolsky. In that sense Stack Overflow is like a celebrity owned restaurant, only it should be around for a while. Joel estimates 1/3 of all the programmers in the world have used the site so they must be serving up something good.
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Highscalability.com - Amazon Architecture

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
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Asynchronous Architectures 4

Availability & Consistency

Highscalability.com - Flickr Architecture

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?
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