• Technology Trends in IT

    • 13 Feb 2018

    Technology is moving at a speedier pace than at any other time. Pushing forward to 2018, the technologies will experience the hugest change and have the greatest effect on our lives.

    Cloud, mobile and big data have, together, changed the very texture of traditional IT services and programming development. Indeed, even as the worldwide IT industry reevaluates itself to come with new computerized realities, a great many old IT and tech occupations around the globe confront imminent extinction, thus, rest guaranteed, birthing numerous new ones. For techies as of now in their pined for IT occupations and for those nearly beginning their careers, 2018 must be the year of reinventing their insight, abilities and qualifications and popping up for the new employment world, divided by the USD 4.0 trillion cloud computing and big data analytics market.

    Here are top technology trends you will see in 2018:

    1.            Software-defined everything

    Software-defined means the control plane is abstracted from the hardware, and it's going on with every piece of equipment a data center can buy. Software-defined servers are established, software-defined networking is maturing and software-defined storage won't have much impact until at least 2018.

    Don't approach software-defined everything as a cost saving venture, because the real point is agility. Avoid vendor lock-in in this turbulent vendor space, and look for interoperable application programming interfaces that enable data-center-wide abstraction. Also, keep in mind that the legacy data center won't die without a fight.

    Software-defined everything (SDE) is an umbrella term that describes how virtualization and abstracting workloads from the underlying hardware can be used to make information technology (IT) infrastructures more flexible and agile.

    The software-defined data center (SDDC) is one in which all elements of the data center infrastructure -- including networking, storage, CPU and security -- are delivered as a service. An administrator can deploy, provision, configure and manage the infrastructure through software and automate as much work as possible. Many technologies fall the SDE umbrella, including:

    •             Software-defined networking (SDN) - abstracts network architecture to make network devices programmable, allowing the administrator to quickly respond to changing business requirements.

    •             Software-defined storage (SDS) - decouples tasks from physical storage hardware, allowing the administrator to pool and manage storage resources through policies and administered configurations.

    •             Software-defined data center (SDDC) - an analytics-driven approach to balancing the resources that application programs require in virtual and cloud computing environments.  Also called composable infrastructure.

    2.            Big data

    Big data analysis is used in a number of ways to solve problems today. For example, police departments reduce crime without blanketing the city with patrol cars, by pinpointing likely crime hot spots at a given point in time based on real-time and historical data.

    Build new data architectures to handle unstructured data and real-time input, which are disruptive changes today. The biggest inhibitor to enterprise IT adoption of big data analytics, however, isn't the data architecture; it's a lack of big data skills.

    Big data is data sets that are so voluminous and complex that traditional data processing application softwareare inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy. There are five dimensions to big data known as Volume, Variety, Velocity and the recently added Veracity and Value.

    Lately, the term "big data" tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem."[2] Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on." Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, fintech, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.[5]

    3.            Automation

    This trend is nothing new, but the next five years will be transformative for IT automation, from opportunistic to systemic implementation.

    The problem, however, is IT administrators love scripts. They love creating the best scripts, fiddling with scripts that come from colleagues, and leaving little documentation when they move on to another job. IT automation must evolve from scripting to deterministic (defined workloads for tasks) then to heuristic design (automation based on data fed in operations). There are banks today that use heuristic automation because they have all the hardware that you could want. But they lack the ability to automatically place workloads that best at any given moment.

    Start down the heuristic path by appointing an automation leader in IT, automating script discovery and rewarding administrators for building resilient, structured scripts.

    4.            Internet of Things and Internet of Everything

    Is IT in charge of the coffee pot? If it has an IP address and connects to the network, it might be.

    Internet-connected device proliferation combined with big data analytics means that businesses can automate and refine their operations. It also means security takes on a whole new range of end points. In data center capacity management, Internet of Everything means demand shaping and customer priority tiering, rather than simply buying more hardware.

    The Internet of things (IoT) is the network of physical devices, vehicles, home appliances and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these objects to connect and exchange data. Each thing is uniquely identifiable through its embedded computing system but is able to inter-operate within the existing Internet infrastructure.

    Experts estimate that the IoT will consist of about 30 billion objects by 2020. It is also estimated that the global market value of IoT will reach $7.1 trillion by 2020.

    The IoT allows objects to be sensed or controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit in addition to reduced human intervention. When IoT is augmented with sensors and actuators, the technology becomes an instance of the more general class of cyber-physical systems, which also encompasses technologies such as smart grids, virtual power plants, smart homes, intelligent transportation and smart cities.

    "Things," in the IoT sense, can refer to a wide variety of devices such as heart monitoring implants, biochip transponders on farm animals, cameras streaming live feeds of wild animals in coastal waters, automobiles with built-in sensors, DNA analysis devices for environmental/food/pathogen monitoring,] or field operation devices that assist firefighters in search and rescue operations.  Legal scholars suggest regarding "things" as an "inextricable mixture of hardware, software, data and service".

    These devices collect useful data with the help of various existing technologies and then autonomously flow the data between other devices.

    The term "the Internet of things" was coined by Kevin Ashton of Procter & Gamble, later MIT's Auto-ID Center, in 1999

    5.            Mobility

    Your workforce is mobile. Your company's customers are mobile. Bring your own device has morphed into bring your own toys. The IT service desk can't fall behind this trend and risk giving IT a reputation of being out of touch.

    Bring data segregation -- personal and business data and applications isolated from each other on the same device -- onto your technology roadmap now.

    6.            Artificial intelligence.

    (AI) will improve the customer service experience. Clearly, AI is one of the biggest tech trends right now, and anyone with solid tech startup ideas in the area of machine learning has the potential to go after big startup investment rounds, as well as to be acquired by the likes of Google, Salesforce or Apple, all of which have acquired more than 40 tech start-ups related to AI.

    7.            Cyber Security

    Recently, high-profile security breaches and hacks happen so often that they’ve become almost commonplace in today’s digital landscape, leading to cyber security becoming a greater priority for businesses like never before. Even your average consumer has become more aware of the implications of data breaches, meaning that companies will be forced to beef up the security in their products.

    However, with new technologies come new security risks, and staying on top of these innovations can be a challenge. Constant vigilance will be needed to keep up with these new technologies being developed, making cyber security one of the top trends driving the future of information technology.



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