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Cloud computing is the recent rage in the IT industry. According to the report by Forbes, the estimated global market for cloud computing is expected to reach $35.6 billion in 2015, from the $12.1 billion market of 2010.

How it began

The idea of cloud computing was inspired by the concept of “utility computing” which introduced the idea of computing using the virtual servers. These virtual servers do not actually exist anywhere physically and can be moved anywhere without causing any disturbance to the end users. Thus it minimizes the cost involved on the devices to a great extent and provides innumerable benefits to the companies that adopt this system.

Cloud Computing Types

Is Your Computer Spying on You?

[Feb, 20, 2013] |
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Computers. They’re a part of our everyday lives. Most of us couldn’t imagine living a day without them. We use them for school, work, and fun and use them to stay connected to those we love and care about. Since the invention of the web cam, millions of us use webcams to communicate with loved-ones and business contacts far away.

Web camera use has leveled the playing field for business entrepreneurs and given teenagers a fun way to chat with friends. However, solid citizens aren’t the only ones who make use of this popular modern technology. Recently, there have been reports of criminals using a type of webcam spy hack to insert themselves unseen into the living rooms and bedrooms of millions of unsuspecting users.

The Webcam Spy Hack

The most popular way criminals gain access to your webcam is through innocent-looking emails. You may receive an e-card from someone in your contacts list. When you click on it, you’re directed to another website to view the e-card. While you’re listening to music and watching animated puppies scroll across the screen, a Trojan horse is silently installed into your computer’s hard drive.

Can Python Predict Outcomes Based on Historical Data?

[Sep, 21, 2017] |
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Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Python Programming for Cisco Networking Engineers

[Jun, 25, 2018] |
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Wondering why Cisco is teaching network engineers Python in addition to their core expertise?

Yes, arguably there are many other tools available to use to automate the network without writing any code. It is also true that when code is absolutely necessary, in most companies software developers will write the code for the network engineers. However, networks are getting progressively more sophisticated and the ability for network engineers to keep up with the rate of change, scale of networks, and processing of requirements is becoming more of a challenge with traditional methodologies.

Does that mean that all network engineers have to become programmers in the future? Not completely, but having certain tools in your tool belt may be the deciding factor in new or greater career opportunities. The fact is that current changes in the industry will require Cisco engineers to become proficient in programming, and the most common programming language for this new environment is the Python programming language. Already there are more opportunities for those who can understand programming and can also apply it to traditional networking practices.

Cisco’s current job boards include a search for a Sr. Network Test Engineer and for several Network Consulting Engineers, each with "competitive knowledge" desired Python and Perl skills. Without a doubt, the most efficient network engineers in the future will be the ones who will be able to script their automated network-related tasks, create their own services directly in the network, and continuously modify their scripts.

Whether you are forced to attend or are genuinely interested in workshops or courses that cover the importance of learning topics related to programmable networks such as Python, the learning curve at the very least will provide you with an understanding of Python scripts and the ability to be able to use them instead of the CLI commands and the copy and paste options commonly used. Those that plan to cling to their CLI will soon find themselves obsolete.

As with anything new, learning a programming language and using new APIs for automation will require engineers to learn and master the skills before deploying widely across their network. The burning question is where to start and which steps to take next?

In How Do I Get Started Learning Network Programmability? Hank Preston – on the Cisco blog page suggest a three phase approach to diving into network programmability.

“Phase 1: Programming Basics

In this first phase you need to build a basic foundation in the programmability skills, topics, and technologies that will be instrumental in being successful in this journey. This includes learning basic programming skills like variables, operations, conditionals, loops, etc. And there really is no better language for network engineers to leverage today than Python. Along with Python, you should explore APIs (particularly REST APIs), data formats like JSON, XML, and YAML. And if you don’t have one already, sign up for a GitHub account and learn how to clone, pull, and push to repos.

Phase 2: Platform Topics

Once you have the programming fundamentals squared away (or at least working on squaring them away) the time comes to explore the new platforms of Linux, Docker, and “the Cloud.” As applications are moving from x86 virtualization to micro services, and now serverless, the networks you build will be extending into these new areas and outside of traditional physical network boxes. And before you can intelligently design or engineer the networks for those environments, you need to understand how they basically work. The goal isn’t to become a big bushy beard wearing Unix admin, but rather to become comfortable working in these areas.

Phase 3: Networking for Today and Tomorrow

Now you are ready to explore the details of networking in these new environments. In phase three you will dive deep into Linux, container/Docker, cloud, and micro service networking. You have built the foundation of knowledge needed to take a hard look at how networking works inside these new environments. Explore all the new technologies, software, and strategies for implementing and segmenting critical applications in the “cloud native” age and add value to the application projects.”

Community resources:

GitHub’s, PYPL Popularity of Programming Language lists Python as having grown 13.2% in demand in the last 5 years.

Python in the June 2018 TIOBE Index ranks as the fourth most popular language behind Java, C and C++.

Despite the learning curve, having Python in your tool belt is without a question a must have tool.

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A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

Learn from the experts.
1. We have provided software development and other IT related training to many major corporations in Germany since 2002.
2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
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