Trending Technologies

Automation
Considering that numerous emerging technologies such as cloud computing, big data, artificial intelligence, and robotics are heading for high-scale growth, it is not surprising to see that automation is at its height. Many software consulting firms manage automation deployment right from banking to manufacturing and software companies.
Edge Computing

Edge computing is transforming the way data is being handled, processed, and delivered from millions of devices around the world. The explosive growth of internet-connected devices – the IoT – along with new applications that require real-time computing power, continues to drive edge-computing systems.

Faster networking technologies, such as 5G wireless, are allowing for edge computing systems to accelerate the creation or support of real-time applications, such as video processing and analytics, self-driving cars, artificial intelligence and robotics, to name a few.

For many companies, the cost savings alone can be a driver towards deploying an edge-computing architecture. Companies that embraced the cloud for many of their applications may have discovered that the costs in bandwidth were higher than they expected.

DevOps
DevOps is a term for a group of concepts that, while not all new, have catalyzed into a movement and are rapidly spreading throughout the technical community. Like any new and popular term, people may have confused and sometimes contradictory impressions of what it is. Here’s my take on how DevOps can be usefully defined; I propose this definition as a standard framework to more clearly discuss the various areas DevOps covers. Like “Quality” or “Agile,” DevOps is a large enough concept that it requires some nuance to fully understand.

DevOps is the practice of operations and development engineers participating together in the entire service lifecycle, from design through the development process to production support.

Intelligent apps
Intelligent apps are software applications that make use of AI components such as machine learning, deep learning, data analytics, robotics, and natural language processing. They help you in making decisions based on real-time data or historical data. Examples of Intelligent apps are voice assistants such as Siri, Google Assistant, and Alexa. As companies such as Google, Apple, and Oracle continue investing in these applications, it is bound to create a lot of jobs in the future. Intelligent applications developers are sure to bring home fat paychecks!