Python

Cost Effective, Fast and Scalable: Is It Time You Considered Automated App Deployment?

cbaart

Our approach to software development has changed in the last few years. IT professionals and software developers are working more closely together than ever before. The DevOps trend also extends to an acknowledgement that automation is a key factor in reducing costs and increasing release speeds.

Striving to be cost effective is a constant for any business but the increased focus on speed of deployment is a product of the growth of the Cloud and Agile development methodology. The bottom line is – the faster new features, fixes and improvements reach the customer, the greater their satisfaction. The same principle applies in an enterprise environment – the faster the latest version of an application reaches users, the more productive they can be.

Both environments require scalability. As your product offerings grow and branch out, the delivery method must be capable of handling the changes. In the enterprise environment a large portfolio of software applications is the norm and any deployment solution must be able to scale.

Automated app deployment can reduce costs, increase speed and scale as needed, but before we take a look at the solution let’s discuss the problem.

App Deployment Nightmares

There are a lot of potential problems in deploying applications manually. Not least of which is the time it can consume for developers and IT support. Configuration is the first challenge. Where is the application stored? Which version should be installed? Where should it be installed? Where is the configuration file and how is it applied?

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Sentiment Analysis using Apache Hive

Joris Bontje

Apache Hive is a data warehouse system built on top of Hadoop. Using SQL-like language you can query data stored in the Hadoop filesystem (HDFS). Those queries are then translated into Map Reduce jobs and executed on your cluster.

As an example we’ll analyze tweets from the Twitter Streaming logs and calculate the top 5 hashtags per day which are associated with positive sentiment signals (smileys).

You can imagine how this can be expand this to simple sentiment analysis on your (potential) customer feedback.

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Bundling a Python application on Mac OS X with VirtualEnv

Arjan Molenaar

When it comes to distributing Python packages, Python has its own mechanism. The tooling (either easy_install or pip) allows you to install a Python package and its dependencies. Typically, those packages are installed as Python Eggs (Java has Jars, Ruby has Gems and Python has Eggs). However, one can not expect Mac users to use these command line tools to download and install Python applications, especially GUI applications.

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