WTF is Elastic Data Grid? (By Example)

Forrester released their new wave report:  The Forrester Wave™: Elastic Caching Platforms, Q2 2010 where they listed GigaSpaces, IBM, Oracle, and Terracotta as leading vendors in the field. In this post I'd like to take some time to explain what some of these terms mean, and why they’re important to you. I’ll start with a definition of Elastic Data Grid (Elastic Caching), how it is different then other caching and NoSQL alternatives, and more importantly -- I'll illustrate how it works through some real code examples.

You can read the full story here.


Hot Scalability Links for June 16, 2010

  • You're Doing it Wrong by Poul-Henning Kamp. Don't look so guilty, he's not talking about you know what, he's talking about writing high-performance server programs: Not just wrong as in not perfect, but wrong as in wasting half, or more, of your performance. What good is an O(log2(n)) algorithm if those operations cause page faults and slow disk operations? For most relevant datasets an O(n) or even an O(n^2) algorithm, which avoids page faults, will run circles around it. 
  • A Microsoft Windows Azure primer: the basics by Peter Bright. Nice article explaining the basics of Azure and how it compares to Google and Amazon.
  • A call to change the name from NoSQL to Postmodern Databases. Interesting idea, but the problem is the same one I have for Postmodern Art, when is it? I always feel like I'm in the post-post modern period, yet for art it's really in the early 1900s. Let's save future developers from this existential time crisis.
  • Constructions from Dots and Lines by Marko A. Rodriguez, Peter Neubauer. Delightful yet in-depth explanation of the complex world of graph data structures. To make use of the graphs beyond simply representing their explicit structure, graph traversal frameworks and algorithms have been developed in order to shape graphs by driving the evolution of the entities that they model—e.g. humans and their relationships to one another and the objects of their world

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How scalable could be a cPanel Hosting service?

Scalability is one of the important words in the web hosting industry. It is more important than the buzz word "cloud". Anyone knows what scalability means, but a very few share the same definition of "Cloud". The purpose of this article is to present a hosting service platform which is both scalable and is "cloud" at the same time.

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The Four Meta Secrets of Scaling at Facebook

Aditya Agarwal, Director of Engineering at Facebook, gave an excellent Scale at Facebook talk that covers their architecture, but the talk is really more about how to scale an organization by preserving the best parts of its culture. The key take home of the talk is: 

You can get the code right, you can get the products right, but you need to get the culture right first. If you don't get the culture right then your company won't scale.

This leads into the four meta secrets of scaling at Facebook:

  1. Scaling takes Iteration
  2. Don't Over Design
  3. Choose the right tool for the job, but realize that your choice comes with overhead.
  4. Get the culture right. Move Fast - break things. Huge Impact - small teams. Be bold - innovate.

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Paper: Propagation Networks: A Flexible and Expressive Substrate for Computation 

Alexey Radul in his fascinating 174 page dissertation Propagation Networks: A Flexible and Expressive Substrate for Computation, offers to help us break free of the tyranny of linear time by arranging computation as a network of autonomous but interconnected machines.  We can do this by organizing computation as a network of interconnected machines of some kind, each of which is free to run when it pleases, propagating  information around the network as proves possible. The consequence of this freedom is that the structure of the aggregate does not impose an order of time. The abstract from his thesis is:

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Sponsored Post: Jobs: Digg, Huffington Post Events: Velocity Conference, Social Developer Summit


Six Ways Twitter May Reach its Big Hairy Audacious Goal of One Billion Users

Twitter has a big hairy audacious goal of reaching one billion users by 2013. Three forces stand against Twitter. The world will end in 2012. But let's be optimistic and assume we'll make it. Next is Facebook. Currently Facebook is the user leader with over 400 million users. Will Facebook stumble or will they rocket to one billion users before Twitter? And lastly, there's Twitter's "low" starting point and "slow" growth rate. Twitter currently has 106 million registered users and adds about 300,000 new users a day. That doesn't add up to a billion in three years. Twitter needs to triple the number of registered users they add per day. How will Twitter reach its goal of over one billion users served?

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Strategy: Cache Larger Chunks - Cache Hit Rate is a Bad Indicator

Isn't the secret to fast, scalable websites to cache everything? Caching, if not the secret sauce of many a website, is it at least a popular condiment. But not so fast says Peter Zaitsev in Beyond great cache hit ratio. The point Peter makes is that we read about websites like Amazon and Facebook that can literally make hundreds of calls to satisfy a user request. Even if you have an awesome cache hit ratio, pages can still be slow because making and processing all those requests takes time. The solution is to remove requests all together. You do this by caching larger blocks so you have to make fewer requests. 

The post has a lot of good advice worth reading: 1) Make non cacheable blocks as small as possible, 2) Maximize amount of uses of the cache item, 3) Control invalidation, 4) Multi-Get.



Hot Scalability Links for June 3, 2010


Web Speed Can Push You Off of Google Search Rankings! What Can You Do?

Google made a right move by adding web-speed to the search engine ranking. With this change site latency does't just impact the user experience but it will determine where you will be placed in google search results.

This move could be a real game changer as it bring site latency and scalability to the front stage. Sites will not only compete on content but on thier performance. It is now clear that site performance have much more direct impact on our business (as appose to indirect impact resulted in user expereince) then ever before.

In this post i try to provide some architecture guide line on how to control and improve site latency under scale based on a discussion with a leading eCommerce site the Netherland.

See detailed story  here