Hyperconvergence Delivers Unexpected Results for VDI Users


The self-help industry is steadily growing due to a basic human desire for improvement

Consumers can find a plethora of books, podcasts, and seminars, not to mention products and services that promise positive change.

IT organizations that want to experience similar improvements can find them by implementing some less than urgent technology makeovers. The results often deliver unexpected and far-reaching benefits. Client virtualization environments stand to benefit more than most because even small improvements in system performance are multiplied across hundreds of desktops.

Technology pilot delivers unexpected performance results

System slowdowns, boot storm delays, and backups or batch jobs that run late into the evening are standard fare in virtual desktop environments. While the situation is not ideal, organizations will often postpone modernization of an aging virtual desktop infrastructure (VDI) as long as it remains functional. This can be a costly mistake. As one IT administrator discovered, a switch to hyperconverged infrastructure (HCI) can lower costs and deliver improvements to end user experience that ripple through the entire company.

In the outdated VDI environment at Maryland Auto Insurance, end users were accustomed to working around performance issues and system limitations, but the systems manager was not satisfied. When it was time for a server refresh, he took a step back and looked at the whole infrastructure. HCI could provide the required reliability and application compatibility, while consolidating the IT footprint in the datacenter. Intrigued, he set up an HCI pilot.

The new system delivered a much higher than expected return. As he put it, his organization didn’t know how slow their system was until they saw what was possible. “We do everything with virtual desktops around here, and the change was remarkable. Outlook and Microsoft Office loaded instantaneously, as did our underwriting and imaging applications. Multitasking was no longer a chore.” The IT team witnessed a growing level of frustration with the existing system. “People would look over their shoulders and see their co-workers in the pilot doing everything faster, and they wanted in.”

Proven Benefits of HCI for VDI

This might seem like an isolated case, but benchmark tests in the industry show similar performance results. Hyperconvergence is a popular choice for VDI because it is modular, efficient, and cost-effective. By converging multiple IT functions into a single server building block, hyperconvergence makes it easy to deploy, manage, and scale infrastructure that supports virtual desktops.

In a recent report, HPE SimpliVity hyperconverged infrastructure powered by Intel® demonstrated high performance in VDI environments. The Login VSI validated study showed consistent, very low latency performance at scale, and plenty of compute and storage resources available to host up to 1,000 knowledge workers. Even during node failure, HPE SimpliVity provided continuity of service with no impact on the end user experience. This kind of speed and resiliency can have a powerful effect on VDI end users and on business operations.

Maryland Auto Insurance reduced their infrastructure from seven racks to just half a rack with HPE SimpliVity, which helped them cut energy consumption nearly in half. They also took advantage of built-in backup, dedupe, and compression features. But the big surprise came in performance benefits, multiplied many times over in the VDI environment. Workloads across their enterprise now are balanced with just a few clicks. Every end user benefits from reduced time to launch applications. And because backups and batch jobs run two to three times faster, the system manager and his team get their evenings back.

If your data center could use improvement, consider HCI. For more information, check out The Gorilla Guide to Hyperconverged Infrastructure Strategy, which includes a chapter focused on VDI.

About the Author

Hyperconvergence Delivers Unexpected Results for VDI Users TechNativeThomas Goepel is the Director Product Management, Hyperconverged Solutions for Hewlett Packard Enterprise. In this role, he is responsible for driving the strategy of HPE’s Hyperconverged products and solutions spanning from the Infrastructure Components to the Management Software. Thomas has over 26 years of experience working in the electronics industry, the last 25 of which at Hewlett Packard Enterprise, where he has held various engineering, marketing and consulting positions in R&D, sales and services. Read more articles by Thomas at HPE Shifting to Software-Defined blog.

Windows Server 2008 End of Support Series


On January 14, 2020, Microsoft will end all support for Windows Server 2008

In the series of videos below, Kyle Todd reminds us of a variety of reasons to upgrade to a newer version before support ends. Sponsored by HPE

In the second clip to highlight the end of support for Windows Server 2008, Kyle Todd explains why enhanced security is one of the biggest reasons to upgrade.

Upgrading to the latest version of Windows Server offers you the chance to capture significant IT efficiency gains, as Kyle Todd explains.

Upgrading to the latest version of Windows Server offers you the chance to leverage the flexibility and deployment strategy that offers the highest value for your applications.

For more information around upgrading, visit the dedicated HPE website.

The Conflict of Tech Innovation and Sustainability

future smart phone green background

Technological advancement has existed throughout human history

Humans have walked the Earth for 200,000 years, inventing countless new processes and systems along the way. The somewhat gradual expansion of human knowledge exploded after the burgeoning of agriculture in the Middle Eastern region of the Levant around 12,000 years ago. Societies at this time manipulated their environment for food-crop cultivation for the first time, inventing sophisticated activities like irrigation and logging.

This nascent field of agriculture created more food and thereby lead to a rapid increase in population size. Yet human expansion also resulted in the increased degradation of the environment. Experts theorise that the mass extinction of megafauna across North America and Australasia was the result of humans rather than environmental factors, while the Mayans were also at fault for causing widespread deforestation and a severe drought through excessive logging, a mistake that brought their eventual demise.

The exploration and proliferation of new technologies is the inevitable result of human intelligence, and the consequences thereof have always been difficult to avoid. Yet our awareness of this damage places humanity in a position of knowledge outside the standard predator-prey relationship that otherwise dominates the world and results in starvation for animals that overeat their food sources.

The current technological dilemmas that we face today are similar to those of ancient time.  Overuse of a resource for immediate human benefit risks longer-term negative influence.  A report conducted by Greenpeace found that Internet data centres have incredibly large carbon footprints, accounting for 3% of global electricity use, much of it in locations that offer cheap, but dirty, electricity. Likewise, the minerals that are found in electronic devices like mobile phones, such as tantalum and gold, often originate from unregulated mining that releases harmful substances into the surrounding soil, air and water. Mining also contributes hugely to deforestation, which is responsible for 15% of global greenhouse gas emissions.

The negative impacts of technological innovation are increasing and action needs to be taken soon to resolve this crisis for the sake of future generations. The Intergovernmental Panel on Climate Change (IPCC) report last month warned that we have just 12 years to reduce the rate of global warming before widespread flooding and droughts become unavoidable. The demand for minerals and energy brought about by technological advancements shows no sign of slowing down, painting a worrying picture for the future of the planet.

Faced with the consequences of our intelligence, humanity now has to use its incredible versatility to overcome the challenges it has created for itself. For example, wind and solar power are increasingly becoming economically-viable sources of unlimited, free electricity and provide us with the opportunity to reduce our dependence on harmful fossil fuels. Bioengineering should help us protect surface soils and the ecosystems that depend on them by maintaining healthy levels of nutrients and soil salinity. Technological advancements will even help us prevent species extinction events that would otherwise destroy our Earth altogether, with NASA already developing spacecraft to push approaching asteroids out of our orbit.

These innovations hold plenty of potential, yet we cannot rely solely on scientists to resolve the conflict of technology and sustainability.  Humans possess the theoretical knowledge to realise our actions are damaging, but have also evolved to think in much shorter timeframes, and created an economy dominated by the next quarterly set of results.  Therefore consumers should make changes to incorporate sustainability into their own lives, choosing to buy products that are ethically sourced or manufactured. Ordinary people should also look to invest in renewable energy where possible, such as by buying solar panels to power their homes. Once sustainable-technology becomes the norm for consumers rather than the exception, tech companies will have greater incentives to adapt their processes to prioritise sustainability.

At its core, technology is neither a sustainability hero or villain. The term is so broad that it encompasses products, systems and processes that both protect the planet and destroy it. The consumption of energy and materials will always be part-and-parcel of technological innovation – that much is clear. Nevertheless, if we change our approach to it in a way that minimises its impact, then the net effect will be positive.

About the Author

The Conflict of Tech Innovation and Sustainability TechNativeAidan Bell is the co-founder of EnviroBuild, a sustainable building materials company based in London. Envirobuild is passionate about sustainable living and specialises in environmentally-friendly building materials that will stand the test of time with minimal harm to the environment.

The Future of Connected Living and Working is Powered by Wireless Charging

Wireless charging

Devices with wireless charging capability rose 40 percent in 2017, compared to the previous year and in all, half a billion devices with wireless charging were shipped last year

But the move to a wireless-world offers so much more than providing a convenient way to keep app-thirsty consumers powered up. Mass deployment of smart wireless charging is a gateway to a new world of connected living and working.

Over the last decade, our lives have been transformed by the rise of the smartphone, together with better access to the internet and new services. We check our mobiles on average every 12 minutes and it would be fair to say our relationship with phones has completely transformed the way we live, work and play. Access to a 3 or 4G network or WiFi is now commonplace and whilst the tech satisfies the need of the always-on, on-demand consumer generation, it is convenient and reliable access to power that provides the critical foundation that enables a fully connected life.

The adoption rate of Qi – the wireless charging standard – parallels Bluetooth and is faster than Wi-Fi – imagining a world without either is near impossible today. So, what’s ahead for wireless charging and what’s really driving the adoption of the technology?

For nearly a decade the wireless charging industry had been in a standards war, initially between three competing technologies. But, in 2017 Apple signalled the end of the battle by adopting the Wireless Power Consortium’s (WPC) Qi standard of charging and it’s a move that created a domino affect across the industry.

This Autumn, the world’s mobile giants – Apple, Google, Huawei – all launched products that will enable consumer experiences like never before proclaiming their commitment to  the wireless world . No more so than Google, who brought back Qi wireless charging capability to its latest Pixel product range and has redefined consumer expectation on powering-up by launching the first commercial smart charging stand – the Pixel Stand. Google had been an early adopter of wireless charging in its Nexus series and whilst the technology remained on the side-lines for the first and second-gen Pixels, it’s now back with a vengeance.

The arrival of the Pixel Stand is an important piece of the jigsaw in Google’s strategy. When the phone connects to the stand, it triggers access to a series of features that transform the phone into a smart display, giving the user easy, seamless access to Google Assistant, a cover art photo album of favourite photos, and integration with the user’s smart-home product with services like the Nest Hello doorbell cam – a significant step away from a dumb docking station to a smart wireless charging hub. It does more than charge without cords, the stand’s functionality transforms the phone’s user experience (UX).

The real gem of the Pixel 3, however, is not just its ability to recognise the Pixel Stand itself, but its ability to tell the difference between specific charging units. Its new and improved smart functionality creates a genuinely intuitive and seamless experience for all mobile users. Let’s look at it like this – you may want Google Assistant to remind you of your meeting schedule whilst you’re frantically getting ready in the morning, but when you’re out for dinner on date night, you’d prefer not to have constant schedule reminders popping up on your screen. Google has built its own solution by embedding a data stream within the wireless charging signal that enables users to pair their phone with particular charges, specifying rules for each.

But, Google isn’t the only one driving the charge for a wireless world. Despite Apple choosing not to release its much-anticipated AirPower charging mat, it signified its move to all things wireless by introducing the tech to all three of its newest iPhones. Whilst Samsung integrated the capability into its mid-range phones making the feature more accessible to those who felt priced-out of Google’s offering… and Huawei, well, Huawei brought us an innovation like no other, a Qi reverse charging capability. These brand commitments signify the move to wireless charging as the norm, offering an essential method to power-up.

All the signs are that businesses are waking up to the fact that wireless charging is here. Workplaces, for example, are integrating smart wireless charging into offices as a response to growing consumer expectation and the demands of the always-on generation. So, it’s little surprise that companies embracing digital workplaces tend to be 21 per cent more profitable, not just because of improved employee wellbeing, but also because new technologies, like smart wireless charging help employers understand their staff and their behaviours better. The expectation of a seamless experience created by consumer tech is influencing employee retention levels as millennials, in particular, are now expecting an intuitive experience across the board.

This expectation will be met by a more connected, smart workspace environment – where, for example, a meeting room is enabled with a wireless charging SmartSpot trigger point that will start video conferences, set personalised atmospheric controls and provide insight on how effectively the office infrastructure is supporting productivity levels – all via smart wireless charging IoT functionality.

Having a fully connected workforce at a businesses’ fingertips will give organisations the opportunity to shape the world around company needs and demands and make their employees’ working day as productive as possible. The opportunity of smart wireless charging is beyond power, it’s about monetising real-time data with a cloud management system and a connected intelligence network that can ultimately improve the bottom line.

There’s no doubt about it – tech talks. This Autumn’s mobile announcements have signified a monumental shift towards a wireless world. Power has now entered the ‘basic requirements’ category, making the shit from a function that is nice-to-have, to one that is a necessity. Making smart wireless charging available is not only crucial in order to keep up with the growing consumer demand, but it also offers businesses an opportunity to monetise by delivering an enhanced and personalised experience. Wireless charging has broken the seal on this immersive era of smart technology – its impact will stretch far beyond what many people can imagine right now. The truth is, we are entering a new era in the digital world and it’s one without a cable in sight.

About the Author

The Future of Connected Living and Working is Powered by Wireless Charging TechNativeDan Bladen is CEO and Co-Founder of Chargifi. Chargifi builds foundational technology that transforms the way the world mass-deploys, manages and monetises power. It delivers a market-leading cloud management platform that enables the mass deployment of smart wireless charging; the patented solution turns wireless power into a service that adds real value for businesses.

All Seeing AI: Video Analytics in Action

Machine Learning object detection and artificial intelligence concept. Application detect object in picture. (Blur human face)

Ubiquitous compute in various form factors has created unimaginably complex and powerful video analysis systems

If you have an iPhone X or a Windows Hello-capable device, like the Surface, you’ll know just how seamless these capabilities can make your experience. These advanced systems, coupled with falling storage costs and better compression algorithms have enabled organisations to capture and analyze a remarkable amount of video. Throw in artificial intelligence tools are now widely used to analyze video without requiring time-intensive human interaction. Modern tools are making video analytics a no brainer in a number of fields.

Theft Prevention

Stores already invest heavily to prevent theft, with burly security guards and CCTV becoming ubiquitous in any mall. But while a few carefully placed cameras can detect nearly all forms of theft, the cost of actively monitoring cameras is high. With video analytics, algorithms derived from modern artificial intelligence systems can detect theft and alert security personnel or law enforcement agents. The ubiquity of cameras, when matched with theft detection systems, will serve as a powerful theft deterrent. People often steal when they’re confident they won’t be caught. Contemporary and upcoming theft detection systems will lead to fewer individuals being willing to risk being caught.


The benefits of theft prevention are clear in retail. However, video analytics can go much further. The role of psychology has long been critical to successful retail stores; knowing where and how to display items for sale can be the difference between profits and losses. Video analytics can provide robust feedback for those running stores, and stores can test various layouts to uncover those that are more successful. When paired with machine learning and other algorithms, retail organizations can uncover previously unexplored ways to raise customer engagement and generate better sales figures. The science behind retail stores is far more mature than many people realize, and the field of video analytics is poised to offer a host of new information.

Manufacturing and Industry

Although the world we inhabit is increasingly going digital, physical items will always be essential. For manufacturing and industry, video analytics offers a compelling suite of new tools. Warehouse management requires a considerable amount of human labor, as inventory management is at the center of successful operations. Armed with video analytics, warehouse managers can rely on automated tracking. Furthermore, analytics tools can find ways to allow warehouses to operate more efficiently, providing a competitive advantage to those who can make the most of the technology. Video monitoring is increasingly being used to detect product faults and find out where the manufacturing process can be further optimized. Predictive maintenance is seeing widespread use, and video analytics can offer data no other tool can replicate.

Public Safety

Video is a powerful tool that can aid public safety, although the technology is not without its own set of controversies. Thanks to facial recognition tools, law enforcement agents can detect when certain individuals are present in an area and can monitor or respond appropriately. It’s growing more difficult to be a fugitive in an era when facial recognition tools have grown so powerful, and law enforcement agencies are expected to rely on the technology more and more in the coming years. Those monitoring for terrorism can note if individuals on watch lists congregate, potentially foiling plans that would have otherwise gone unnoticed. Whether society is willing to accept ubiquitous facial recognition remains to be seen, although many have credited video surveillance, with and without analytics, as one of the reasons violent crime rates have fallen in the United States and elsewhere.


Public transportation systems are the backbones of cities, and video analytics can help detect areas for improvement. Smart systems can automatically count how many people use certain routes, and they can track changes on a continuous basis, unlike more traditional counting methods done on a periodic basis. For areas reliant on personal automobiles, video analytics can provide robust usage data, helping governments determine when roads, bridges, and other infrastructure will need maintenance work. Again, the affect on public safety will be significant and likely controversial. Automatically logging license plates, for example, lets law enforcement agencies detect where and how individuals are traveling, and public transportation systems armed with facial recognition capabilities make it difficult for people to conceal their activities. Benefits, however, will be unambiguous for pedestrians. Tracking how people navigate cities, including roads and other dangerous areas, lets city planners mitigate dangers and implement pedestrian-friendly infrastructure to reduce dangers.


Video and healthcare are a natural combination. Being able to track patients in a health center lets doctors and other providers know where to reach their patients instantly, and it can lead to greater efficiency in hospitals and other busy locations. One specific use case will prove to be especially useful: Monitoring patients with dementia. Those with Alzheimer’s and other conditions are prone to walking away and becoming lost and endangered. With facial recognition, care centers can ensure staff members are alerted if a patient leaves the facility and respond promptly. Video analysis is also being used as a diagnostic tool, a use case that’s become far more popular in recent years. By combining video with analytics tools, healthcare providers can rely on artificial intelligence to aid their diagnostic capabilities. Privacy concerns, however, need to be addressed, as regulations in healthcare are typically substantial.

Digital video once seemed to require far too much data to ever be practical. Today, most of us carry smartphones able to shoot and store a large amount of video, and the Internet of Things has shown that digital cameras are now remarkably inexpensive. While video is becoming ubiquitous, the tools needed to analyze data automatically are coming online quickly, and the benefits to society may prove to be immense. It’s important, however, to consider some of the negative ramifications. How much privacy are people willing to sacrifice for safety and convenience?

Data Quality vs Data Quantity: What’s More Important for AI?

Artificial Mind

Business are enjoying a data revolution

The sheer volume of data being collected from Internet of Things devices has skyrocketed in recent years, and sophisticated artificial intelligence and machine learning tools are able to extract valuable information that would otherwise go unnoticed. However, this glut of data has raised a critical question: How important is the quality of the data being collected?

Artificial intelligence and machine learning can provide remarkable insight. However, AI can’t distinguish between good data and bad data on its own, and the algorithms powering AI can only assume the data being analyzed is reliable. Bad data, at best, will produce results that aren’t actionable or insightful. But there’s an even bigger concern: Bad data can lead to results that are misleading. In addition to the time and money wasted analyzing bad data, AI systems can encourage a company to take steps that are even more wasteful.

Martha Bennett at Forrester believes deriving meaningful insights from data is key to staying competitive.

One concern that often arises in statistics is erroneous signals. A small bias in a sensor, for example, can cause AI systems to see an effect that isn’t real. The likelihood of a system picking up on an errant signal rises with the volume of data collected; a tiny bias in a sample is far more likely to be noticed by AI when using the volume of data common with today’s machine learning systems. Even data of reasonably high quality can lead to erroneous results, potentially leading companies down an unproductive path. This is part of the reason why data scientists are in such high demand. Their ability to implement the right algorithms is clearly important, but it also takes human judgment to make sense of the results AI systems produce. Determining whether a signal is a real effect can be a challenging task.

The power of machine learning is largely due to its ability to learn on its own. In order to get started, however, ML systems need to be trained with a set of data, and this data set needs to be of especially high quality, as even small problems can spoil the algorithms from the beginning. ML often works best when it’s left alone; tweaking the results manually can introduce bias and other problems. However, it’s important to carefully note how the ML system was trained and what data set was used. If problems arise later on, being able to examine the original data can be essential.

Relying on AI is important for a growing number of businesses. However, it can be tempting to use AI when it’s not the appropriate choice. In some situations, there simply isn’t enough high-quality data for systems to analyze, yet people often feel tempted to use AI systems anyway. Before launching an AI project, it’s important to examine the data itself and determine if quality results are even possible. AI systems all have their limitations, and none are able to make up for a lack of good data to analyze. Again, human expertise is essential. Data scientists and other statistics experts know how to examine data and find out what type of analysis is appropriate.

In general, more data leads to better results. Eventually, however, there comes a point where no additional data is needed as the data set is already broad enough to get the most out of AI and ML systems. It can be easy to fail to recognize when there’s no need to gather additional data due to the low cost of data storage and processing power. Over time, however, costs can creep up and eventually become less sustainable. This problem is also exacerbated by cloud storage, which makes acquiring storage space only a few clicks away. Before feeding more data into AI and ML systems, organizations should take time to determine all of the associated costs and ask whether doing so is worthwhile. If AI and ML systems are already fully saturated with data, it may make more sense to cut back instead of expand.

Data is driving today’s tech fields, and there’s no sign of this trend slowing down in the near future. However, it’s important to use the right tools when analyzing data to make the most of it, as misusing data can be wasteful or even dangerous. Before feeding more and more data to AI and ML systems, take some time to determine if there are ways to improve overall quality. A bit of data quality improvement can go a long way toward making the most of AI and ML systems.

Study Suggests Companies Reaping Benefits of Combining AR and IIoT

iot smart industry 4.0 concept. Industrial engineer(blurred) using smart glasses with augmented mixed virtual reality technology to read the data that  how to fix or maintenance the machine in factory

A new study offers fascinating insights into how companies are crafting industrial IoT and augmented reality experiences

Published by PTC, the “State of Industrial Innovation” study represents an ongoing analysis from the ThingWorx maker which explores market and adoption trends in industrial internet of things and mixed reality – two fields becoming more robust and complex as they evolve and intertwine.

AR adoption is increasing at a rapid pace. With enterprises in the midst of digital transformation, those looking to keep up cannot afford to delay adopting AR technology. Enterprises need to determine the business case across a wide range of potential AR applications: Customers are expecting better experiences when dealing with enterprises, and AR can play a crucial role in providing innovative services, solutions, and products. AR used internally is crucial as well, as it allows employees to be more productive and provide better interactions with customers.

Study Suggests Companies Reaping Benefits of Combining AR and IIoT TechNative

PTC’s report aims to focus on strategic differentiation; that is, how effectively companies are using AR to differentiate themselves from their competitors. The report shows that companies are reaping the benefits of AR technologies, often experiencing a return on their investment within a year. This high pace of adoption, PTC notes, presents tremendous opportunity but also the potential for disruption across entire industries.

Remote Monitor and Maintenance

IoT’s potential use cases are broad, but for industrial IoT, AR’s most beneficial use case may be remote monitoring and maintenance. We recently spoke to PTC’s Chirag Mehta to hear how BAE Systems are using augmented reality to help train new staff.

Usage differs between small and large companies, with smaller companies aiming to increase their market share by offering unique products and services to stand out from their competitors. Large companies, by contrast, typically have substantial interior service capabilities, and their industrial IoT focus lies more on increasing their productivity and efficiency. Mike Campbell, EVP for AR at PTC believes “the window to leverage AR to differentiate is limited”.

In compiling this report, we observed that pilots start with internal proofs of concept and quickly become deployed across multiple areas, including customer-facing product and service initiatives. Enterprises and consumers alike are on the verge of truly experiencing the transformative power of augmented reality.

The power of remote monitoring is clear to enterprises, and PTC found that they’re often implementing IoT technology in parallel with other technologies. Remote monitoring can serve as a foundation for innovative ideas. This provides a layer upon which many enterprises are building machine learning and predictive analytics. One of the most powerful features of this new technology is being able to predict failures ahead of time, helping customers best use their products. Manufacturers can also use this technology to find service opportunities that would go unnoticed internally or by third-parties.

Study Suggests Companies Reaping Benefits of Combining AR and IIoT TechNative

Varian stands as an excellent example of how industrial IoT can transform companies. The manufacturer of radiation oncology equipment was able to reduce the cost of their service by using IoT technology to improve the uptime of their machines. Predictive maintenance, in particular, has proven to be beneficial; Varian was able to reduce the frequency of service trips to their machines by 42 percent, saving a considerable amount of labor costs and reducing inconvenience to customers.

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