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Blog on All Things Cloud Foundry

Two Powerful Iterator Methods

Emiliano Coppo

Everybody who deals with Ruby knows that collections can be tedious. This post overviews two methods that can greatly simplify you development routines. You will get real-life examples that demonstrate how to optimize the code to make it work fast and look good. You will be given some tips on increasing code readability to simplify system support in the future.

Read the full text of the Two Powerful Iterators article written by Emiliano Coppo, Ruby Developer from our Argentinian team.

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PaaS News Summary: June 2013

Eugene Okhrimenko

Learn about the things that happened in the rapidly changing world of PaaS in June 2013.

Highlights:

• Stratos 2.0: PaaS on almost any IaaS plus multiple clouds at the same time
• Progress released a PaaS for mobile applications
• Quebell’s PaaS allows for changing live apps without compromising stability
• DiscountASP.NET releases a PaaS for .NET applications
• SmartFile offers an IaaS/SaaS toolset for application development
• How to save millions with PaaS
• AppFog purchased by CenturyLink
• OpenShift Online will cost $20 a month
• Engine Yard now supports Windows Azure

(more…)

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Why CoffeeScript

Alena Vasilenko

Developers who are used to object-oriented languages, such as Ruby or Python, may find JavaScript ambiguous. However, it is the only language that is interpreted by browsers. CoffeeScript is an amazing language that compiles into JavaScript and may run even faster than a native JavaScript code. Read the article Why CoffeeScript, written by Nicolas Oga, Ruby Developer from Altoros’s office in Argentina, to learn how this language can help you to write less lines of code as well as keep the code readable and clear. You will know why some people like/don’t like this language and will find some tips on how to make an easier start with CoffeeScript.

Enjoy the full article: Why CoffeeScript!

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Hadoop News Summary: June 2013

Andrei Paleyes

Here is the main Hadoop-related news for June 2013. Learn about the latest events, releases, and developments in the world of distributed computing.

Highlights:

  • Hortonworks Data Platform 2.0 will feature Apache YARN
  • Hadoop deployments can now be managed via vSphere
  • The industry’s first comprehensive Hadoop-as-a-service offering
  • HBaseCon 2013 @ San Francisco, CA
  • Hadoop Summit North America (San Jose, CA)

(more…)

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Speeding up Ruby Tests

Alena Vasilenko

Test driven development is quite a popular thing that allows you to stay on the safe side and be sure that the system works correctly. However, there are some routines that make tests in Ruby really slow. In this post, you will read how to save some precious seconds when you start Ruby on Rails tests. You will learn how to avoid re-starting the tests each time when any changes to a file are made. This post also explains how to check the test coverage of your app.

To learn how to make your Ruby/Ruby on Rails tests work much faster, read the full article.

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Diving into Ember.js: Part 1

Alena Vasilenko


Good news from Nastia Shaternik, a Ruby Developer at Altoros. She prepared a tutorial on how to create an Ember.js application from scratch without any bootstrapping tools. She uploaded the source code, so you could take a look at a commit history to catch on to her idea. This is the first part of the tutorial, the updates will arrive soon!

Find the full version of the article here. Have a nice reading!

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NewSQL News Summary: June 2013

Eugene Okhrimenko

Below is a brief NewSQL news summary for June 2013 from our R&D team. Read on to learn about the latest developments in the world of scalable relational databases.

Highlights:

  • TransLattice and VoltDB Are Now Among Top 100 Companies in Data
  • MemSQL and VoltDB Announce Programming Contests
  • ScaleArc Registers Two Patents
  • 59% of MySQL Users Have or Expect Scalability Issues Within 6–12 Months
  • NuoDB Receives the “Red Herring Top 100” Award

(more…)

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Big Data Analytics 2013 in London Gathered over 550 Attendees, Altoros Was Among Them

Alena Vasilenko

BDA is one of the most prestigious events in UK organized for large enterprises. The business leaders from various industries met to share their experience in dealing with huge volumes of data and using this data intelligently. Data science, advanced data analytics, rich visualization were among the hottest topics discussed. The featured sessions demonstrated how data analysis can increase product quality and profitability, how to monetize data stored in a company, how to address streaming data, social media data, and many other useful insights into the issues posed by data size and complexity.

Many information-driven companies prepared compelling presentations for the seminar part of the event. The attendees could only select one seminar they want to visit, so Altoros competed for the audience with such market leaders as HP, QlickView, 10gen, Telefonica UK, etc.

(more…)

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Which Ruby Framework Is Faster, Sinatra, Espresso, Padrino, Goliath, or Ruby on Rails?..

Eugene Melnikov

There are a number of Ruby frameworks that allow for creating amazing feature-rich applications. However, very often you need some simple functionality and your main goal is to ensure the fastest performance possible. I decided to compare performance of the basic applications that were created with Sinatra, Espresso, Padrino, Goliath, and Ruby on Rails to find out which framework is the fastest one.

See all 4 tables with the performance tests on our Github blog.

Updated: The new version of this performance comparison was released on Feb 7, 2014.

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Hadoop + GPU: Boost Performance of Your Big Data Project by 50x-200x?

Vladimir Starostenkov

Hadoop, an open-source framework that enables distributed computing, has changed the way we deal with big data. Parallel processing with this set of tools can improve performance several times over. The question is, can we make it work even faster? What about offloading calculations from a CPU to a graphics processing unit (GPU) designed to perform complex 3D and mathematical tasks? In theory, if the process is optimized for parallel computing, a GPU could perform calculations 50-100 times faster than a CPU.

Read my article at NetworkWorld to find out what is possible and how you can try this for your large-scale system.

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Benchmarks and Research

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