Gartner’s predictions — a look at the top 10 tech trends

Three of Gartner’s top 10 technology trends envision significant changes — and problems — with data centers.

The number of systems managed on premise is on decline, as more work is moved to cloud providers, SaaS vendors and others. But that trend doesn’t mean that an IT manager’s job is getting easier.

“IT shops are realizing that as we move more work off-premise, it makes the job more complex,” said David Cappuccio, the Gartner analyst who develops the research firm’s annual list. He presented it Monday at the this year’s Symposium/ITxpo here in Orlando.

The “Disappearing Data Center” was the top-ranked technology trend. But another point about data centers, “Stranded Capacity” — listed as No. 6 on the list — is closely related.

Gartner, through its user surveys, found that 28% of the physical servers in data centers are “ghost” servers, or what are often called “zombie” servers. These are systems that are in service but not running workloads.

Another problem Gartner found in data centers is that 40% of racks are underprovisioned. That means data center managers are wasting space by not utilizing racks, and might be able to shrink the size of their data centers through better management, said Cappuccio. Servers are also operating at 32% of their performance capacity.

Another data center-related trend, No. 5 on Gartner’s list, was the idea of Data Center-as-a-Service. Instead of thinking about the “data center” as the center of computing resources, managers are seeing their role as a deliverer of services to the business.

Other trends included interconnect fabrics, listed at No. 2, which are increasingly available in multi-tenant data centers. They provide networks that give users access to multiple services, such as the cloud services offered by Google, Amazon and Microsoft, as well as SaaS providers and analytics services. It gives users more flexibility to find the best platform and price, as well as redundancy.

The third top trend concerned the use of containers, microservers and application streams. Virtual machines need an operating system, but containers only require what’s needed to run a specific program. Containers can last weeks, days or seconds — “they drive new ways of looking at development,” said Cappuccio.

In fourth place is “business-driven IT.” Survey data shows that at least 29% of IT spending is outside the IT department. “Business is not willing to wait for IT,” said Cappuccio.

Two of the top 10 trends involved the internet of things (IoT), in particular emerging IoT platforms, which in many cases are incompatible. As for another trend, remote device management — “This could be a major headache,” said Cappuccio.

Micro and edge computing environments is next to last as a trend, and involves putting compute resources in places where they are most needed. That may include installing analytical capabilities at distant worksites that can be managed, for the most part, remotely.

The final trend, as pegged by Gartner, concerned the skills needed to manage emerging environments, including IoT architect, someone to manage cloud sprawl, and a capacity and resource manager.

Gartner

Source: cio.com-Gartner’s predictions — a look at the top 10 tech trends

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Gartner Predicts Our Digital Future

Gartner’s Top 10 Predictions herald what it means to be human in a digital world.

Here’s a scene from our digital future: You sit down to dinner at a restaurant where your server was selected by a “robo-boss” based on an optimized match of personality and interaction profile, and the angle at which he presents your plate, or how quickly he smiles can be evaluated for further review.  Or, perhaps you walk into a store to try on clothes and ask the digital customer assistant embedded in the mirror to recommend an outfit in your size, in stock and on sale. Afterwards, you simply tell it to bill you from your mobile and skip the checkout line.

These scenarios describe two predictions in what will be an algorithmic and smart machine driven world where people and machines must define harmonious relationships. In his session at Gartner Symposium/ITxpo 2016 in Orlando, Daryl Plummer, vice president, distinguished analyst and Gartner Fellow, discussed how Gartner’s Top Predictions begin to separate us from the mere notion of technology adoption and draw us more deeply into issues surrounding what it means to be human in a digital world.

Gartner’s Top Predictions 

1-Robo-writers create content

By 2018, 20 percent of business content will be authored by machines.

Content that is based on data and analytical information will be turned into natural language writing by technologies that can proactively assemble and deliver information through automated composition engines. Content currently written by people, such as shareholder reports, legal documents, market reports, press releases and white papers are prime candidates for these tools.

2-Things will need help

By 2018, 6 billion connected things will be requesting support.

In 2021, 1 million new IoT devices will be purchased every hour of every day. What happens when they require help and support? Organizations will need to develop strategies and mechanisms for responding to things in different ways than when communicate with and problem-solve for people.

3-Agents get independence

By 2020, autonomous software agents outside of human control will participate in 5 percent of all economic transactions.

Algorithmically driven agents already participate in our economy, but are tethered to mechanisms controlled by humans in our corporate, legal, economic, and fiduciary systems. In what Gartner calls the programmable economy, new autonomous software agents will hold value themselves and be set free on the blockchain, capable of banking, insurance, exchanges, and all other types of financial instruments.

4-You work for a robo-boss

By 2018, more than 3 million workers globally will be supervised by a “robo-boss.”

Some performance measurements can be consumed more swiftly by smart machine managers aka “robo-bosses,” who will perform supervisory duties and make decisions about staffing or management incentives.

5-Smart buildings are vandalized

By year-end 2018, 20 percent of smart buildings will have suffered from digital vandalism.

Digital vandals will plunge buildings into darkness or deface signs in exploits that may be more nuisance than threat, but which require adequate perimeter security and a strategy that links building security with the larger organizational security process.

6-More smart machines go to work

By 2018, 45 percent of the fastest-growing companies will have fewer employees than instances of smart machines.

It will happen with startups and new companies first, but the speed, cost savings, and productivity improvements of employing smart machines means that some companies will use machines over human workers, such as in a fully automated supermarket, robotic hotel, or security firm with drone-only surveillance services.

7-Customer digital assistants hold conversations

By year-end 2018, customer digital assistants will recognize individuals by face and voice across channels and partners.

Multichannel customer experience will take a big leap forward with seamless, two-way engagement between customer digital assistants and customers in an experience that will mimic human conversations, with both listening and speaking, a sense of history, in-the-moment context, tone, and the ability to respond.

8-Employees wear trackers

By 2018, 2 million employees will be required to wear health and fitness tracking devices as a condition of employment.

For people whose jobs can be dangerous or physically demanding, wearable devices can provide remote monitoring of heart rates, respiration, and potentially, their stress levels, to send help immediately if required.

9-Smart agents manage our tasks

By 2020, smart agents will facilitate 40 percent of mobile interactions, and the post-app era will begin to dominate.

Instead of using discreet apps, we’ll rely on smart agents in the form of Virtual Personal Assistants (VPA) or newly built business agents to predict our needs, build trust, and act autonomously on our behalf.

10-Customers cause cloud failures

Through 2020, 95 percent of cloud security failures will be the customer’s fault.

Many organizations still harbor security concerns about use of public cloud services. However, only a small percentage of security incidents impacting enterprises using the cloud have been due to vulnerabilities that were the provider’s fault. Customers increasingly will use cloud access security brokers products to manage and monitor their use of SaaS and other forms of public cloud services.

Source: Gartner- Gartner Predicts Our Digital Future

Gartner Identifies the Top 10 Strategic Technology Trends for 2016

Analysts Explore Top Industry Trends at Gartner Symposium/ITxpo 2015, October 4-8 in Orlando

Gartner, Inc. today highlighted the top 10 technology trends that will be strategic for most organizations in 2016. Analysts presented their findings during the sold-out Gartner Symposium/ITxpo, which is taking place here through Thursday.

Gartner defines a strategic technology trend as one with the potential for significant impact on the organization. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization’s long-term plans, programs and initiatives.

“Gartner’s top 10 strategic technology trends will shape digital business opportunities through 2020,” said David Cearley, vice president and Gartner Fellow. “The first three trends address merging the physical and virtual worlds and the emergence of the digital mesh. While organizations focus on digital business today, algorithmic business is emerging. Algorithms — relationships and interconnections — define the future of business. In algorithmic business, much happens in the background in which people are not directly involved. This is enabled by smart machines, which our next three trends address. Our final four trends address the new IT reality, the new architecture and platform trends needed to support digital and algorithmic business.”

The top 10 strategic technology trends for 2016 are:

The Device Mesh
The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses. The device mesh includes mobile devices, wearable, consumer and home electronic devices, automotive devices and environmental devices — such as sensors in the Internet of Things (IoT).

“In the postmobile world the focus shifts to the mobile user who is surrounded by a mesh of devices extending well beyond traditional mobile devices,” said Mr. Cearley.

While devices are increasingly connected to back-end systems through various networks, they have often operated in isolation from one another. As the device mesh evolves, we expect connection models to expand and greater cooperative interaction between devices to emerge.

Ambient User Experience
The device mesh creates the foundation for a new continuous and ambient user experience. Immersive environments delivering augmented and virtual reality hold significant potential but are only one aspect of the experience. The ambient user experience preserves continuity across boundaries of device mesh, time and space. The experience seamlessly flows across a shifting set of devices and interaction channels blending physical, virtual and electronic environment as the user moves from one place to another.

“Designing mobile apps remains an important strategic focus for the enterprise,” said Mr. Cearley. “However, the leading edge of that design is focused on providing an experience that flows across and exploits different devices, including IoT sensors, common objects such as automobiles, or even factories. Designing these advanced experiences will be a major differentiator for independent software vendors (ISVs) and enterprises alike by 2018.”

3D Printing Materials
Advances in 3D printing have already enabled 3D printing to use a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceuticals and biological materials. These innovations are driving user demand, as the practical applications for 3D printers expand to more sectors, including aerospace, medical, automotive, energy and the military. The growing range of 3D-printable materials will drive a compound annual growth rate of 64.1 percent for enterprise 3D-printer shipments through 2019. These advances will necessitate a rethinking of assembly line and supply chain processes to exploit 3D printing.

“3D printing will see a steady expansion over the next 20 years of the materials that can be printed, improvement in the speed with which items can be printed and emergence of new models to print and assemble composite parts,” said Mr. Cearley.

Information of Everything
Everything in the digital mesh produces, uses and transmits information. This information goes beyond textual, audio and video information to include sensory and contextual information. Information of everything addresses this influx with strategies and technologies to link data from all these different data sources. Information has always existed everywhere but has often been isolated, incomplete, unavailable or unintelligible. Advances in semantic tools such as graph databases as well as other emerging data classification and information analysis techniques will bring meaning to the often chaotic deluge of information.

Advanced Machine Learning
In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend.

DNNs (an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear “intelligent.” DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.

Autonomous Agents and Things
Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. While advances in physical smart machines such as robots get a great deal of attention, the software-based smart machines have a more near-term and broader impact. VPAs such as Google Now, Microsoft’s Cortana and Apple’s Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.

“Over the next five years we will evolve to a postapp world with intelligent agents delivering dynamic and contextual actions and interfaces,” said Mr. Cearley. “IT leaders should explore how they can use autonomous things and agents to augment human activity and free people for work that only people can do. However, they must recognize that smart agents and things are a long-term phenomenon that will continually evolve and expand their uses for the next 20 years.”

Adaptive Security Architecture
The complexities of digital business and the algorithmic economy combined with an emerging “hacker industry” significantly increase the threat surface for an organization. Relying on perimeter defense and rule-based security is inadequate, especially as organizations exploit more cloud-based services and open APIs for customers and partners to integrate with their systems. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfill the adaptive security architecture.

Advanced System Architecture
The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. Providing this required boost are high-powered and ultraefficient neuromorphic architectures. Fueled by field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic architectures, there are significant gains to this architecture, such as being able to run at speeds of greater than a teraflop with high-energy efficiency.

“Systems built on GPUs and FPGAs will function more like human brains that are particularly suited to be applied to deep learning and other pattern-matching algorithms that smart machines use,” said Mr. Cearley. “FPGA-based architecture will allow further distribution of algorithms into smaller form factors, with considerably less electrical power in the device mesh, thus allowing advanced machine learning capabilities to be proliferated into the tiniest IoT endpoints, such as homes, cars, wristwatches and even human beings.”

Mesh App and Service Architecture
Monolithic, linear application designs (e.g., the three-tier architecture) are giving way to a more loosely coupled integrative approach: the apps and services architecture. Enabled by software-defined application services, this new approach enables Web-scale performance, flexibility and agility. Microservice architecture is an emerging pattern for building distributed applications that support agile delivery and scalable deployment, both on-premises and in the cloud. Containers are emerging as a critical technology for enabling agile development and microservice architectures. Bringing mobile and IoT elements into the app and service architecture creates a comprehensive model to address back-end cloud scalability and front-end device mesh experiences. Application teams must create new modern architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible and dynamic user experiences that span the digital mesh.

Internet of Things Platforms
IoT platforms complement the mesh app and service architecture. The management, security, integration and other technologies and standards of the IoT platform are the base set of capabilities for building, managing and securing elements in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital mesh and ambient user experience and the emerging and dynamic world of IoT platforms is what makes them possible.

“Any enterprise embracing the IoT will need to develop an IoT platform strategy, but incomplete competing vendor approaches will make standardization difficult through 2018,” said Mr. Cearley.

Source: Gartner-Gartner Identifies the Top 10 Strategic Technology Trends for 2016

 

Top 10 Technology Trends Signal the Digital Mesh

An evolving digital mesh of smart machines will connect billions of things into a continuous digital experience.

We sit at the center of an expanding set of devices, other people, information and services that are fluidly and dynamically interconnected. This “digital mesh” surrounds the individual and new, continuous and ambient experiences will emerge to exploit it. In his session revealing Gartner’s Top 10 Strategic Technology Trends at Gartner/Symposium ITxpo 2015 in Orlando, David Cearley, vice president and Gartner Fellow, shared three categories for this year’s trends: the digital mesh, smart machines, and the new IT reality.

Top10StrTechTrend2016

The Digital Mesh

Trend No. 1: The Device Mesh

Here, all devices such as cars, cameras, appliances, and more are connected in an expanding set of endpoints people use to access applications and information, or interact with people, social communities, governments and businesses. As the device mesh evolves, Gartner expects connection models to expand and greater cooperative interaction between devices to emerge. We will see significant development in wearables and augmented reality, especially,virtual reality.

Trend No. 2: Ambient User Experience

All of our digital interactions can become synchronized into a continuous and ambient digital experience that preserves our experience across traditional boundaries of devices, time and space. Users can interact with an application in a dynamic multistep sequence that may last for an extended period. The experience blends physical, virtual and electronic environments, and uses real-time contextual information as the ambient environment changes or as the user moves from one place to another. Organizations will need to consider their customers’ behavior journeys to shift the focus on design from discreet apps to the entire mesh of products and services involved in the user experience.

Trend No. 3: 3D-Printing Materials

We’ll see continued advances in 3D printing with a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceuticals and biological materials for practical applications expanding into aerospace, medical, automotive, energy and the military.

Recent advances make it possible to mix multiple materials together with traditional 3D printing in one build. This could be useful for field operations or repairs when a specific tool is required and printed on demand. Biological 3D printing — such as the printing of skin and organs — is progressing from theory to reality, however, politicians and the public don’t have a full understanding of the implications.

Smart Machines

Trend No. 4: Information of Everything

Everything surrounding us in the digital mesh is producing, using and communicating with virtually unmeasurable amounts of information. Organizations must learn how to identify what information provides strategic value, how to access data from different sources, and explore how algorithms leverage Information of Everything to fuel new business designs.

Trend No. 5: Advanced Machine Learning

Advanced machine learning is what makes smart machines appear “intelligent” by enabling them to both understand concepts in the environment, and also to learn. Through machine learning a smart machine can change its future behavior. For example, by analyzing vast databases of medical case histories, “learning” machines can reveal previously unknown insights in treatment effectiveness. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.

Trend No. 6: Autonomous Agents and Things

Advanced machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. This feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.

The New IT Reality

Trend No. 7: Adaptive Security Architecture

The complexities of digital business and the algorithmic economy, combined with an emerging “hacker industry,” significantly increase the threat surface for an organization. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks.

Trend No. 8: Advanced System Architecture

The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. They’ll get this added boost from ultra-efficient neuromorphic architectures. Systems built on GPUs and field-programmable gate-arrays (FPGAs) will function more like human brains that are particularly suited to be applied to deep learning and other pattern-matching algorithms that smart machines use. FPGA-based architecture will allow distribution with less power into the tiniest IoT endpoints, such as homes, cars, wristwatches and even human beings.

Trend No. 9: Mesh App and Service Architecture

The mesh app and service architecture are what enables delivery of apps and services to the flexible and dynamic environment of the digital mesh. This architecture will serve users’ requirements as they vary over time. It brings together the many information sources, devices, apps, services and microservices into a flexible architecture in which apps extend across multiple endpoint devices and can coordinate with one another to produce a continuous digital experience.

Trend No. 10: Internet of Things Architecture and Platforms

IoT platforms exist behind the mesh app and service architecture. The technologies and standards in the IoT platform form a base set of capabilities for communicating, controlling, managing and securing endpoints in the IoT. The platforms aggregate data from endpoints behind the scenes from an architectural and a technology standpoint to make the IoT a reality.

Source: gartner-Top 10 Technology Trends Signal the Digital Mesh

Hadoop big data adoption fails to live up to hype, says Gartner

More than half of survey respondents have no plans to deploy the open source analytics platform

Gartner research shows that more than half of companies have no current plans to adopt Hadoop-based data analytics, despite large firms like British Airways and Marks & Spencer being big fans of the technology.

Gartner’s 2015 Hadoop Adoption Study has found that investment remains “tentative” in the face of “sizable challenges around business value and skills”. The survey, which was conducted in February and March 2015 among 284 Gartner Research Circle members, found that only 125 respondents had already invested in Hadoop or had plans to do so within the next two years.

The Gartner Research Circle is a Gartner-managed panel composed of IT and business leaders. “Despite considerable hype and reported successes for early adopters, 54 percent of survey respondents report no plans to invest at this time, while only 18 percent have plans to invest in Hadoop over the next two years,” said Nick Heudecker, an analyst at Gartner.

“Furthermore,” he said, “the early adopters don’t appear to be championing for substantial Hadoop adoption over the next 24 months; in fact, there are fewer who plan to begin in the next two years than already have.”

Hadoop is an open source framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

According to the Gartner research, only 26 percent of respondents claim to be either deploying, piloting or experimenting with Hadoop, while 11 percent plan to invest within 12 months and seven percent are planning investment in 24 months.

Responses pointed to two interesting reasons for the lack of intent, said the analyst. First, several responded that Hadoop was simply “not a priority”. The second was that Hadoop was “overkill” for the problems the business faced, “implying the opportunity costs of implementing Hadoop were too high relative to the expected benefit”, said Gartner.

Gartner analyst Merv Adrian said: “Future demand for Hadoop looks fairly anaemic over at least the next 24 months. Moreover, the lack of near-term plans for Hadoop adoption suggest that despite continuing enthusiasm for the big data phenomenon, demand for Hadoop specifically is not accelerating.

“The best hope for revenue growth for providers would appear to be in moving to larger deployments within their existing customer base.”

Skills gaps were a major adoption inhibitor for 57 percent of respondents, while figuring out how to get value from Hadoop was cited by 49 percent. “The absence of skills has long been a key blocker,” the analyst said. “Tooling vendors claim their products also address the skills gap. While tools are improving, they primarily support highly skilled users rather than elevate the skills already available in most enterprises,” Gartner said.

Gartner estimates it will take “two to three years” for the Hadoop skills challenge to be addressed.

Source: computerworlduk-Hadoop big data adoption fails to live up to hype, says Gartner