The January issue of Digitalisation World contains a substantial amount of predictions for 2020 and beyond – following on from a similar series of articles in both our November and December 2019 issues. The good news is that…the February issue will include/conclude the predictions series. So, by then you’ll have a substantial quantity of ideas and opinions which will, hopefully, help you make your own decisions as to what technology developments and what business trends are worth investigating and/or implementing during the coming year.

If I might be allowed to add a prediction of my own? Well, I just do not believe that the hype around 5G will turn into serious deliverables for quite some time. By this I mean that, while 5G may well find deployments within organisations – whether in the office or on the factory floor – the wholescale rollout of 5G infrastructure across cities, regions and, ultimately, whole countries, is some way off. Primarily, because of the expense of building out the required infrastructure against a fairly unpredictable return.

Of course, it maybe that our friends the hyperscalers come up with some killer apps and decide that, rather than wait for the telcos to do the expensive ‘heavy-lifting’, they’ll build out the infrastructure themselves, but it’s not immediately obvious what those apps might be.

Right now, as I may well have mentioned before, when I make the drive home from London to Wiltshire, as soon as I leave the M4 in Berkshire and join the A4 (still a major road) my mobile phone signal varies from an unreliable 4G, through 3G and GPRS to absolutely nothing. If the telcos don’t think it financially worth their while to provide decent mobile phone connectivity right now, why would they go to the expense of building out a 5G network for no obvious return?

And don’t be fooled into thinking that autonomous vehicles will be that killer app. The more I think about it, I just can’t see AVs ever gaining serious traction, unless, and this is a big unless, the insurance industry has a massive overhaul, and the automotive industry is prepared to cannibalise itself – or a new breed of vehicle manufacturers springs up.

So, the multi-billion car industry is going to stand by and watch as pretty much commoditised AVs replace the massive variety of vehicles currently available. They are barely accepting of electric vehicles…

However, even if AVs do gain momentum, there is still the issue of responsibility. The ‘dream’ AV experience is supposed to be one where a central pool of vehicles can be called upon when required. So, a vehicle is ordered for a night out, duly collects and delivers passengers to their required destination, and picks them up at the end of the night and drops them off home. And if a few drinks have been taken, then no worries, because the AV has everything under control.

Right now, AI-assisted vehicles do a great job of helping drivers manage their speed, their parking and various other tasks, but will any AV manufacturer, or, more importantly, an insurer, ever remove any shred of responsibility from the driver? Unlikely.

Oh, and as above, who’s going to build the required, reliable, resilient control network for those stretches of road which are used by a handful of cars a day?

And we haven’t even started to talk about the security aspect.

The vast majority (92%) of debt and equity investors surveyed expect the overall value of investment into Europe’s data centre infrastructure to increase over the next 24 months, according to research commissioned by DLA Piper and published today.

Data centres are used by organisations for the remote storage, processing and distribution of large amounts of data and are currently estimated to use 3-4% of world’s power. According to DLA Piper’s report European Data Centre Investment Outlook: Opportunities and Risks in the Months Ahead, investors anticipate an investment increase in data centres of between 10% and 29% over the next two years.

Data from Acuris in the report shows that the first half of 2019 has already seen a notable rise in investment - with EUR1 billion flooding into the data centres market in H1 alone, compared with a total of EUR1.5 billion for the whole of 2018.

Data centre investment levels in Europe has been impacted by Brexit uncertainty. All respondents agreed that it has negatively impacted the data centre infrastructure market since June 2016, with 56% of equity investors going as far as to say that the negative impact has been ‘significant’. On the flip side, the continuing weakness of the sterling means UK assets may look like a bargain for Eurozone investors.

In an increasingly interconnected world, with an ever-expanding need for data storage facilities, respondents are expecting rent charges to increase for data centres with superior technology, with over a third expecting the increase to be 10% or more.

The majority of respondents chose Germany as the European country that will see the biggest growth in data centre project investment over the next 24 months. Investors also expect the UK to see some of the biggest investment growth in the industry, followed by the Netherlands and France.

Commenting on the findings, partner and head of the Infrastructure sector, EMEA and Asia Pacific, at DLA Piper, Martin Nelson-Jones, said: “Investment into European data centres has spiked recently, with transaction values reaching a new high. Figures for the first half of 2019 suggest strongly that another record year could be in sight. While not without risks, data centres are attractive to many infrastructure investors.”

Intellectual Property & Technology partner at DLA Piper, Anthony Day, said: “What makes data centres so attractive to many investors? Strong fundamentals help. While data centre investment can involve a higher level of risk as compared to other types of infrastructure assets, demand for big data, cloud computing, artificial intelligence and the Internet of Things is rising significantly. The macro trend is that these technologies drive significantly increased demand for data and digital services and, by extension, the buildings and equipment that make them possible.”

Survey with IDG reveals that empowering business units has led to more complex audits, unchecked costs and security vulnerabilities.

In a new report from IDG Connect and Snow Software 67% of IT leaders said at least half of their spend is now controlled by individual business units. While most believe this is beneficial for their organisation, it presents new challenges when combined with increased cloud usage – 56% of IT leaders are concerned with hidden cloud costs and nearly 90% worry about the prospect of vendor audits within cloud environments. The survey, conducted to understand how the rise of infrastructure-as-a-service (IaaS) and democratised IT spending is impacting businesses, found that more than half of IT leaders expressed the need to gain better visibility of their IT assets and spending across their organisation.

Business Units Control a Significant Share of Tech Spend – Which is a Mixed Bag

Traditionally, technology purchasing and management was controlled by IT departments. The cloud and as-a-service models shifted this dynamic, enabling employees throughout the organisation to easily buy and use technology without IT’s involvement. IT leaders are embracing this trend, with 78% reporting that the shift in technology spending is a positive for their organisations. But decentralised IT procurement also creates new complexities for organisations as they try to manage their increasingly diverse IT estates.

The IT leaders in the study voiced concern that the shift in spending to business units:

• Increases the risk to data security
• Increases the threat of non-compliance
• Leaves cloud spending spiralling out of control
• Makes audit preparation more time-consuming and complex

In fact, more than three-fourths (78%) said audit preparation is growing increasingly complex and time consuming.

Executives are Justified in Worrying About Audits

Results suggest that annual audits are now the rule rather than the exception – 73% of those surveyed said they have been audited by at least one software vendor in the past 12 months.

When asked which vendors they had been audited by within the last year, 60% said Microsoft, 50% indicated IBM and 49% pointed to SAP. Such enterprise software audits can put a tremendous strain on internal resources and result in six, seven and even eight-figure settlement bills.

The vast majority of IT leaders surveyed said they are concerned about the looming possibility of audits, specifically when it comes to IaaS environments. When asked if the thought of software vendor audits for licensed usage on the IaaS front worries them, 60% responded “yes, very much so” and 29% said they are somewhat concerned.

The Roles and Requirements for IT Have Changed

Survey respondents also voiced concern that with the decentralisation of IT spending within their organisations, they will be held responsible for something they currently can’t control. More than half (59%) said that in the next two years they need to gain better visibility of the IT estate. Just slightly less than that (52%) said in that same timeframe, they would have to obtain an increased understanding of who is spending what on IT within the larger organisation.

“As the research highlights, the shift to cloud services coupled with democratised technology spend is fundamentally changing the way businesses and IT leaders need to operate,” said Sanjay Castelino, Chief Product Officer at Snow. “Empowering business units to get the technology they need is largely a positive development, but it creates challenges when it comes to visibility and control – and that can put organisations at risk of having problematic audits. It is more important than ever for organisations to have complete insight and manageability across all of their technology in the IT ecosystem.”

Over half of European manufacturers are implementing AI use cases in the sector with Germany a frontrunner on 69% AI adoption versus US at 28% and China at 11%.

A new report from the Capgemini Research Institute highlights that the European market is leading in terms of implementing Artificial Intelligence (AI) in manufacturing operations. 51% of top global manufacturers in Europe are implementing at least one AI use case. The research also analyzed 22 AI use cases in operations and found that manufacturers can focus on three use cases to kickstart their AI journey: intelligent maintenance, product quality control, and demand planning.

Capgemini’s report entitled ‘Scaling AI in manufacturing operations: A practitioners’ perspective’analyzed AI implementation among the top 75 global organizations in each of four manufacturing segments: Industrial Manufacturing, Automotive, Consumer Products and Aerospace & Defense. The study found that AI holds tremendous potential for industries in terms of reduced operating costs, improved productivity, and enhanced quality. Top global manufacturers in Germany (69%), France (47%) and the UK (33%) are the frontrunners in terms of deploying AI in manufacturing operations, according to the research.

Key points from the report include:

AI is being utilized and making a difference across the operation value chain

Leading organizations are using AI across manufacturing operations to significant benefit. Examples include food company Danone[1] which has succeeded in reducing forecast errors by 20% and lost sales by 30% through using machine learning to predict demand variability. Meanwhile, tire manufacturer Bridgestone[2] has introduced a new assembly system based around automated quality control, resulting in over 15% improvement in uniformity of product.

Manufacturers tend to focus on three main use cases to kickstart their AI journey

According to the report, manufacturers start their AI in operations journey with three use cases (out of 22 unique ones identified in the study) as they possess an optimum combination of several characteristics that make them an ideal starting point. These characteristics include: clear business value, relative ease of implementation, availability of data and AI skills, among others. Executives interviewed by Capgemini commented that product quality control, intelligent maintenance, and demand planning are areas where AI can be most easily implemented and deliver the best return-on-investment. For instance, General Motors[3] piloted a system to spot signs of robotic failures before they occur. This helps GM avoid costs of unplanned outages which can be as high as $20,000 per minute of downtime. While there is consensus on which use cases are best to get started with AI in operations, the study also points out the challenge of scaling beyond the first deployments and then systematically harvest the potential of AI beyond those initial use cases.

“As implementation of AI in manufacturing operations matures, we will see large enterprises transitioning from pilots to broader deployment,”said Pascal Brosset,Chief Technology Officer for Digital Manufacturing at Capgemini. “Quite rightly, organizations are initially focusing their efforts on use-cases that deliver the fastest, most-tangible return on investment: notably in automated quality inspection and intelligent maintenance.

“The executives we interviewed were clear that these are functions which can deliver considerable cost savings, improve the accuracy of manufacturing and eliminate waste. However, the leaders do not solely focus on these use cases but, in parallel with their deployment, prepare for the future by reinvesting part of the savings into building a scalable data/AI infrastructure and developing the supporting skills.” He further added.

The market for extended reality devices shows the typical signs of early volatility, but the long-term outlook for the technology remains positive.

The market for extended reality products, which comprises virtual reality (VR) and augmented reality (AR) devices, will enjoy 21% growth in 2019, to slightly more than 10 million devices, according to the latest forecast by technology analyst firm CCS Insight. Marina Koytcheva, vice president of forecasting, notes, "Although this growth rate might seem disappointing for a market that has had so much hype, it should be assessed pragmatically. Right now, there are still just a handful of successful devices, and a lot rides on every new iteration or new model brought to market by the established players Sony, HTC and Oculus".

CCS Insight believes that Sony is on track to record a solid 2019, and Facebook has also started gaining meaningful revenue from its Oculus devices. HTC, however, despite leading in the premium end of the market, looks set for less growth in 2019. But Koytcheva notes, "It's still early days in the nascent VR market and I have positive expectations for this exciting product category".

The recently published forecast projects that market demand will grow sixfold to 60 million units in 2023. Leo Gebbie, senior analyst at CCS Insight, covering wearables and extended reality devices, explains, "Our optimism is supported by our consumer research of early technology adopters: those who don't yet own a VR device show a strong willingness to buy an extended reality device within the next three years, particularly as more attractive and affordable products with richer content and experiences become available. I believe this is particularly good news for entry-level devices like the standalone Oculus Go headset, which retails at less than $200".

CCS Insight also notes that the variety of VR devices is growing. The company expects new products in 2020 from Oculus, HTC and others, including the highly anticipated Sony PlayStation 5, which is widely expected to be accompanied by an updated PlayStation VR headset.

A further boost to the VR market is coming from the advent of 5G mobile networks. In South Korea, currently the most advanced 5G market in the world in terms of adoption, mobile operators have successfully positioned 5G as a technology that can deliver an attractive VR experience. "Operators in other markets should be encouraged by the success of their South Korean counterparts, and we expect more consumer offerings to be built on the coupling of VR and 5G in the near future", says Koytcheva.

China will also play an important role in the growth of the VR market. The Chinese government's initiative to be a global leader in VR and AR technologies by 2025 will have an impact in the near future. Education is being targeted as one of the major sectors where VR should be adopted. This tallies with CCS Insight's prediction that extended reality will become a standard educational tool in schools in at least two countries by 2025.

"All these trends support our view that the VR market is just heating up. Some quarters will be better than others, but the direction of travel is onward and upward", concludes Koytcheva.

When it comes to AR, adoption by business users is picking up, although the numbers are currently very small. CCS Insight expects about 150,000 AR devices will be sold globally in 2019.

Adoption of AR devices in logistics and remote assistance continues to rise, and other industries are also starting to follow suit, with important vertical markets such as medicine, entertainment and travel beginning to show signs of growth. Importantly, end-to-end AR solutions, consisting of hardware, software and support, are also improving, making adoption much easier than it was a couple of years ago.

The consumer market for smart AR glasses, however, is still a few years away. Gebbie comments, "We've seen some very exciting products starting to emerge, but they're generally prototypes or early iterations of future device designs. It will be some time before mass-market products capable of delivering significant volume hit the market".

CCS Insight also notes that component miniaturization remains a major challenge. Unlike warehouse workers and other enterprise users, consumers are unlikely to be willing to accept anything heavier than and much different in appearance from traditional eyeglasses in their everyday lives. However, Gebbie concludes, "We're confident that this technology will improve rapidly, and predict that by 2022 a major consumer electronics brand will enter the consumer smart glasses market, opening the gates for strong growth in years to come".

98% say improved mobile access would benefit business outcomes.

Domo has released new research that finds business executives want greater access to company data on their mobile devices to power digital transformation across the enterprise. In fact, 98% of respondents believe that improved mobile access to decision-making data would benefit business outcomes.

Decision makers increasingly use mobile devices to conduct business but they often struggle to access the most up-to-date information while on the go. According to the study conducted by Dimensional Research, 96% of teams say it would help decision-making if stakeholders at all levels of the organization had access to up-to-the-minute data on their phones. 87% want to instantly share reports with their team and collaborate on their phones.

According to 2018 McKinsey & Company research1, deployment of mobile internet technology has emerged as the most impactful technology deployed in successful digital transformation efforts across organizations of all sizes. McKinsey’s research found that 68% of organizations that deployed mobile internet technologies reported successful digital transformations compared to 53% of companies that did not.

Other key findings about decision-making data on mobile devices from the Dimensional survey include:

• There is no longer a stigma about bringing your phone to a meeting. The vast majority of data-driven decision makers (91%) have access to their phones in face-to-face meetings. And there is no difference between executives and non-executives (both 91%).
• Decision-makers want better mobile apps. An overwhelming majority (95%) would do more data-driven tasks from their mobile devices if apps were better. Some of the key hurdles that business leaders highlight include having reports that are not conducive for viewing on a mobile device (56%), security policies that keep them from accessing the apps they want (42%) and overcoming fears that colleagues will judge them for being on their mobile phone (20%).
• Companies are increasingly dispersed — and so are executive teams. About two-thirds (65%) of data-driven decision makers report that their companies have become more geographically dispersed in the past ten years. As companies become more dispersed, the importance of sharing data increases. At companies where the number of offices is expected to increase dramatically, almost all (95%) agreed that they want to instantly share reports and collaborate from wherever they are.

“When teams have immediate access to their data, they can make better and more timely decisions,” said Josh James, founder and CEO, Domo. “The global mobile workforce2 is expected to reach 1.87 billion workers by 2022, and Domo is the best and easiest platform for customers to have the same experience with real-time data on a mobile device as they do on their laptop. Business leaders are spending more time away from their desks so that means they need data on their mobile devices to make key decisions on the go.”

The vast majority (94%) of environmental services managers in councils, local authorities, government or infrastructure agencies admit their organisation is yet to digitalise operations. Budget restrictions (47%) and outdated systems architecture (50%) are seen as two of the main barriers to digitalisation.

Nearly three quarters (72%) of those surveyed noted, however, that they expect the pace of digital transformation to accelerate in the next three to five years. Cloud architectures are expected to have the biggest impact in shaping the future of environmental services over that timeframe (42%), while mobile technologies were referenced by more than a third (35%) of respondents.

Artificial intelligence and machine learning were regarded as impactful by a third of the sample (33%), while Internet of Things (IoT) technologies, including sensors were close behind, with 25% of respondents citing them among the technologies likely to have the most impact in shaping the future of environmental services over the next three to five years.

Tim Woolven, product consultant at Yotta, said: “While most environmental services teams are well underway on their journey to digital or even nearing completion, there is still work to do. Outdated technology systems are seen as one of the main barriers but we would expect that to change over the coming years as mobile systems and cloud architectures become ever more pervasive and advanced technologies like AI, sensors and machine learning continue to mature”.

The study discovered that just under half (48%) of those polled expect improved operational efficiency to be one of the main benefits digital transformation would bring to their organisation’s environmental services provision in the future. Further to this, 44% cited ‘better employee morale’, clearly showing the importance of giving a workforce the latest technology to assist them in their roles. In total, 39% highlighted ‘enhanced data quality’ as a main benefit.

Major global data centre markets are seeing soaring construction costs as development in new and emerging hubs continues to heat up, according to research from global professional services company Turner & Townsend.

The Data Centre Cost Index 2019 highlights the intensification of investment in leading locations in the global data centre network as a trigger for escalating costs. Globally, over 40 per cent of markets surveyed are showing 'hot' construction conditions – where competition for supply chain resources is putting pressure on budgets.

The research analyses input costs – including labour and materials – across 32 key markets, alongside industry sentiment and insight from data centre professionals.

The 2019 report points to the rise of new hotspots across the globe as technological investment in emerging economies takes hold. In Nairobi, Kenya, average build costs stand at $6.5 US per watt on the back of investment required to meet the government’s focus on digitisation of the economy and in response to the arrival of tech giants.

Cost pressures are contributing to the growth of secondary markets in key geographies – including in the US and Europe. In California, Silicon Valley has risen to be the third most expensive place to build globally at a rate of $9.4 US per watt – with unprecedented construction market conditions. Inter-state competition to attract hyperscale investment in the US continues and the study indicates that construction costs in both Dallas and Phoenix ($7.4 US per watt and $7.1 US per watt respectively) are favourable over the world’s largest data centre market of Northern Virginia where costs stand on average at $8 US per watt.

European markets are seeing a significant shift, with capital costs of hyperscale development in the dominant markets of Scandinavia - in Stockholm ($8.6 US per watt) and Copenhagen ($8.5 US per watt) - now exceeding those of the established FLAP markets Frankfurt ($7.6 US per watt), London ($8.5 US per watt), Amsterdam ($7.8 US per watt) and Paris ($7.7 US per watt). Zurich remains the most expensive market to feature in the report but is also expected to be one of the hottest markets for Europe in 2020.

In this environment, respondents to Turner & Townsend’s survey view delivering within budget as a critical challenge, with 90 per cent seeing this as more important than innovation.

Global demand for new space looks set to continue into 2020, with just nine per cent of respondents to the research believing that data centre demands have been met in their markets in the last year – down from 12 per cent in 2018. 70 per cent of those surveyed highlighted the impact of data sovereignty and data protection acts – including those being brought in by the EU, Switzerland and Kenya – as a major catalyst for demand.

The most significant limiter on growth over the next five years is seen as availability of power, especially in the context of pressure on the industry to decarbonise. In Turner & Townsend’s survey, the industry is split 50:50 on whether technological advances with solid state batteries alongside green energy sources can render traditional fossil fuel generators obsolete.

Dan Ayley, global head of hi-tech and manufacturing at Turner & Townsend, said:“Data continues to be one of the most valuable commodities. As deals get bigger and more profitable, we are seeing investment in both established hot spots and emerging markets heat up – putting pressure on cost and resources.”

“Although our report points to certainty in delivery as the key issue for the sector across global markets, sustainability is one of the most pressing challenges coming down the track. With power density requirements for data centres increasing by as much as 50 per cent year on year, demonstrating steps towards decarbonisation needs to be a priority for how hubs are conceived, built and operated across their lifecycle.”

Leaseweb USA, a leading hosting and cloud services company, has released the results of its “Developer IaaS Insights Study,” based on a survey conducted at DeveloperWeek Austin. The research revealed that 61.4% of companies see hybrid cloud (31.6%) or private cloud (29.8%) as the infrastructure for the future of their company, and 75.9% of developers prioritized scalability, speed, ease of use and cost as top factors when choosing their IaaS hosting solution.

 “As companies evolve, their hosting needs and capabilities also evolve,” said Lex Boost, CEO of Leaseweb USA. “Understanding why companies choose to migrate to an IaaS solutions vendor provides insight to not only the marketplace, but what value vendors can bring to the businesses. This survey is a microcosmic example of the current industry trend. The power, speed, flexibility and functionality of dedicated, hybrid and private cloud infrastructure environments are undeniable. Companies are shifting back to custom solutions designed to fit their exact needs, in this precise moment of their company lifecycle. The mettle of metal cannot be ignored.”

The results are particularly significant when considering that less than 20% of respondents believe they are using the industry standard, are happy with the performance of their infrastructure and have no plans to change. Further, 51.7% plan on migrating in the next two years while 26.7% have not yet made a decision as to whether they will migrate in the same timeframe. Clearly, most companies are reevaluating their DevOps infrastructures, and will either be migrating to solutions or considering solutions that more thoroughly meet their hosting and infrastructure requirements.

Barriers to Migration

To assist developers who are looking for the right fit for their company’s DevOps infrastructure needs, providers need to address cost of migration and the size of the job which rose to the top as barriers to migration that remain a prohibitive factor. Cost of migration or the size of the job were cited as top barriers to migration by 37.5% of companies, while 24.2% of respondents identified cost alone as the top barrier.

The survey also revealed 15% aren’t sure what to outsource, 8.3% are not finding the right partner and 3.3% are held ransom by public cloud providers. 

Global report examines latest trends in business communications and how they affect employee productivity and the bottom line.

Mitel has published the results of its latest global report on workplace productivity and business communications trends. The independent research study - conducted by research firm Vanson Bourne with advisement and analysis from KelCor, Inc -surveyed 2,500 business professionals in five countries across North America, Western Europe and Australia to examine overarching trends in business communications and how existing communications and collaboration practices are impacting both workforce productivity and the bottom line.

Key findings from the report:

• Employees reportedly spend more than half of the average workday communicating and collaborating. However, respondents note that, on average, 13% of their day is wasted due to communications inefficiencies, resulting in over $10,000 per employee per year.

• Lost productivity is not the only negative result of communications inefficiencies. Almost half (47%) of respondents had experienced friction between employees and/or departments due to inefficient communications and collaboration. Nearly a quarter (24%) cited that inefficient communications have had a negative impact on customer satisfaction. With that knowledge, it’s likely that additional costs of lost business, employee attrition, or missed opportunities also have a hidden impact on the bottom line of many organizations.

The report also looked at which methods of communications and collaboration employees find most efficient and effective, offering helpful insights for IT and business leaders looking to ensure digital transformation initiatives and related technology investments are successful.

• Employees are inclined to “use what they know” when it comes to their communications and collaboration tools, which means phone and email are not going away any time soon. These technologies still dominate the top five most used communications methods (97% each) while face to face meetings are still considered the most effective way to communicate (53%).

• With today’s increasingly distributed and mobile workforce, the appetite for more modern communications and collaboration technologies is clearly on the rise. Respondents expect to use online shared workspaces (45%), chat/messaging (51%) and video (39%) tools more frequently in the future.

Given the significant waste surrounding resource costs and time, it’s no surprise that 74% of respondents felt that more effective use of technology within their organization would improve their personal productivity. However, the report brings to light several interesting findings on what is causing communications inefficiency and what organizations should consider to reduce it:

• The real obstacles organizations must overcome aren’t rooted in the tools themselves; instead, insufficient training (32%) and resistance to change (25%) are the biggest culprits. This confirms that digital transformation is broader than simply implementing technology; it requires careful and strategic shifts in an organization’s culture and processes.

Businesses have an opportunity to lessen the impact of lost productivity by aligning their tools, processes and culture to achieve better results. When it comes to communications and collaboration, clear leadership, improved planning, effective training and employee education on the goals and benefits of the tools could have a strong positive impact on adoption and ROI. 

Training remains a critical form of defence against cyber-attacks.

Organisations are leaving themselves unnecessarily exposed to significant security risks. This is according to data from, Databarracks, revealing over two-thirds of IT decision-makers believe their employees regularly flout internal IT security policies.

With industry practitioners speculating on how the cyber security landscape will evolve in 2020, Peter Groucutt, managing director of Databarracks, highlights why training is still a critical form of defence against cyber-attacks.

“People are often the weakest link in the information security chain and to prevent your organisation being caught, it’s important you make employees aware of the risks. Our research has revealed two-thirds (67 per cent) of IT decision-makers believe their employees regularly circumvent company security policies.”

Groucutt continues, “Employees flouting security policies are never deliberately threatening the business – either they don’t know the possible consequences of their actions or feel too restricted by the policies in place. In any case, this neglect for security leaves an organisation exposed to threats.

“To reduce the danger, there are practical steps an organisation can take. Firstly, to develop a culture of shared responsibility, where the cyber security burden doesn’t just rest with the IT department. We understand this in the physical working environment – an unknown person would not be allowed to walk in to an office, and start taking belongings unchallenged – so why should digital security be any different?

“Secondly, lines of communication between the IT department and the rest of the business need to improve. For users to feel like they are part of the solution, they need to be aware of the ongoing battle IT face. Often, IT teams handle incidents in the background with only key senior individuals being informed, but if threats aren’t communicated internally to all employees, they won’t know how to change their behaviour in future. The IT department has a responsibility to educate the entire business on why an incident took place, what the implications were and, most importantly, what can be done to prevent this from happening again.”

Groucutt continues, “When security processes hinder an employee’s performance, they will often find a way to get around them to get a job done quicker. To avoid staff taking the easy route security must be built into an organisation’s overall strategy and communicated down through employees’ objectives. Equally, IT need to be receptive when policies are flagged for being too restrictive. That creates the dialogue and an understanding of a shared goal for IT and users.

“Finally, regular training and education is vital. Awareness training is typically only carried out annually or as part of an initial induction, but this should be increased. Employees need ongoing security refreshers throughout the year, at least twice annually, to address any new threats, and ensure security remains front of mind.”

 “This past year, infrastructure trends focused on how technologies like artificial intelligence (AI) or edge computing might support rapidly growing infrastructure and support business needs at the same time,” said Ross Winser, senior research director at Gartner. “While those demands are still present, our 2020 list of trends reflect their ‘cascade effects,’ many of which are not immediately visible today.”

During his presentation, Mr. Winser encouraged I&O leaders to take a step back from “the pressure of keeping the lights on” and prepare for 10 key technologies and trends likely to significantly impact their support of digital infrastructure in 2020 and beyond. They are:

Trend No. 1: Automation Strategy Rethink

In recent years, Gartner has detected a significant range of automation maturity across clients: Most organizations are automating to some level, in many cases attempting to refocus staff on higher-value tasks. However, automation investments are often made without an overall automation strategy in mind.

“As vendors continue to pop up and offer new automation options, enterprises risk ending up with a duplication of tools, processes and hidden costs that culminate to form a situation where they simply cannot scale infrastructure in the way the business expects,” said Mr. Winser. “We think that by 2025, top performing leaders will have employed a dedicated role to steward automation forward and invest to build a proper automation strategy to get away from these ad hoc automation issues.”

Trend No. 2: Hybrid IT Versus Disaster Recovery (DR) Confidence

“Today’s infrastructure is in many places — colocation, on-premises data centers, edge locations, and in cloud services. The reality of this situation is that hybrid IT will seriously disrupt your incumbent disaster recover (DR) planning if it hasn’t already,” said Mr. Winser.

Often, organizations heavily rely on “as a service (aaS)” offerings, where it is easy to overlook the optional features necessary to establish the correct levels of resilience. For instance, by 2021, the root cause of 90% of cloud-based availability issues will be the failure to fully use cloud service provider native redundancy capabilities.

“Organizations are left potentially exposed when their heritage DR plans designed for traditional systems have not been reviewed with new hybrid infrastructures in mind. Resilience requirements must be evaluated at design stages rather than treated as an afterthought two years after deployment,” said Mr. Winser.

Trend No. 3: Scaling DevOps Agility

For enterprises trying to scale DevOps, action is needed in 2020 to find an efficient approach for success. Although individual product teams typically master DevOps practices, constraints begin to emerge as organizations attempt to scale the number of DevOps teams.

“We believe that the vast majority of organizations that do not adopt a shared self-service platform approach will find that their DevOps initiatives simply do not scale,” said Mr. Winser. “Adopting a shared platform approach enables product teams to draw from an I&O digital toolbox of possibilities, all the while benefiting from high standards of governance and efficiency needed for scale.”

Trend No. 4: Infrastructure Is Everywhere — So Is Your Data

“Last year, we introduced the theme of ’infrastructure is everywhere’ that the business needs it. As technologies like AI and machine learning (ML) are harnessed as competitive differentiators, planning for how explosive data growth will be managed is vital,” said Mr. Winser. In fact, by 2022, 60% of enterprise IT infrastructures will focus on centers of data, rather than traditional data centers, according to Gartner.

“The attraction of moving selected workloads closer to users for performance and compliance reasons is understandable. Yet we are rapidly heading toward scenarios where these same workloads run across many locations and cause data to be harder to protect. Cascade effects of data movement combined with data growth will hit I&O folks hard if they are not preparing now.”

Trend No. 5: Overwhelming Impact of IoT

Successful IoT projects have many considerations, and no single vendor is likely to provide a complete end-to-end solution. “I&O must get involved in the early planning discussions of the IoT puzzle to understand the proposed service and support model at scale. This will avoid the cascade effect of unforeseen service gaps, which could cause serious headaches in future,” said Mr. Winser.

Trend No. 6: Distributed Cloud

Distributed cloud is defined as the distribution of public cloud services to different physical locations, while operation, governance, updates and the evolution of those services are the responsibility of the originating public cloud provider.

“Emerging options for distributed cloud will enable I&O teams to put public cloud services in the location of their choosing, which could be really attractive for leaders looking to modernize using public cloud,” said Mr. Winser.

However, Mr. Winser points out that the nascent nature of many of these solutions means a wide range of considerations must not be overlooked. “Enthusiasm for new services like AWS Outposts, Microsoft Azure Stack or Google Anthos must be matched early on with diligence in ensuring the delivery model for these solutions is fully understood by I&O teams who will be involved in supporting them.”

Trend No. 7: Immersive Experience

“Customer standards for the experience delivered by I&O capabilities are higher than ever,” said Mr. Winser. “Previous ‘value adds’ like seamless integration, rapid responses and zero downtime are now simply baseline customer expectations.”

Mr. Winser warned leaders that as digital business systems reach deeper into I&O infrastructures, the potential impact of even the smallest of I&O issues expands. “If the customer experience is good, you might grow in mind and market share over time; but if the experience is bad, the impacts are immediate and could potentially impact corporate reputation rather than just customer satisfaction.”

Trend No. 8: Democratization of IT

Low-code is a visual development approach to application development that is becoming increasingly appealing to business units. It enables developers of varied experience levels to create applications for web and mobile with little or no coding experience, largely driving a “self-service” model for business units instead of turning to central IT for a formal project plan.

“As low-code becomes more commonplace, the complexity of the IT portfolio increases. And when low-code approaches are successful, I&O teams will eventually be asked to provide service,” said Mr. Winser. “Starting now, it is in I&O leaders’ best interest to embed their support and exert influence over things that will inevitably affect their teams, as well as the broader organization.”

Trend No. 9: Networking — What’s Next?

In many cases, network teams have excelled in delivering highly available networks, which is often achieved through cautious change management. At the same time, the pace of change is tough for I&O to keep up with, and there are no signs of things slowing down.

Mr. Winser said that the continued pressure to keep the lights shining brightly has created unexpected issues for the network. “Cultural challenges of risk avoidance, technical debt and vendor lock-in all mean that some network teams face a tough road ahead. 2020 needs to be the time for cultural shifts, as investment in new network technologies is only part of the answer.”

Trend No. 10: Hybrid Digital Infrastructure Management (HDIM)

As the realities of hybrid digital infrastructures kick in, the scale and complexity of managing them is becoming a more pressing issue for IT leaders.

Organizations should investigate the concept of HDIM, which looks to address the primary management issues of a hybrid infrastructure. “This is an emerging area, so organizations should be wary of vendors who say they have tools that offer a single solution to all their hybrid management issues today. Over the next few years, though, we expect vendors focused on HDIM to deliver improvements that enable IT leaders to get the answers they need far faster than they can today.”

Infrastructure-led disruption will drive business innovation

By 2025, 60% of infrastructure and operations (I&O) leaders will drive business innovation using disruptive technologies, up from less than 5% who do so today, according to Gartner, Inc. This trend of infrastructure-led disruption will support the growth of the I&O function within the enterprise.

“As businesses face increased pressure to lower operating costs, many I&O leaders have been siloed into a tactical role rather than a strategic one — essentially, becoming custodians of legacy infrastructure,” said Katherine Lord, research vice president at Gartner. “The result is stunted I&O maturity over the past decade. I&O leaders who harness the power of disruptive technologies, such as cloud and artificial intelligence (AI), will discover new opportunities to serve as business innovators.”

Infrastructure-led disruption is the use of I&O technologies, processes, people, skills and capabilities to promote disruption and embrace risk. “I&O leaders who champion infrastructure-led disruption are constantly looking for new ways to use technology to deliver business value, rather than just remaining reactive to stakeholder needs,” said Ms. Lord.

New Technologies Make Way for I&O Maturity

IT infrastructure remains in a period of protracted change, spurred by new technologies that only increase the complexity of modern, distributed infrastructures. Recognizing the need for growth to remain relevant in the digital age, 45% of respondents in the Gartner 2019 I&O Executive Leaders Survey* indicated that improving maturity was among their top three goals for their I&O organizations. Embracing technologies such as automation, edge and quantum computing can help I&O leaders mature their infrastructure for the next wave of digital.

“Infrastructure-led disruption is about more than avoiding obsolescence,” said Ms. Lord. “It presents an opportunity for I&O to purposefully take an entrepreneur-like approach to extend the function beyond existing organization charts, and even reinvent the role itself. Keeping a pulse on emerging technologies will help center I&O as a part of the business innovation and market disruption they support.”

Evolve Talent, Culture and Practices for the Future of I&O

Through 2022, traditional I&O skills will be insufficient for more than half of the operational tasks that I&O leaders will be responsible for. Further, while 66% of I&O leaders believe that behaviors related to culture hinder their agility, 47% have not adapted these behaviors to align with their cultural and organizational transformation.

“I&O leaders are at a critical decision point, in which they can either choose to embrace disruption or sit in a ‘watch and wait’ mode,” said Ms. Lord. “For those who choose to take the proactive approach, new skills, talent and culture will be critical for driving change in the early stages.”

Strategic alignment and purposeful alliances with the C-suite will also be crucial for the future of I&O. As business becomes increasingly digital, I&O leaders have the chance to use their technology expertise to collaborate with other leaders on breakthrough opportunities.

“Digital transformation presents a real opportunity for I&O to align more closely with the CEO and other key business stakeholders, elevating the function to a more strategic role within the organization and helping the enterprise stay ahead of the curve when it comes to embracing disruptive technologies,” said Ms. Lord.

Several factors will help to drive the adoption of 5G over the next several years:

• Data Creation and Consumption. The amount of data created and consumed by consumers and businesses will continue to grow over the coming years. Shifting data-intensive users and use cases to 5G will allow network operators to more efficiently manage network resources, improving performance and reliability as a result.
• More Things Connected. As the IoT continues to proliferate, the need to support millions of connected endpoints at the same time will become increasingly critical. With the ability to enable an exponentially denser number of simultaneous connections, 5G's densification advantage be key for mobile network operators in providing reliable network performance.
• Speed and Real-Time Access. The speed and latency that 5G enables will open up the door for new use cases and add mobility as an option to many existing ones. Many of these use cases will come from businesses looking to leverage 5G's technological advantages in their edge computing, artificial intelligence, and cloud services initiatives.

"While there is a lot to be excited about with 5G, and there are impressive early success stories to fuel that enthusiasm, the road to realizing the full potential of 5G beyond enhanced mobile broadband is a longer-term endeavor, with a great deal of work yet to be done on standards, regulations, and spectrum allocations," said Jason Leigh, research manager for Mobility at IDC. "Despite the fact that many of the more futuristic use cases involving 5G remain three to five years from commercial scale, mobile subscribers will be drawn to 5G for video streaming, mobile gaming, and AR/VR applications in the near term."

In addition to building out the 5G network infrastructure, mobile network operators will have a lot to do to ensure a return on their investment:

• Unique, must-have applications. Mobile network operators need to invest in the development of 5G mobile apps and work with developers to create robust apps and use cases that take full advantage of the speed, latency, and connection density offered by 5G.
• Guidance on 5G best practices. Mobile operators need to position themselves as trusted advisors around connectivity, dispelling misconceptions and providing guidance on where 5G might best be utilized by a customer and, equally as important, when the need can be met by other access technologies.
• Partnerships are critical. Deep partnerships with software, hardware, and services vendors, as well as close relationships with industry partners, are required to integrate the diverse technologies necessary to realize the most complex 5G use cases and ensure that 5G solutions closely align with the operational reality of customers' day-to-day needs.

Server market declines 6.7%

According to the International Data Corporation (IDC) Worldwide Quarterly Server Tracker, vendor revenue in the worldwide server market declined 6.7% year over year to $22.0 billion during the third quarter of 2019 (3Q19). Worldwide server shipments declined 3.0% year over year to just under 3.1 million units in 3Q19.

In terms of server class, volume server revenue was down 4.0% to $17.9 billion, while midrange server revenue declined 14.3% to $3.0 billion and high-end systems contracted by 23.7% to $1.1 billion.

"While the server market did indeed decline last quarter, next generation workloads and advanced server innovation (e.g., accelerated computing, storage class memory, next generation I/O, etc.) keep demand for enterprise compute at near historic highs," said Paul Maguranis, senior research analyst, Infrastructure Platforms and Technologies at IDC. "In fact, 3Q19 represented the second biggest quarter for global server unit shipments in more than 16 years, eclipsed only by 3Q18."

Overall Server Market Standings, by Company

Dell Technologies and the combined HPE/New H3C Group ended 3Q19 in a statistical tie* for the number one position with 17.2% and 16.8% revenue share, respectively. Revenues for Dell Technologies declined 10.8% year over year while HPE/New H3C Group was down 3.2% year over year. The third ranking server company during the quarter was Inspur/Inspur Power Systems, which captured 9.0% market share and grew revenues 15.3% year over year. Lenovo and Cisco ended the quarter tied* for the fifth position with 5.4% and 4.9% revenue share, respectively. Lenovo saw revenue decline by 16.9% year over year and Cisco saw its revenue grow 3.1% year over year.

The ODM Direct group of vendors accounted for 26.4% of total revenue and declined 7.1% year over year to $5.82 billion. Dell Technologies led the worldwide server market in terms of unit shipments, accounting for 16.4% of all units shipped during the quarter.

Notes:

* IDC declares a statistical tie in the worldwide server market when there is a difference of one percent or less in the share of revenues or unit shipments among two or more vendors.

^a Due to the existing joint venture between HPE and the New H3C Group, IDC will be reporting external market share on a global level for HPE and New H3C Group as "HPE/New H3C Group" starting from 2Q 2016.

Due to the existing joint venture between IBM and Inspur, IDC will be reporting external market share on a global level for Inspur and Inspur Power Systems as "Inspur/Inspur Power System

Notes:

* IDC declares a statistical tie in the worldwide server market when there is a difference of one percent or less in the share of revenues or shipments among two or more vendors.

^a Due to the existing joint venture between HPE and the New H3C Group, IDC will be reporting external market share on a global level for HPE and New H3C Group as "HPE/New H3C Group" starting from 2Q 2016.

^b Due to the existing joint venture between IBM and Inspur, IDC will be reporting external market share on a global level for Inspur and Inspur Power Systems as "Inspur/Inspur Power Systems" starting from 3Q 2018.

Top Server Market Findings

On a geographic basis, Asia/Pacific (excluding Japan) (APeJ) and Japan were the only regions to show growth in 3Q19 with Japan as the fastest at 3.3% year over year and APeJ flat at 0.2% year over year. Europe, the Middle East and Africa (EMEA) declined 9.6% year over year while Canada declined 4.7% and Latin America contracted 14.2%. The United States was down 10.7% year over year. China saw its 3Q19 vendor revenues remain essentially flat with year-over-year growth of 0.7%.

Revenue generated from x86 servers decreased 6.2% in 3Q19 to $20.6 billion. Non-x86 servers declined 13.1% year over year to $1.4 billion.

Converged Systems market grows 3.5%

According to the International Data Corporation (IDC) Worldwide Quarterly Converged Systems Tracker, worldwide converged systems market revenue increased 3.5% year over year to $3.75 billion during the third quarter of 2019 (3Q19).

"The converged systems market continues to grow despite a challenging overall datacenter infrastructure environment," said Sebastian Lagana, research manager, Infrastructure Platforms and Technologies at IDC. "In particular, hyperconverged solutions remain in demand as vendors do an excellent job positioning the solutions as an ideal framework for hybrid, multi-cloud environments due to their software-defined nature and ease of integration into premises-agnostic environments."

Converged Systems Segments

IDC's converged systems market view offers three segments: certified reference systems & integrated infrastructure, integrated platforms, and hyperconverged systems. The certified reference systems & integrated infrastructure market generated roughly $1.26 billion in revenue during the third quarter, which represents a contraction of 8.4% year over year and 33.7% of all converged systems revenue. Integrated platforms sales declined 13.9% year over year in 3Q19, generating $475 million worth of sales. This amounted to 12.6% of the total converged systems market revenue. Revenue from hyperconverged systems sales grew 18.7% year over year during the third quarter of 2019, generating nearly $2.02 billion worth of sales. This amounted to 53.7% of the total converged systems market. 

IDC offers two ways to rank technology suppliers within the hyperconverged systems market: by the brand of the hyperconverged solution or by the owner of the software providing the core hyperconverged capabilities. Rankings based on a branded view of the market can be found in the first table of this press release and rankings based on the owner of the hyperconverged software can be found in the second table within this press release. Both tables include all the same software and hardware, summing to the same market size.

As it relates to the branded view of the hyperconverged systems market, Dell Technologies was the largest supplier with $708.4 million in revenue and a 35.1% share. Nutanix generated $262.2 million in branded hardware revenue, representing 13.0% of the total HCI market during the quarter. There was a 3-way tie* for third between Cisco, Hewlett Packard Enterprise, and Lenovo, generating $109.0 million, $91.9 million, and $91.5 million in revenue each, which represents 5.4%, 4.6%, and 4.5% share of the market share respectively.

EMEA purpose-built backup appliances market shows growth

The EMEA purpose-built backup appliance (PBBA) market rose in value 2.7% year-on-year to reach $325.5 million in the third quarter of 2019, according to International Data Corporation's (IDC) Worldwide Quarterly Purpose-Built Backup Appliance Tracker. This follows the 6.3% YoY decline seen in the second quarter of 2019, bringing the market back to growth.

Total EMEA PBBA open systems shipments were valued at $307.5 million, which represented an increase of 5.7% year-on-year. Conversely, mainframe system sales decreased 31% year-on-year in 3Q19.

Regional Highlights

Western Europe

The PBBA tracker for Western Europe indicates a nearly flat performance of this region in terms of value, with 0.9% year-on-year growth, reaching $262.9 million in the third quarter of 2019.

The DACH market became the largest in Western Europe in 3Q19, responsible for 36.2% of the market's value and growth of 33.3% year-on-year.

The United Kingdom lost 6.3% of market value, gaining second place in the Western European PBBA market, suffering a contraction of 19% year-on-year in value.

The French PBBA market ranked third 39.3% growth year-on-year in value, giving it a 14.2% market share.

"The United Kingdom and Germany are the main drivers in the development of data protection technology in Europe," said Jimena Sisa, senior research analyst, EMEA Storage Systems, IDC. "Organizations are becoming increasingly disposed to update their legacy or third-platform technologies with tools that provide more functionality in terms of automation, better monitoring deployment, data management, analytics and orchestration. This is creating more desire to engage in cloud-based data protection-related projects that would help companies to grow their business in a digital transformation era."

CEMA

The PBBA market in Central and Eastern Europe, Middle East and Africa (CEMA) again recorded growth in value (12.2% YoY) in 3Q19, reaching $58.38 million.

The Middle East and Africa (MEA) market was the subregion that prevented the EMEA backup appliances market recording a decline. The major vendors in the open systems space recorded significant growth. The Central and Eastern European (CEE) region had more subdued performance, but nevertheless most companies closed a successful quarter.

"In countries like Saudi Arabia, Egypt, and Israel, there was a demand for larger-drive systems with increased data reduction, backup, and restore rates," said Marina Kostova, research manager, EMEA storage systems, IDC. “In CEE, the large countries of Poland and Russia saw increased shipments for both incumbents and data protection companies, while smaller countries experienced and overall slowdown in infrastructure spending, affecting PBBA as well."

The IT infrastructure of a typical organisation has become much more critical and much more complex in the digital world. Flexibility, agility, scalability and speed are the watchwords of the digital business. To meet these requirements, it’s highly likely that a company must use a multi-IT environment, leveraging a mixture of on-premise, colocation, managed services and Cloud infrastructure.

However, with this exciting new world of digital possibilities comes a whole new level of complexity, which needs to be properly managed. If an application is underperforming, just how easily can the underlying infrastructure problem be identified and resolved? Is the problem in-house or with one of the third party infrastructure or service providers? Is the problem to do with the storage? Or, maybe, the network? Does the application need to be moved?

Right now, obtaining the answer to these and many other performance-related questions relies on a host of monitoring tools. Many of these can highlight performance issues, but not all of them can isolate the cause(s), and few, if any, of them can provide fast, reliable and consistent application performance problem resolution – let alone predict future problems and/or recommend infrastructure improvements designed to enhance application performance.

Application performance monitoring, network performance monitoring and infrastructure performance monitoring tools all have a role to play when it comes to application performance optimisation. But what if there was a single tool that integrated and enhanced these monitoring solutions and, what’s more, provided an enhanced, AI-driven analytics capability?

Step forward AIOps. A relatively new IT discipline, AIOps provides automated, proactive (application) performance monitoring and analysis to help optimise the increasingly complex IT infrastructure landscape. The four major benefits of AIOps are:

1)     Faster time to infrastructure fault resolution – great news for the service desk

2)     Connecting performance insights to business outcomes – great news for the business

3)     Faster and more accurate decision-making for the IT team – great news for the IT department

4)     Helping to break down the IT silos into one integrated, business-enabling technology department – good news for everyone!

AIOps is still in its infancy, but its potential has been recognised by many of the major IT vendors and service and cloud providers and, equally important, by an increasing number of end users who recognise that automation, integration and optimisation are vital pillars of application performance.

Set against this background, Angel Business Communications, the Digitalisation World publisher, is running a one day event, entitled: AIOPs – enabling application optimisation. This one-day event will be dedicated to AIOPs - as an essential foundation for application optimisation – recognising the importance of proactive, predictive performance monitoring and analysis in an increasingly complex IT landscape.

Presentations will focus on:

• Why AIOps is a vital part of the new hybrid data centre and wider IT landscape
• AIOps as a replacement for existing monitoring tools, providing a new level of intelligence and proactive analysis, all designed to improve application optimisation
• Optimising the hybrid infrastructure and faster time to infrastructure fault resolution
• How AIOps can benefit from faster and more accurate decision-making for IT teams (storage, networks, apps, service desk etc.)
• Connecting performance insights (infrastructure/app) to business outcomes
• Panel Session: Making sense of the new hybrid IT landscape and why monitoring and analysis is so critical and how AIOps adds a new level/layer of valuable information to help improve application optimisation
• AIOps in action: Customer story
• Faster fault cause analysis, faster alerts, faster problem analysis
• Improving infrastructure/capacity bottlenecks, and recommended infrastructure improvements
• The impact of AIOps in terms of improving application optimisation
• AIOps in action: Customer story
• Panel Session: How will AIOps augment and/or replace traditional monitoring and analysis tools. What does the optimum AIOps solution look like?

Companies participating in the event to date include: Bloor Research, Dynatrace, Masergy, SynaTek, Virtana, Zenoss.

To find out more about this new event – whether as a potential sponsor or attendee, visit the AIOPS Solutions website: https://aiopssolutions.com/

Or contact Jackie Cannon, Event Director:

Email: jackie.cannon@angelbc.com

Tel: +44 (0)1923 690 205

In the next year alone, Gartner has forecast worldwide 5G network infrastructure revenue will reach a staggering $4.2 billion. That’s almost double its current value. The analyst house has claimed that, despite still being in the early days, ‘vendors, regulators and standards bodies’ alike all have preparations in place.

Meanwhile, the UK government is pushing back against planning authorities that are attempting to halt the installation of 5G masts, with a spokesperson for the Department for Culture, Media and Sport (DCMS) expressing the government’s commitment to 5G, highlighting the economic benefits of the roll-out.

Even as the first 5G services are starting to go live, however, there are still many questions that remain unanswered. To ask how fifth generation networks will affect life inside the data centre, therefore, is similar to asking how a city would stand up to a natural disaster. It depends on the city and the storm.

Moving to the edge

We now know enough about 5G to know that it will without doubt change how data centres are designed and, in some cases, will even alter the role that they play in the larger network. From a technical standpoint, 5G will have several defining characteristics.

The most obvious of these is the use of the 5G New Radio (NR) air interface. Exploiting modern spectrums and providing latency capabilities in just milliseconds, this enhanced performance will drive the deployment of billions of edge-based connected devices. It will also create the need for flexible user-centric networks, pushing the compute and storage resources closer to both users and the devices.

The only way to meet these ultra-reliable, low latency requirements will be to deploy edge nodes as mesh networks, with an east-to-west flow and parallel data paths. In some cases, these nodes may be big enough to classify as pod-type data centres or micro data centres in their own right, similar to those being used by both telecom and cable providers.

Preparing for disruption

Cloud-scale data centres – as well as larger, enterprise facilities – may be the only ones to see just some impact of this move. They are already using distributed processing and have been designed to deal with increased data flow from the edge. At the other end of the scale, retail multi-tenant data centres (MTDCs) will likely incur the most disruption, as they have traditionally grown in response to rising demand for cloud-scale services.

The biggest changes, however, will be seen among service providers. As they begin to refine their relationship between core data centres and evolving centralised RAN (CRAN) hubs, adaptation will become a choice of sink or swim. Increasing virtualisation of the core networks and the radio-access networks will be key when it comes to handling the anticipated 5G data flow. This will also enable service providers to be more flexible with compute and storage capacity, easily moving it to where is most needed.

More broadly across service provider networks, increasing virtualisation may have a more direct effect in the core data centre, with wireless and wireline networks becoming more converged. This will generate an even stronger business case for a single physical layer infrastructure, it then just depends on the degree of convergence that occurs between the core network and the RAN. Whether this occurs in a central office or in a data centre, we still don’t know.

The role of new tech

Aside from considering cloud models, we also need to focus on the impact that new technologies such as artificial intelligence (AI) and machine learning (ML) will have on data centres when 5G makes its mark. These technologies will not only require accelerated server speeds, but also higher network capacity to enable greater volume of growing edge services. When building these data models, processing vast data pools will be essential which, in most cases, are best suited to core data centre capabilities.

Most of the data that goes on to develop AI models will come from the edge. This nods to a potential shift in how more established, cloud-scale data centres will support the network. One potential use-case involves using the power of the core data centre to assemble data from the edge to develop the AI models. These would then be pushed out to deliver localised, low-latency services. The process would then be repeated, in turn creating a feedback loop that revolutionises the operating model.

A balancing act

As with any other aspect of digital transformation, the level and requirement of change within various data centre environments will depend on the individual application. Data streams generated by the billions of sensors and devices may well produce a steady flow of data, whereas others might be delivered intermittently or in irregular bursts. Either way, it’s very much out of our control. It’s how the data is then collected, processed and analysed that needs to be optimised, considering factors such as how much data should remain local to the edge device, and how much should be processed in the core centre?

Once these questions are answered, network engineers need to determine the best way to move the data through the network. Different latency and reliability requirements require the ability to prioritise data traffic at a very granular level. What can be off-loaded onto the internet via local Wi-Fi versus having to be backhauled to the cloud service provider (CSP) data centre?  And remember, edge networks must fit into a financial model that makes it profitable. 

Infrastructure as an enabler

The widespread roll-out of 5G is still a few years away, but there is no better time to start preparing for what’s to come. At the very core of this evolution, infrastructure must adapt to support higher wireless bandwidth and more universal data usage. Behind closed doors, organisations and building owners are considering more than just Wi-Fi to enable robust and dependable in-building mobile wireless with distributed antenna systems (DAS). Outdoors, it’s a different story. Service providers are upgrading and expanding their fiber networks to carry wireless data back to the core of the network, or in many cases, to edge data centres.

What we really need to think about, is the applications and innovations that these changes will develop as part of a 5G era more broadly. Self-driving cars, facial recognition, smart cities and industrial automation will all be made possible and more advanced by 5G. The problem remains, however, that each of these applications all have a varied set of requirements regarding reliability, latency, and the type/volume of data traffic generated. Unless you therefore understand the parameters of the situation, it’s difficult to pinpoint it’s exact impact on the data centre.

Something we do know, however, is that the avalanche of new data from the network edge, and thanks to 5G, goes hand-in-hand with high compute and storage power. Exactly how much power? You guessed it: that depends!

Ever since analogue mobile phones first appeared in the early 80s, we’ve become used to a steady evolution of performance and functionality, through 2G, 3G, 4G and their variations.

This evolution has led us to 5G; a concept that is now becoming reality.  Services are already starting to roll out in the UK, US and South Korea, and another 80 operators in 46 countries plan to launch 5G services between now and 2022.

The standard is truly a game-changer because its performance, in terms of speed, latency and connection densities, is such a significant improvement over 4G (or even the ‘4.5G’ technologies, 4G LTE-Advanced and LTE Advanced pro) that it will enable entirely new applications that simply weren’t viable with the earlier standards.

Remote surgery is a good example of this; because a 5G network virtually eliminates the small lag between pinging the network and receiving its response, a surgeon can control a robot arm remotely, without having his precision compromised by feedback delay.

5G could also facilitate driverless cars; the network’s instant response and ubiquitous coverage will allow the cars to use 5G to talk to other cars and sensors built around the city, from street lamps to petrol stations.

Many of these emerging opportunities owe as much to timing as they do to the promise of 5G. Progress in cellular wireless technology has been matched by equally impressive developments in the Internet of Things (IoT) – and the IoT currently comprises sets of geographically distributed smart devices that must communicate, often wirelessly, with a local facility and on to a centralised – typically cloud-based - data processing and analysis resource. So, by giving the IoT wireless channels a step increase in power, 5G will enable a new generation of remote smart devices that reach similarly heightened levels of performance and functionality.

But this new 5G landscape has major implications for the data centres that must handle the data they generate, in terms of performance, capacity, and geographical distribution. Below, we take a closer look at this impact on data centres and their associated power requirements; finally, we show how modern, modular UPS technology can meet this new set of challenges.

Expected 5G impact on data centres

The relationship between 5G and the IoT is highlighted by a Gartner survey[i], in which 57% of respondents reported that their main interest in 5G was to drive IoT communications - and with potentially billions of IoT-connected devices, the amount of data generated will be huge. 5G is estimated to be able to handle 1000 times more connected devices per metre than 4G without being affected by bandwidth congestion, meaning more devices can work in closer proximity. 

Additionally, 5G’s bandwidth and speed - estimated to be between 20 and 100 times faster than 4G - will allow it to compete with ISPs’ traditional broadband wired connections; so creating a further huge demand for data processing and storage capacity, and hence data centres. Data centres will also need to compress data to handle the increase in, for example, video streams. This will require new technologies and compression algorithms.

Data centres and telecom providers will therefore require the right high-performance hardware and technology to handle the routing and switching necessary to match the flow of data; additionally, they will need to manage their power consumption. This is not only for cost efficiency, but also due to increasing pressure to demonstrate a greener footprint, and in many cases, the need to avoid upgrading power feeds into the data centre. One solution is installing software defined power (SDP) based on both hardware and software that can skilfully allocate power throughout the data centre, and another is to select more energy efficient equipment; this will save both direct energy costs, and costs associated with keeping the equipment cool.

Data centres that have set up for 4G will have the capacity for handling 5G data. However, they will have to change their infrastructure to cater for 5G’s frequencies. 5G uses short wavelengths, which means small cells rather than large cell towers scattered around the country. These super-high frequencies (30 GHz to 300 GHz) will only work if devices are in close proximity to antennas. Therefore, it is likely we will see multiple input and output antennas (MIMOs) and many more small cells installed around public infrastructure.

Small cells have a clear advantage over traditional cell sites as they can be located in areas which lack space for large cell towers. What’s more, they are cheaper to deploy. Data centres will, however, need to be close enough to these cells to maintain 5G’s low latency performance and meet service-level agreements. In some cases micro data centres might even be deployed at the base of cell towers, allowing limited data processing with even faster response times for critical applications like autonomous vehicles.

These trends will likely lead to the break-up of larger data centres into smaller, more local data centres close to these cells. The new, low latency IoT-type applications such as the above remote surgery and driverless cars examples will clearly depend on data processing, communications channels and power infrastructures that offer very highly reliability alongside ground-breaking performance. This will call for Tier 3 and Tier 4 data centres with near 100% redundancy.

Implications for UPSs

The above predictions for 5G indicate that there will be a proliferation of small and very small data centres - but these data centres, however small, must be just as reliable as the best of their larger counterparts. So how can UPS technology facilitate the scaled-down yet highly-reliable power solutions essential to such environments?

The answer lies with today’s transformerless modular topology, as exemplified by Kohler Uninterruptible Power’s PowerWAVE 8000DPA UPS – See Fig.1. Designed for low to medium-scale high power density applications, the UPS offers high energy efficiency, 99.9999% (‘Six Nines’) availability and flexible scalability in a tower or rack-mountable configuration.

While a single module can be used to deliver 10 kW or 20 kW, further modules can be added incrementally to increase capacity or provide N+1 (or N+n) redundancy. Up to 80kW (60kW N+1) rack-mounting capacity can be provided, with an ultimate capacity of 400kW for two fully-populated tower versions in parallel.

The PowerWAVE 8000DPA’s rack-mounting capability and high power density allows it into restricted spaces,  while its high energy efficiency minimises the heat to be extracted from such spaces. As well as the completely self-contained UPS, each module includes battery and communications capability. This allows monitoring of UPSs in remote data centres from a centralised location.

The system’s Decentralised Parallel Architecture (DPA) means that single points of failure are eliminated, and uptime is maximised. Mean time to repair (MTTR) is minimised, as the modules are ‘hot swappable’ and can be safely removed and replaced without interrupting power to the critical load.

Fig.1: PowerWAVE 8000DPA UPS system - rack-mounting version[NC1] 

Effective maintenance is essential too

While providing a UPS of suitable size, scalability, efficiency and availability is essential for the new generation of small 5G-oriented data centres, this alone is not enough. To be kept in prime condition and optimally reliable, the UPS, especially its battery, must be regularly monitored and maintained. This can be challenging for an implementation comprising many small data centres distributed over a wide geographical area.

An experienced and well-resourced UPS supplier like Kohler Uninterruptible Power can solve situations like this. Firstly, they offer remote monitoring services including PowerREPORTER Remote UPS Monitoring, and PowerNSURE Battery Monitoring.

PowerNSURE not only provides battery monitoring, but also performs proactive maintenance. It checks every battery’s internal resistance, temperature and voltage, and reports on the results – see Fig.2. Additionally, it executes an equalisation process to keep battery charging voltages within operating range. By preventing gassing, dry-out and thermal runaway, this assures continuous battery availability.

PowerREPORTER communicates constantly with UPS systems, and detects any fault conditions or alarm messages. While customers can monitor all of their UPS systems centrally, any incident is reported to KUP’s Service Centre by email, complete with status and any available details. The Centre’s personnel can pass this information to the field team, allowing them to reach the UPS site within the contracted service agreement time, already briefed on the issue and equipped to resolve it rapidly.

Fig.2: PowerNSURE battery monitoring report, highlighting a weakness in Battery 6[NC1] 

KUP’s remote monitoring services are complemented by their nationwide team of trained field engineers. Covering the entire UK, this team not only responds to alarm callouts as described, but also performs scheduled maintenance visits to comply with any established service agreement. Emerging problems are fixed before they can cause failures, so the power protection system’s maximum possible availability is assured.

Conclusion

In recent years, popular news has focused on the drive by organisations like Google and Facebook to build hyperscale data centres. However, the rise of the IoT and expected growth in 5G means that, for many users, the emphasis will shift towards smaller, sometimes micro-scale facilities.

These will call for UPSs that are suitably scaled down, while still offering levels of availability associated with Tier 3 and 4 installations. They must be compact, scalable, simply installed, efficient, and easy to manage remotely.

But it’s not just about providing the right hardware. Critically, the UPS supplier must have the remote monitoring technology and field service infrastructure needed to guarantee that UPSs in multiple facilities spread over a wide geographical area unfailingly achieve their full performance and availability potential.

“Driven by the need for on-demand services and automation, there will be a surge in requirements for the use of technology that interconnects through APIs. Vendors that don’t interconnect may find themselves passed over for selection in favour of others with API access that add value to existing solutions.

DevOps capabilities will continue to increase their significance in moving projects to products, with only 9% of technology professionals responsible for the development and quality of web and mobile applications stating that they had not adopted DevOps and had no plans to do so. This will drive an increased focus on DevSecOps and how opensource software is managed within projects.

We will begin to see more examples of the theft of encrypted data as cybercriminals begin to stockpile information in preparation for the benefits of quantum-computing where traditional encryption will become easy to crack.  The advances in quantum computing that Google has recently published bring this possibility closer to becoming reality.

Significant issues will surface around the lack of adequate detection of threats that have bypassed prevention defences.  To combat this, in 2020, we will see the addition of deception technology into security framework guidelines, compliance requirements, and as a factor in cyber insurance premiums and coverage.”

Uncommon attack techniques will emerge in common software 

Steganography, the process of hiding files in a different format, will grow in popularity as online blogs make it possible for threat actors to grasp the technique. Recent BlackBerry research found malicious payloads residing in WAV audio files, which have been utilised for decades and categorised as benign. Businesses will begin to recalibrate how legacy software is defined and treated and effectively invest in operational security around them. Companies will look for ways to secure less commonly weaponised file formats, like JPEG, PNG, GIF, etc. without hindering users as they navigate the modern computing platforms. 

Changing network topologies challenge traditional assumptions, require new security models

Network-based threats that can compromise the availability and integrity of 5G networks will push governments and enterprises alike to adopt cybersecurity strategies as they implement 5G spectrum. As cities, towns and government agencies continue to overhaul their networks, sophisticated attackers will begin to tap into software vulnerabilities as expansion of bandwidth that 5G requires creates a larger attack surface. Governments and enterprises will need to retool their network, device and application security, and we will see many lean towards a zero-trust approach for identity and authorisation on a 5G network. Threat detection and threat intelligence will need to be driven by AI/ML to keep up.

2020 will see more cyber/physical convergence

As all sectors increasingly rely on smart technology to operate and function, the gap between the cyber and physical will officially converge. This is evident given the recent software bug in an Ohio power plant that impact hospitals, police departments, subway systems and more in both the U.S. and Canada. Attacks on IoT devices will have a domino effect and leaders will be challenged to think of unified cyber-physical security in a hybrid threat landscape. Cybersecurity will begin to be built into advanced technologies by design to keep pace with the speed of IoT convergence and the vulnerabilities that come with it. 

State and state-sponsored cyber groups are the new proxy for international relations

Cyber espionage has been going on since the introduction of the internet, with Russia, China, Iran and North Korea seen as major players. In 2020, we will see a new set of countries using the same tactics, techniques, and procedures (TTPs) as these superpowers against rivals both inside and outside national borders. Mobile cyber espionage will also become a more common threat vector as mobile users are significant attack vector for organisations that allow employees to use personal devices on company networks. We will see threat actors perform cross-platform campaigns that leverage both mobile and traditional desktop malware. Recent research discovered nation-state based mobile cyber espionage activity across the Big 4, as well as in Vietnam and there’s likely going to be more attacks coming in the future. This will create more complexity for governments and enterprises as they try to attribute these attacks, with more actors and more endpoints in play at larger scale.

If this last year has taught us one thing, it is never to take cyber security for granted. Threats continue to develop as quickly as new technology emerges. Hackers continue to use age-old techniques on new vulnerabilities. Organisations who fail to adequately protect their data continue to suffer the ramifications of large fines. As we move into a new decade, there is no room for complacency.

New Year, old tricks

Another key learning point from the year has been to never underestimate the opportunistic skills of hackers. When there’s economic gain to be had, they’ll always find innovative ways to use existing malware and ransomware techniques to mount new attacks.

For example, we are seeing image-based spam re-emerge as a major threat in the cyber space. Thirteen years after image-based spam was at its peak, a newer, darker version is back. If a message is composed using an image, there’s a chance it can evade most spam filters, even today. Steganography is a technique which was prevalent over a decade ago that we are seeing used by hackers leveraging the rapid growth of social media to deliver a malicious payload. If recipients are not cyber aware, then it’s easy to take the bait and with nearly half of data breaches in the last year being caused by internal error, it’s no wonder hackers circle back and take their chances using old-school methods.  

To help put these threats to bed, optical character recognition and anti-steganography technology within data loss prevention solutions need to be adopted as standard by organisations as we move into 2020. With these technologies applied, images can be processed just like a normal electronic document where they are analysed, and any sensitive information is redacted or removed from the file.

Clearly, in the same way that we know not to trust an image just because it looks innocent, we must not assume that just because certain threats haven’t been seen for a while, they won’t occur again moving forward.

Innovation will threaten security

The latest claim from Google of achieving ‘quantum supremacy’ reignites fears that quantum computers could break most modern cryptography, and effectively be the end of encryption as we know it. Though this threat is hypothetical, it feeds into the wider concern that the increasing sophistication of the technology used by both businesses and cybercriminals will boost the ability to exploit vulnerabilities in 2020.

The reality is, as new technologies are emerging, new threats are appearing alongside them. With the increasing use of biometric data by the public and private sector alike, critical national infrastructure (CNI) organisations are storing more valuable data than ever. The defence sector will increasingly be targeted due to the lucrative nature of the data they store, and this is something that will continue to rise.

To deal with these threats effectively, an evolving cyber strategy for 2020 is needed which can adapt as technology advances. Regular reviews of cyber strategies are imperative, and any new technologies introduced throughout the year must be assessed and paired with appropriate levels of security. If we’re prepared for what’s around the corner, we can make the most of new technology at the same time as protecting our businesses.

Internet of Things (IoT) is growing exponentially with some forecasts estimating total number of IoT devices by 2025 to be north of 25 billion devices. For a layman, IoT devices are small, low-powered devices that generate infrequent low-volume traffic, such as smart meters. While that is generally true, IoT devices cover a much larger segment. One could classify IoT into two categories – wide-area IoT and short-range IoT.

Wide-area IoT: Low Power and Long Range

Wide-area IoT devices are generally low power and transmit infrequent short bursts of data over a low-power wide area network (LPWAN). These devices are generally installed in remote areas with no external power supply (i.e., they are running on batteries) and therefore are expected to be very power efficient. LPWANs can work in both licensed spectrum as well as unlicensed spectrum. Two of the most common LPWAN technologies that work in unlicensed spectrum are SigFox and long-range wide area network (LoRaWAN). Those that work in licensed spectrum are narrowband (NB) -IoT and LTE-M or LTE machine type communication, also known as Cat-M1, both of which are specified by 3GPP in Release 13 and are collectively known as cellular IoT.

SigFox is a proprietary technology owned by a French company of same name. It is ultra-narrowband technology enabling wireless signals to pass freely through solid objects making it suitable for underground and in-building operations. SigFox operates in 868MHz band in Europe and 902MHz band in U.S. It is designed to support arrays of devices likely to send small amounts of data (100 bytes per second) in short bursts (e.g. parking sensors, utility meters). As of end of 2018, a little more than 60 countries had SigFox-based deployments.

LoRaWAN is a spread-spectrum technology with a wider band than SigFox. LoRaWAN is actually a medium access control protocol running on top of the Long Range (LoRa) physical layer (PHY) protocol operating in unlicensed bands such as 433 MHz and 868MH in Europe, and 915 MHz in Australia and North America. LoRaWAN technology is licensed by SemTech and has been developed under the LoRaWAN alliance since 2015. As of end of 2018, about 100 countries had LoRaWAN-based IoT deployments.

Short-range IoT: Higher Power Requirements, PAN or LAN Connected

Before we jump into cellular IoT, let us briefly look at short-range IoT devices. These generally need higher power, but still significantly lower than most smartphones, and exchange higher amounts of data. Because of the higher power requirement, these devices either need to be frequently recharged or need an external power supply source. These devices can be further divided into personal area network (PAN) or local area network (LAN). PAN IoT devices have a range of few feet and the most common technologies connecting these devices are Bluetooth, ZigBee and 6LoWPAN or IPv6 low-powered wireless personal area network. The most common PAN IoT devices are headphones, fitness tracking devices, etc. LAN IoT devices have a range of hundreds of feet generally and use some version of 802.11 wireless LAN technology for the underlying connectivity. PAN IoT devices generally run on rechargeable batteries, while LAN IoT devices run on both rechargeable batteries, as well as external power sources. The most common LAN IoT devices are security cameras, home appliances such as refrigerators, etc. A single device can be part of both PAN as well as LAN IoT networks. Such a device could aggregate information from a PAN IoT network into a LAN IoT network, which could then connect to a WAN or the internet through an IoT gateway.

Per Ericsson’s Mobility Report, June 2019, wide-area IoT devices, numbering at about one billion, make up a little more than one-tenth of all IoT deployments today and are growing at a 27 percent CAGR to reach 4.5 billion devices by 2024. Short-range IoT devices make up about 90 percent of deployments and are growing at a 15 percent CAGR to about 18 billion devices by 2024. Short-range IoT devices are going to continue to exist in the market in the foreseeable future.

Wide-area IoT devices are going to see exponential growth, especially with introduction of 5G service-based architecture (SBA) core, which will scale much more compared to the 4G LTE packet core. Similarly, we expect LPWAN deployments based on unlicensed spectrum technologies such as SigFox and LoRaWAN to continue to exist and proliferate, albeit at a much lower rate than cellular IoT.

Current Cellular IoT Technologies Bridge 4G LTE and 5G NSA

Cellular IoT technologies, NB-IOT and LTE-M, are deployed as part of the LTE network today and are expected to work with 5G networks using the non-standalone (NSA) architecture. In 5G NSA, the radio interface will still be LTE-based, while the core network will be 5G SBA. As 5G new radio (NR) technology for IoT in Release 16 and beyond is developed, we will start seeing 5G NR-based IoT devices deployed in standalone (SA) mode with the 5G SBA packet core.

What is the difference between NB-IoT and LTE-M?

Before we go any further, one question that usually comes up is why we need NB-IoT and LTE-M as two different technologies in Release 13. LTE-M supports lower device complexity, massive connection density, low device power consumption, low latency and provides extended coverage, while allowing the reuse of the LTE installed base. NB-IoT is characterized by improved indoor coverage, support of massive number of low throughput devices, low delay sensitivity, ultra-low device cost, low device power consumption and optimized network architecture.

This makes them sound awfully similar. However, there are some notable differences: 1) LTE-M supports higher bandwidth [1.4MHz with data rates of up to 1Mbps], while NB-IoT supports lower bandwidth [200 MHz with data rates < 100 Kbps]; 2) LTE-M supports device mobility, while NB-IoT does not; 3) LTE-M supports voice traffic using VoLTE, while NB-IoT is restricted to data only; 4) LTE-M works at higher frequency band, while NB-IoT works in a lower frequency band making it excellent for indoor uses, while LTE-M may not be as good for indoor use; 5) finally, LTE-M has much lower latency (50 – 100 ms) as compared to NB-IoT, which is usually 30 to 100 times of LTE-M at (1.5 to 10 sec).

LTE-M and NB-IoT integration into the existing LTE network. Service Capability Exposure Function (SCEF) is the new entity added into the LTE network in Release 13. To help meet the low power requirements for LTE-M and NB-IoT, the power-hungry protocol to establish IP data bearers has been replaced by extending the non-access stratum (NAS) protocol to allow small amounts of data to be transferred over the control plane. In this case, the IP stack is not necessary, so this type of transfer has been named Non-IP Data Delivery (NIDD) and is shown with the red large dashed line in Figure 1 below.

3GPP defined SCEF to be the interface for small data transfers and control messaging between enterprises’ IoT application servers and the operator’s core network. SCEF provides APIs to the enterprises for the small data transfers and control messages and uses 3GPP-defined interfaces with the network elements in the operator’s core network to perform its functions. Release 13 also supports IoT IP data delivery with NAS control plane, which is shown in Figure 1 below with green small dashed line.

Cellular IoT in 4G LTE Network

In a 5G SBA core, Network Exposure Function (NEF) provides small data delivery service similar to the Non-IP Data Delivery (NIDD) service of 4G SCEF, exposing APIs to application servers. Figure 2 below shows existing NB-IoT and LTE-M networks connecting to the 5G SBA core in non-standalone mode. NEF is the interface for small data transfers and control messaging between enterprises’ IoT application servers and the operator’s 5G core network. The NIDD data transfer is shown with red large dashed line in the Figure 2 below. IoT IP data delivery with NAS control plane is shown with green small dashed line.

Cellular IoT with 5G SBA Core

In summary, currently deployed LTE-M and NB-IoT devices will connect to the 5G SBA core in non-standalone mode, as the 5G SBA core gets deployed. Most of the cellular IoT deployment today is with the 4G network, providing device density of about 60K devices for every square kilometer. Massive IoT deployment requirements in 5G call for device density to be scaled to a minimum of one million devices for every square kilometer. 3GPP is working on enhancements to 5G technical specifications to get to this density in Release 16 (expected to be completed by June 2020) and Release 17 (expected to be completed by end of 2021 or early 2022).

Land Grab

The promise of 5G has been compelling for many reasons. From businesses looking to achieve widespread IoT deployments, to those seeking a viable broadband and leased line replacement alternative or companies struggling in areas of rural connectivity deprivation, on paper 5G appears to have all the answers. The recent 5G roll out announcements, however, have been something of a disappointment for all. Limited to just six cities initially (EE) – and with variable accessibility even within these areas – the 5G rollout is a promise rather than a reality. It will take several years before 5G offers ubiquitous accessibility – and there are no firm plans to support rural areas and manufacturing – rather, a set of innovation challenges that are funding Consortia projects to look at innovation to address the problem. Even then, a number of key features of the service are still to be clarified.

The reality today is that 5G – where it is available – is providing enhanced mobile broadband and no more. For those with compatible devices – an issue in itself given the lack of available devices and the Huawei situation – 5G will enable voice calls and broadband internet access. Even then, the promised speeds are not being delivered – customers can expect 150-200Mbps at best, and on the Vodafone commercial plans we see ‘guarantees’ of 2Mbps, 10Mbps or ’the fastest available’ – this falls short of the Gigabit speeds promised. Furthermore, consistency is a very concerning issue, with both speed and coverage variable within the launch city locations. On the plus side, Vodafone has offered an ‘Unlimited’ data plan that will begin to chip away at one of the big pillars of operator revenues, i.e. the mobile data costs.

So why have EE, Vodafone and Three rushed to announce 5G networks that are still more of a half-promise than a reality? The answer is a land grab, to try and get to market first with something, rather than nothing. The impact for businesses that want to make investments in high speed wireless technology, leveraging the value of repeatable, consistent, widespread and easy to use services, is that 5G is already a significant disappointment. Carriers will need to raise their game significantly if they want businesses to invest their communications budgets in the new technology.

5G Dissected

While the Tier 1 network providers are promising to rapidly expand the 5G network range – with EE planning to upgrade more than 100 sites to 5G every month – this is very much a work in progress. On the plus side, the 5G network will address the capacity issues facing overloaded 4G networks, enabling millions of additional connections on existing spectrum.

But what about the other key aspects of the 5G network offering? 5G has been touted as a viable alternative to leased lines and a chance for companies to avoid expensive fibre or copper-based Ethernet connections. Unfortunately, the promised Fixed Wireless Access based on ‘millimeter wave’ (FWA) – essentially very high speed connections between two points – requires significant infrastructure change that the network providers are struggling to deliver. Rather than towers, FWA is a very short range service and, as such, demands very high antenna density, with small cells (antennas) deployed on buildings, street furniture and lamp posts 10metres apart. Network providers have overestimated the willingness of local authorities and building owners to provide the planning permission required to install antennas on lampposts and buildings. Without antenna density, FWA is not a viable, scalable option for business connectivity; at best companies will have to wait three years or more before 5G offers a viable wireless leased line alternative. At the time of writing, Three UK has just launched their FWA offering in a few postcode areas in London for home broadband, and already there are accounts of intermittent signal problems impacting performance, which lends weight to the argument for more antenna density being required to achieve stable, repeatable service coverage.

At worst, of course, the continuing concerns regarding the potential health implications of 5G networks could further delay installation. Local authorities will remain wary about exposing the public to risk; unless and until the 5G industry can address in a concerted, focused way that the persistent claims that running high frequency networks in high density areas is not a risk, planners may meet resistance from schools, hospitals, and community building managers.

There are other shortcomings. 5G services today do not include any Service Level Agreements, undermining any business confidence in the quality and repeatability of the service. There seems to be no ‘network slicing’ (the technique to separate traffic types), making it impossible to prioritise network traffic – such as IoT. Indeed, the entire IoT aspect of 5G has been shelved for now, with both EE and Vodafone confirming that IoT will not be part of the initial service. There is no clarity regarding support for IoT devices in the future, the ability to upgrade or migrate from current to 5G networks or any commercial information that would help both Managed Service Providers and businesses build 5G into their future IoT strategies.

What to do: Use what we have already - mature 4G services

So what are the options? 5G is disappointing but companies cannot afford to postpone much needed network investments in wireless primary and backup services indefinitely.  The good news is that 4G networks are now mature – and that means both widely available and reliable. The arrival of 5G will address the burgeoning capacity issue for 4G, which is great news; and recent market price adjustments have taken 4G out of the last resort category into a viable option for primary and resilience connectivity. 

4G is proven to support VoIP and Unified Communication streaming; it can also be used for machine to machine communication. Software Defined Networking (SDN) enables 4G to be blended with other networks to deliver primary connections that deliver a reliable and affordable leased line alternative. Furthermore, IoT is deliverable today using the unlicensed spectrum and other standards, including NarrowBand IoT and LoRaWAN, to enable mass IoT deployments (which will be incorporated later into the emerging 5G standard, future proofing investment).

Critically, all of these services come with SLAs; networks are reliable and accessible. Essentially, it is possible today to meet business needs for affordable and consistent primary and secondary connectivity services with the existing 4G network infrastructure.

Conclusion

5G technology looks good on paper and there have been significant deployments in the US and other countries. But there remain a number of very significant infrastructure challenges that continue to undermine 5G value and impact on our business landscape in the short to medium term.

As the 5G network plans and service offerings stand today, businesses will struggle to justify investment in the new technology. However, while waiting for the promise of 5G to be realised, businesses can extract significant value from 4G today. And with further price disruption expected within the 4G market, the cost model will become ever more compelling, for primary, secondary and IoT connectivity.

Politicians know about the importance of context more than most of us – if something they say is taken out of context by the wrong person, the consequences can be severe. The same rule applies in analytics, in the sense that if it is captured, stores and analysed within a vacuum, it’s difficult to derive any meaningful insights.  

Data is one of the most powerful assets we have in the digital era. Yet, it remains redundant if we lack contextual information. Hence, “context is king”.

We rely on context to receive and reveal the truth. When things are taken out of context, however, this aggregates misinformation. Relating this to data analytics language it translates to giving importance to context as the key to avoid gathering of unusable data.

In other words, if on a factory floor an error event occurs every day at the same time, and there is nothing apparently wrong with the machinery, how does a data scientist get to the root of the problem? He/she adds context.

Take, for example, Covestro, which makes high tech polymers materials used in the automotive and construction industries. In its quest to improve its production process, Covestro took a different tack. It knew that hiring an army of data scientists was a challenge - the right ones are hard to find - and if they leave, the company would lose that knowledge. 

Instead it decided to arm its factory engineers with advanced self-service analytics. Coverstro’s knowledge workers analyse the production process daily with the help of the embedded AI and ML models. They improve the effectiveness of those models by feeding in events that they deem relevant. Those events act as context for the models. This vastly enhances the models’ effectiveness in detecting and predicting faults and failures.

Here is how it works: If something happens in the factory that the engineers deem important, it will be logged into what they call the context hub. The engineers can even automate some of the logging, once they figure out that those events are significant for the analytics and happen regularly. That includes things like maintenance events or production situations - like the heat of the engine remaining above a certain level longer than 10 minutes.

In my eyes, those engineers are the front-runners of the next generation of workers. Introducing the Contextualist!

The Contextualist isn’t a technical data scientist, and as such the role will only really thrive if the technology used can be simplified to a point that the analyst’s and developer’s roles are reduced to a minimum. This is going to happen soon, I believe.

Self-service analytics enter the picture

Software companies are putting their efforts and resources toward making existing tech more easily accessible in order to increase mainstream adoption. Currently ML, AI and other technologies are so difficult to implement that only the really big companies can afford the very expensive workforce.

Simplification will come through self-service interfaces, making it easier to apply the technology in a horizontal (generic) way, or through solution accelerators, where domain relevant knowledge and decisions can be applied in a vertical way.

There’s no doubt that new technologies are helping humans do their jobs more effectively, but in order for this collaboration to be its most efficient, a context hub is needed. If the job that you’re doing relies on the effectiveness of AI to augment decisions, then it becomes vital that it is being fed with the relevant contextual information. This will ultimately help organisations improve decision making in the long-term. 

New developments in machine learning are being powered by deep link graph analytics which support unsupervised learning of graph patterns, feature enrichment for supervised learning and explainable models and results. It’s a potent combination that will serve enterprises well for years to come.

We see machine learning (ML) being used for a range of complex computing tasks, including fraud detection, personalised recommendations, predictive analytics, identification of user groups and influential users, reporting weaknesses or bottlenecks in operations and supply chains, and more.

But ML is computationally demanding, and graph-based machine learning no less so. With every hop, or level of connected data, the size of data in the search expands exponentially, requiring massively parallel computation to traverse the data. Computationally this is too expensive for key-value databases as it requires a large number of separate table lookups and for relational database management systems (RDBMS) which must create table joins for every query. Even a standard graph database may not be able to handle deep-link analytics on large graphs.

One solution is a native graph database featuring massively parallel and distributed processing.

Unsupervised machine learning

Applying graph database capabilities to ML is a relatively new, but ultimately not very surprising, development: the Google Knowledge Graph, which popularised the concept of extracting actionable information based on patterns of relationships in data, was introduced in 2012, and graphs are known to be ideal for storing, connecting and drawing inferences from complex data.

That it didn’t happen sooner is down to the fact that, until recently, graph databases didn’t support the algorithms for deep-link analytics and struggled with very large datasets. But using ML algorithms in a native graph database opens new doors to these unsupervised methods, making possible the use of whole classes of graph algorithms to extract meaningful business intelligence including:

●      community detection

●      PageRank

●      label propagation

●      betweenness centrality

●      closeness centrality

●      similarity of neighbourhoods

These algorithms share a common requirement: the ability to gather data and analyse it while traversing large numbers of nodes and edges. This is a powerful feature of modern graph databases. Without it, many of these classes of algorithms would simply not be feasible to run.

Now these algorithms are finding uses in business to tackle a range of ‘difficult’ problems including fraud detection, identifying user groups and communities and reporting weaknesses or bottlenecks in operations and supply chains.

Supervised machine learning

Graph is also giving a boost to supervised machine learning because of its ability to support the analysis of a much richer set of data features – allowing you to deploy more sophisticated ML algorithms.

Consider the problem of detecting spam phone calls on a massive mobile phone network. This was precisely the problem that China Mobile wanted to solve. It has more than 900 million subscribers who make over two billion phone calls a week, but a tiny percentage of those are unwanted or fraudulent phone calls which the operator was keen to disrupt.

The approach was to analyse the data features of the phone that was initiating the call to determine whether it met the risk criteria for being fraudulent and then send a warning to the recipient’s phone – while it was still ringing – to warn them that the caller might be a scammer. The recipient could then decide whether to answer or not.

One could use a simple set of data features to detect phones associated with fraudulent calls, but China Mobile found that relying on duration of phone call and percentage of rejected calls to raise a warning flag resulted in too many legitimate calls being flagged as fraudulent – i.e., false positives.

China Mobile chose to broaden the scope considerably and monitor 118 data features to identify ‘good’ and ‘bad’ phones. The ML algorithms had to be powerful enough to analyse all of these data features and fast enough to do it in the time it took the network to connect a new call. Using ML, it would be possible to classify a caller as good or bad based on their relationships to other phones on the network which could be summarised in three key properties: 

●      Stable group – based on how many phones a given phone calls and receives calls from on a regular basis. Relevant factors include the number of phones it regularly connects with, the frequency of interactions to and from each phone and the duration of the relationship with each phone.

●      In-group connections – the degree of connectedness between the phones that the target phone is in regular contact with.

●      3-step friend relationships – the degree of extended connectedness between the target phone and other phones. Does the given phone have connections with other phones that have connections with other phones that in turn initiate calls to the first phone (forming a sort of friendship loop)?

It turns out that bad phones score consistently and reliably low on these metrics, and it’s difficult for scammers to redress or hide these features of the phones they are using. Using data on known good and bad phones, the ML algorithms can be trained to recognise suspicious patterns of behaviour with a high level of confidence.

But its one thing modelling these metrics and another challenge altogether to implement them across a network of nearly one billion phones in real time. The real time element of this was very important because there is no point warning the recipient of a phone call that it might be fraudulent if you can’t do it while the phone is still ringing – an important consideration in China Mobile’s choice of graph database.

A native graph database not only has the query language to traverse many connections and filter and aggregate the results but also the computational power and underlying system architecture to do this in real time.

Explainable models

A criticism of neural networks and deep-learning networks is they don’t provide insight into causal factors – how did you get this output from those inputs? Without that, you don’t know what factors the ML system is associating with the given output, which erodes confidence in the ability of the system to maintain consistent results over time.

This underscores the importance of explainable models in ML. The objective is to be able to highlight the key variables associated with a result, and it turns out that graph analytics is well suited to compute and show the evidence behind ML decisions.

Explainable ML boosts user confidence in the result. In an online retail environment, the likelihood that a consumer will respond to a product recommendation is higher if the recommendation is accompanied by a reason, such as people you like also liked this product or this product is similar to a previous purchase.

In the more business critical scenario of fraud detection, explainable ML can be a regulatory or audit requirement, and it is also more helpful to fraud investigators if they can see the connections that caused a transaction to be flagged as suspicious rather than just receiving a numerical fraud score.

Graph databases represent data on networked objects in a way that closely mirrors reality, opening new doors to supervised and unsupervised machine learning techniques. It also exposes the underlying decision making process in a way that neural networks do not, satisfying the need for explainable ML models. It’s no surprise then that businesses are turning to graph to solve deep-link data analysis challenges.

A host of predictions from the world of information security:

Data exists everywhere within an enterprise, including databases, data warehouses, data lakes, CRM tools, and ERP systems. But in order to leverage that information, it is critical to understand how to access, refine, apply, and manage that data to make smarter business decisions.

While it’s more straightforward for companies that started off digitally native to think data first, it is a lot harder for legacy companies that are just starting out on their digital transformation journeys.

One company that is truly excelling in its data strategy is none other than media-services provider and production company, Netflix. Unlike its media rivals, who are legacy behemoths, Netflix uses data to drive every decision, from content development to its creative and marketing strategies. The data Netflix collects helps the company glean deep insights into every customers’ preferences and usage habits in real-time, empowering them to make almost all strategic and tactical business and operational decisions based on data.

There’s no doubt Netflix is a modern data company in today’s digital era, and its impact is felt across multiple industries. How can companies take a leaf out of Netflix’s data philosophy and begin their journey towards being truly digital?

Step 1: Ensure your data is accessible, easy to discover, and easy to process for everyone

In most organisations, the access and availability of data is controlled and managed through a centralised group of database administrators (DBAs) with no self-service capabilities for practitioners who need data. Data access and availability remains a set of ticket-driven manual processes with excessive workloads being put on the DBAs to do repetitive low-value tasks. But data should be accessible by those who need it, when they need it, and where they need it, in real-time. Companies should be embracing technologies and policies that empower their data practitioners to get the data they need, when they need it.

In addition, most companies lack even basic inventories of their data. The absence of good data classification makes it difficult, or in most cases, impossible to manage and govern data based on its risk-value profile and category. All the data ends up being treated in the same manner, with the same governance overhead and restrictions, which makes data less usable and easy to process than it can be, and of course, makes it difficult to find the right data. You simply can’t manage what you don’t understand.

Step 2: Remember that the longer you take to find the data, the less valuable it becomes

As organisations evolve to newer, modern technology stacks without retiring older stacks completely (still waiting on the mainframe to go away as predicted in the 1990s), or through acquisitions where they bring in an entirely new set of platforms, data is sprawled across heterogeneous sets of data stores – many of which are not compatible with each other and may even have multiple versions of the same database in use in different parts of the organisation. By spreading data in this way, creates challenges around data protection and governance, which is a pain point for the business. Multiple data systems storing the same information can lead to expensive data and infrastructure sprawl.

This sprawl of data store technologies means that it take businesses much longer to find the data and the sprawl further expands with the addition of cloud-native, fit-for-purpose data stores that developers are beginning to adopt as they develop new cloud-native applications, which have a different need as opposed to traditional databases. This is because spreading the data creates a lack of visibility and expertise, slow manual processes and issues surrounding compliance and regulation.

Step 3: Visualise your data - whether your dataset is large or small, being able to visualise it makes it easier to explain

With the rise of DevOps, monitoring and logging of all software components in your tech stack has become critical. Typically, monitoring tools are used to facilitate feedback between the operations and development teams during software development. If there are consistent errors for certain components, the teams are able to communicate and collaborate to resolve those issues. In response, DataOps is emerging as an approach to address these data-related challenges. It spans change across process, technology, and people to help an organisation become a data company, like Netflix and address data-related challenges.

It's important that organisations have a proactive incident response policy like this in place and use it when things go wrong — because they will go wrong. Data never lies, so organisations shouldn't base their decisions on hunches.

Data and visualisation tools, like Splunk, take threats we cannot perceive directly and make them accessible and easier to explain to our human sensory system through correlation, time mapping, and a graphical display that echoes our own visual systems. This means data must become a real-time resource, available at the fingertips of every user in a self-service format they can consume as insights. Driven by this need, we see an overwhelming demand to shift toward a way of working that enables data agility and accessibility. 

Data is the winning ingredient

If there’s one thing companies can take away from Netflix’s data philosophy, it is the need to shift towards a data-driven culture.

To drive innovation and stay ahead of the competition, today’s enterprises need to master data. Organisations must take a holistic approach to nurturing a data-driven culture by rethinking their data management and governance processes as well as their data-related technology stacks to succeed in today’s digital-first business landscape.

A foundational change in how data is accessed, managed, secured, and leveraged across the enterprise is essential in dramatically modernising your data strategy while achieving regulatory compliance with today’s new privacy laws and growing number of data breaches.

Data is the key to today’s businesses and modern-day software development. Leveraging data to drive innovation, identify new business models and add new value-added services and offerings delivers meaningful value to customers.

While augmented reality (AR) is primarily seen as a consumer technology, it is fast earning a seat at the business table through its ability to drive more efficient operations by bridging the gap between customer expectations and services.

AR adoption is growing rapidly: research from Cognizant’s Centre for the Future of Work found that nearly half (49 per cent) of senior executives believe AR will become a mature technology that is accepted, established, and in widespread use within the next 18 months to three years. Additionally, one-third of the 300 respondents said they have already fully implemented AR initiatives and are capturing value as a result.

In fact, according to Gartner, 25 per cent of organisations will have deployed AR to production by 2020. It also estimates that the technology will create 2.3 million jobs during 2020.

With emerging technologies, it is often the case that companies will look for evidence of their success in the consumer market first. While the release of the Google Glass AR headset in 2013 did not lead to widespread adoption, many would argue that it was too far ahead of its time. Apple’s rumoured move to release its first pair of AR smart glasses in early 2020, together with Adobe’s recent Aero AR app launch and the success of Sephora’s Visual Artist AR tool, are signs that the global market could finally be ready for the technology.

What would a world with AR-enhanced enterprises look like and what are the remaining barriers to getting there?

Delivering process transformation

Soon, AR could reshape the way we work thanks to its ability to meld people, places, and time into one immersive experience. Creating these experiences will drive employee engagement, productivity, and efficiency, which are the keys to success in the face of increased competition.

Where technology has digitised previously repetitive manual and paper-based work processes, AR will take the next step by rewiring business process journeys to allow information to be exchanged while on the move. It will remove “look away” activities that involve checking information and toggling between multiple documents or screens. For example, factory workers can use AR to display construction schematics, assembly or repair instructions in front of their eyes rather than having to check and recheck a static document.

Furthermore, 82 per cent of respondents surveyed by Cognizant believe that redesigning business processes is the most notable benefit of AR, empowering employees to take a more analytical approach to work and driving time efficiencies. One of the main benefits of AR is that it enables employees to work more quickly, and the rollout of 5G will drive further AR adoption. The improved network latency will reduce the slow data speeds that can lead to non-fluid AR experiences, which will be integral to creating connectivity across the business.

Concerns and barriers are not showstoppers

Given the current talent shortage in many roles involving digital expertise, companies may be concerned about their ability to acquire the necessary people to make AR a success. Eighty-five per cent of respondents identified user experience and user interface as the most necessary skill. However, demand for user experience and user interface design, especially people who are experienced in this field, is already high even though AR is really in its infancy. There is also a need for the development of natural language processing, which is expected to drive adoption as voice is an easier format than hand gesturing for many.

The value of AR within businesses is also becoming clearer. According to 62 per cent of the senior executive respondents in our survey, brand reputation is expected to be the top qualitative benefit of AR adoption. Companies understand the need for their brand to stay up-to-date with emerging consumer demographics and see AR as a way of achieving this.

When faced with the need to manage the perception that AR is a technology reserved for the consumer market, it seems as though its success in the consumer setting is driving more interest from businesses. For 65 per cent of respondents, the “fun and games” aspect of AR is serious business. They believe gaming engines such as Unity or Epic’s Unreal Engine will be the external suppliers of choice for AR capabilities. Dismissed until recently as being “just a game thing”, the massive computing power and beautiful image rendering of these engines will transpose best practices from the immersive world of gaming to catalyse mission-critical enterprise processes as fit-for-purpose in an AR-enabled world.

AR coming to an enterprise near you in 2020

AR has the potential to revolutionise the way we work. Consumer familiarity with the concept of AR on a mobile phone (think: Snapchat filters and Pokemon GO!), along with its benefits, will make its transition into the workplace much smoother. Organisations can use knowledge around acceptance in this space to understand how AR will create more personalised interactions, augmenting the business experience in 2020 and beyond. Like the advent of the smartphone over a decade ago, this moment requires all of us to think differently because, with AR, the journey becomes the process – and the process becomes the journey.

What is iSCSI?

iSCSI is a block storage protocol for storage networking. It stands for “Internet Small Computer Systems Interface” and runs the very common SCSI storage protocol across a network connection which is usually Ethernet with TCP. You can read more about iSCSI at the “What Is” section of the SNIA website. (The SCSI storage protocol is also used to access block storage as part of the SAS, SRP, and FCP protocols, which run over various physical connections.)

Originally, the SCSI protocol was used only for local storage, meaning individual disk drives or direct-attached storage (DAS). Then around 1993, Fibre Channel came along and enabled SCSI to run the Fibre Channel Protocol (FCP) on top of a Fibre Channel Storage Area Networks (FC-SAN). iSCSI was submitted as a standard in 2000 and grew in popularity as it was supported by more operating systems, first requiring dedicated iSCSI HBAs but later using a software iSCSI initiator that ran on top of any type of Ethernet NIC. 

The dedicated iSCSI HBAs gave iSCSI faster performance that was closer to Fibre Channel performance at the time, while the software iSCSI initiator made it easy to use iSCSI from many servers without buying special HBAs for each server.  Probably the biggest boost to iSCSI adoption was when Microsoft Windows Server 2008 included a software iSCSI initiator (starting in 2008, of course).

iSCSI Use in the Enterprise

In the enterprise, iSCSI has been used mostly for so-called “secondary” block storage, meaning storage for applications that are important but not mission-critical, and storage that must deliver good—but not great—performance. Generally, the most critical applications needing the fastest storage performance used FC-SAN, which ran on a physically separate storage network. FC speeds stayed ahead of iSCSI speeds until 2011, when 10GbE reached high volumes in servers and storage arrays, equaling 8GFC performance. Starting in 2016, Ethernet (and iSCSI) speeds pulled ahead as 25G and 100G Ethernet adoption far outpaced 32GFC adoption.

The fact that iSCSI runs on Ethernet and can be deployed without specialized hardware has made it very popular in clouds and cloud storage, so its usage has blossomed with the growth of cloud. Today, iSCSI is the most popular way to run the SCSI protocol over Ethernet networks. The rapid growth of faster Ethernet speeds such as 25G, 50G and 100G (replacing 1G, 10G and 40G Ethernet), along with increasing support for congestion management and traffic QoS on Ethernet switches, have greatly improved the performance, reliability, and predictability of iSCSI as a storage protocol. 

Other Storage Protocols Threaten iSCSI

However, the emergence of NVMe over FabricsÔ (NVMe-oF) now threatens to displace iSCSI for high-performance block storage access to flash storage. Simultaneously, the growing use of file and object storage poses a threat to both iSCSI (and to FC-SAN).

NVMe-oF is more efficient than iSCSI (and NVMe is more efficient than SCSI). It was designed as a leaner protocol for solid state (flash or other non-volatile memory) so it eliminates the SCSI layer from the protocol stack and delivers lower latency than iSCSI. Note that NVMe-oF can run over Ethernet TCP, Ethernet RDMA, Fibre Channel, or InfiniBand fabrics, with the RDMA options delivering the lowest latency, but all versions of NVMe-oF (including on FC or TCP) deliver faster performance than iSCSI on the same-speed connection.  So now the fastest flash arrays and fastest applications (on Linux) are moving to NVMe-oF.

iSCSI Advantage: Broad Support

Probably the biggest advantage iSCSI still holds today is that it’s widely supported by all major operating systems and hypervisors. NVMe-oF is currently only fully supported on Linux, and maybe only 1/3^rd of enterprise storage arrays today support NVMe-oF on the “front end” meaning from server to storage (and a few of those support NVMe-oF only on Fibre Channel, not yet on Ethernet). However, VMware has announced plans to support an NVMe-oF initiator and another vendor has independently developed a Windows Server NVMe-oF initiator. In addition, some specialized SmartNICs are able to take NVMe-oF storage and make it look like a local NVMe SSD, meaning it can be used by nearly any OS or hypervisor. (While only Linux fully supports an NVMe-oF initiator today, nearly every modern OS and hypervisor does support local NVMe SSDs.) 

iSCSI Advantage: Hardware acceleration options

iSCSI runs most commonly on top of Ethernet using the TCP protocol, but can also run on top of InfiniBand. Also, it can run on standard network cards or specialized Host Bus Adapters (HBAs) to take advantage of either RDMA (using iSER) or iSCSI offloads and/or a TCP offload engine (ToE). iSCSI is still supported by almost all enterprise storage arrays. iSCSI can be accelerated by using network adapters with an iSCSI hardware offload and/or TCP Offload Engine (TOE). In the former, the adapter (host bus adapter or HBA) offloads the iSCSI initiator function from the server CPU. In the latter case, the adapter offloads the TCP processing from the server kernel and CPU. Use of a TOE has fallen out of favor in some circles due to limitations that arise from handling all TCP tasks in hardware, but other forms of stateless TCP offload are still popular, can be used to improve iSCSI performance, and are supported by most enterprise Ethernet adapters.

But… NVMe-oF can also be accelerated in the network adapters, can also use RDMA, and can run over a wider variety of networks than iSCSI.

iSCSI Limitation – Block access only

iSCSI can only support block storage access, but file and object storage capacity are growing more rapidly than block storage capacity because so much of the new content today—audio, video, photos, log files, documents, AI/ML data, etc.—are more easily stored and used as files or objects instead of blocks. File and object storage enable easier sharing of data across multiple users and applications than block storage.

If use of file and object storage continues to grow faster than use of block storage, it could limit the growth rates of all block storage, including iSCSI, Fibre Channel, and NVMe-oF.

iSCSI – An Uncertain Future

On the one hand, iSCSI use is being driven by the growth of cloud deployments that need block storage on Ethernet. On the other hand, it’s being displaced by NVMe-oF in areas that need the fastest performance, and also challenged by file and object for the storage of multi-media content, big data, and AI/ML projects. Widespread use and support—and the current OS limitations of NVMe-oF—mean iSCSI will still be widely deployed for at least the next few years, but its growth prospects beyond that are very unclear. 

New Intelligent Building concepts are changing the game for construction professionals, architects, design engineers and interior installation organisations. Ethernet and Power over Ethernet (PoE) is an integral part of Building Information Modelling (BIM) and Building Management Systems (BMS) and supporting the development of working environments that are a platform for increased worker productivity, health, safety and connectivity.

Across the property value chain there is recognition that digital infrastructure must be embraced to improve sustainability while providing the types of intelligent connected buildings that people, businesses and communities require.

New standards are being developed as digital becomes a new value proposition for the building sector. Ethernet and specifically PoE infrastructure, which combines data communications and power delivery over a single Ethernet cable, is becoming the dominant technology platform.

Ethernet cable infrastructure for combined power and data communications solves smart building connectivity, power delivery, network topology and supports thermal management requirements. A new white paper from Panduit – (Power over Ethernet – Fixed Network Foundation Layer for 21^st Century Smart Buildings), illustrates how PoE will streamline processes and improve building performance, while creating fully connected and environmentally sustainable working environments.

Professionals are turning to digital infrastructure to reduce energy use and lower greenhouse gas emissions and meet energy use requirements. New generations of digitally native architects and designers are leading the efforts to attain net zero emission buildings. They recognise that technology capable of reducing installation costs and driving operational efficiency will be embraced.

BIM & BMS – Building Information Models and Building Management Systems

As BIM models advance and become interoperable this is driving evermore technology integration into building operation. Ultimately the goal is to develop interoperability between BIM, BMS, IT, IoT and manufacturing based on open standards. As this evolves, one estimate is that more than one billion sensors and connected devices will be deployed globally in buildings by 2021, alongside the billions of mobile connected devices brought into buildings by tenants, workers and visitors.

Figure 1: Building / BMS Network (From PoE Whitepaper)

This integration of devices into buildings will require cabling infrastructure which meets or exceeds the latest communications, power and thermal standards, and which does not add to network complexity and cost. The latest standards from the IEEE are PoE++ are IEEE 802.3bt TYPE 3 and IEEE 802.3bt TYPE 4. This is driving the adoption of PoE for integrated communications and power as the network standard in new builds and in the replacement networks in refurbishments. The latest standards provide PoE delivering up to 99w over twisted pair cables, enough to power the latest lighting, wireless access points and more.

Big changes in how buildings and occupants interact are being enabled by PoE cable infrastructure. The Royal Institution of Chartered Surveyors says “By combining BIM with the Internet of Things we can start to gain a living picture of our buildings. For the first time in history, the planning of the architects and designers can be verified and compared with the use of the building, with tracking over time as the use of the space and its occupiers’ changes. Bringing together all this data, we can gain new and better understanding of how our buildings actually work.”  NB1

Ethernet represents the core infrastructure standard for combined communications and power which will provide plug and play connectivity for easy deployment of app-based sensors and devices which will make up the digital building.

Power and Data Network Infrastructure for the Long Term

The pace of change in consumer technology and endpoint IT continues to accelerate. So, it is vital to choose a standards-based technology with a clear roadmap. Ethernet is the local area network communications de facto standard for data. PoE runs over the same copper cable as the LAN, providing decades of stable, high performance network infrastructure.

Buildings are becoming digital with an infrastructure that supports all of the various applications to optimise operations. Building Management Systems are becoming more advanced, with applications which run and manage HVAC, water, lighting and security are constantly developing, becoming more responsive and smarter. This expansion of capabilities meant the control of these applications being transferred onto the data infrastructure plane. Now, PoE is extending to powering and communicating with an ever-growing variety of physical devices

Figure 2: What is Driving Digital Buildings – From PoE Whitepaper

In a security context, public and private multiple and single use buildings require evermore security and access control. Schools, hospitals, government and other public buildings must balance the needs for accessibility and security by ensuring a building’s physical security at access points and through the expansion of video monitoring. Another change is that the future direction of buildings in urban environments is upwards. That means major changes to modern buildings as multi-use and shared environments become ever more common.

Low voltage cameras, embedded sensors, kiosks, wireless access points, physical access points, digital signage and displays are being deployed in ever greater numbers. Market forecasts show an explosion in the number of devices about to enter buildings. Wireless access point numbers alone are forecast to expand by 30% per year until 2027. Kiosks and digital screens will become ubiquitous in multi-use environments. According to a report on the Global Kiosk Market, published by KBV research, the global kiosk market will reach $5.4 billion by 2024, at a growth rate of 26.4% CAGR.

High performance cable infrastructure is the base layer for these smart technologies. All these different devices need to run over a single network which provides power and data. With lower installation costs, fewer hazards and more flexibility, PoE is a proven, viable, cost-effective solution.

A single network has positive implications for ease of installation, lower maintenance and better performance and interoperability between different building elements. PoE is a simple means to power digital building infrastructure devices over the same network. Factors affecting cable infrastructure cost and operations include locations, runs, distances, connections and cable fill and these key factors effect performance and OpEx management in digital buildings.

Figure 3 Distributed Building Services – Millions / Outlets in Commercial Buildings by Type of Products – 2015-2021

New topologies for network infrastructure will provide direct connections from Telecom Rooms (TR) to the device allowing the switch to directly control the power and data communication to the device. Common challenges within the TR are crowded cable pathways and bulk is an issue as cable runs and access is becoming a serious concern as the number of connections increases cable and port densities. Solutions such as smaller cable diameters, angled connectors, and high-density patching help address these issues. These innovative solutions release space that would otherwise be used for cable management, to make room for active gear or switches.

Panduit’s Category 6A cable with MaTriX technology features an integrated tape that gives the cable advanced thermal properties for handling the heat rise within cable, which is caused by PoE. A digital building requires PoE cables in new physical environments; in ceiling voids and under floor spaces. To operate effectively at scale cable infrastructure flexibility becomes ever more important.

Conclusion

In the built environment, too many networks remain siloed and separate. This approach is no longer suitable for the new era of intelligent buildings. The new generation of architects and engineers have the responsibility for delivery of the next generation of smart digital buildings. Understanding the power and benefits of future proof PoE cable infrastructure is at the core of physical, economic and digital innovation.

Notes

NB1: https://www.rics.org/globalassets/rics-website/media/knowledge/research/insights/big-data-smartcities-intelligent-buildings-surveying-in-a-digitalworld-rics.pdf

“2020 will see machine learning and artificial intelligence used to create distributed and targeted malware and attacks. An attacker using machine learning algorithms can create a suite of botnets or worm-style malware that gathers data from multiple attempts to breach commercial sites, ultimately generating more sophisticated attacks that could be targeted at Critical National Infrastructure or Governments. 

“Using data from breaches, vulnerabilities, successful and failed attacks - the ‘next generation’ of malware can be created. It will make fewer obvious attacks but be more successful by using tactics proven to work. This would make pattern matching or DOS/brute-force security measures less and less effective. 

“Protecting against this style of attack requires analysis of network patterns, command and control, and a large-scale dataset of attacks to see these attempts happening across multiple sites and networks, rather than a single instance or victim.”

“In 2019 we’ve seen a number of digital transformation projects not fully meeting expectations. Consequently, in 2020 I expect to see a number of small but significant step changes in the way businesses approach digitalisation projects, particularly with regards to security. Focus will be on improving user experience and generating value from smaller more tangible projects. For cyber security, this will mean solutions that make day-to-day operations easier and that are proven to mitigate the impact of security incidents. As a result of this, in 2020, security teams will need to be looking to communicate the value they bring in terms of the bottom line.”

Today, all the most popular consumer and enterprise applications are hosted in data centers. From Google and Facebook to YouTube and Instagram, this cloud-centric methodology has become essential for enabling our connected lifestyles. Underpinning this is a hierarchical client-server architecture that sees most servers located in data centers scattered around the globe. For years, this has been the optimum way of hosting applications that provide access to content and information to client devices (e.g.: smartphones or tablets.) However, new trends point to this quickly becoming a less efficient way of managing data.

Changing landscape

Firstly, there has been an explosion of computing devices and embedded computing in all things. This has grown the ‘edge’, often referred to as the Internet of Things, where devices are connected to centralized servers in data centers through gateways and hubs. However, with edge devices having more computational power than servers of just a decade ago, the edge is becoming progressively more powerful.

Secondly, the advent of social media on mobile devices, orders-of-magnitude more personal multimedia content are generated on these edge devices. People are creating and sharing thousands of times more content than what major studios and broadcasters are hosting on central servers in the cloud. Today, most of the data generated on (edge) devices is sent back to servers on the central cloud for processing and to facilitate sharing.

The third trend is the decomposition of solutions. The emergence of APIs and microservices and their automated deployment are contributing to a serverless backend environment. Instead, the cloud is used to scale resources to fit demand either through volume or geography.

A new way

The current fixed and hierarchical client-server approach makes central cloud resources and network connectivity the bottleneck for future growth. Sending data from hundreds of billions of client devices to tens of millions of centralized cloud servers wastes bandwidth and energy and it has serious social and economic implications.

Furthermore, developers are reliant on cloud service providers who have access to the apps and the data stored or processed in their servers. Essentially, a handful of large companies have to manage the majority of consumer and enterprise data. And despite all the sophisticated security measures, storing data and hosting applications on third-party resources exposes the owners of the information to risks.

This challenge of exponential growth of computing at the edge, has opened up a massive opportunity. Enabling any computing device to act as a cloud server when it makes sense to do so can create a hybrid edge cloud that scales organically with new capable devices. In this way, central cloud resources that require significant real-estate and power, and are bandwidth hungry can offload much of their burden onto edge devices. Many microservices can be hosted on edge devices instead of being hosted in a centralized server, making them faster and more flexible to changing user requirements. 

Edge power

Acting as servers when feasible, edge devices can perform many of the functions of the servers in central cloud. This creates a hybrid edge cloud that is significantly more powerful than the centralized cloud.

For example, there are currently over 80 million Sony PlayStation 4 (PS4) consoles in peoples’ homes. This represents more than 600 million processor cores and 40,000 petabytes of storage. In comparison, this is much larger computing, storage, and memory resources in the aggregate than the entire Amazon Web Services (AWS) infrastructure.

And the PS4 is only one type of device. There are billions of smartphones, PCs, set-top-boxes, game consoles, streaming players, routers, tablets, and other computing devices that can potentially act as cloud servers.

The benefits of such a hybrid edge cloud architecture are phenomenal. From reduced cloud hosting costs and communication bandwidth and latency to improved network efficiency, reduced energy consumption and carbon emission. Moreover, this new approach leads to increased data privacy and providing consumers and enterprises with better control over their data.

Software-driven

Cynics might argue that a change as fundamental as this will require significant investment in overhauling network infrastructure. Yet, if a software-driven model is adopted, no change will be needed to the low-level design of edge devices.

All that is required is a downloadable software development kit (SDK) that runs on top of existing operating systems. No changes to hardware or operating systems are necessary. Instead, developers have the power to decentralize the existing cloud infrastructure.

Ultimately, the hybrid edge cloud environment will provide consumers and enterprises with more control over their personal data, minimize the cost of hosting and delivery of applications and services, and improve network performance.

Decentralization is the next revolution in cloud computing and an essential element to drive the Fourth Industrial Revolution.

Advancements in IoT and edge-computing technologies will fuel demand for low power networks, micro-datacentre and micro-cloud environments. To be prepared for these emergent trends and to accommodate new technologies, telecoms and datacentre providers must consider adopting versatile network architectures and product offerings.

IoT and Smart Cities are becoming mainstream as more public and private sector organisations are becoming comfortable with the technology and are beginning to benefit from real-time data and decision-making capabilities.

Early iterations of IoT devices were primitive; with basic functionality and limited processing power – capable of simple measurements and wireless communication, but with limited analysis or processing capabilities. Recent developments in embedded systems technology have greatly improved the performance, power characteristics and capabilities of these devices.

Modern IoT chipsets now feature ultra-low power components, artificial intelligence, encryption, visual imaging and advanced-wireless systems. These enhancements have given rise to the concept of ‘edge computing’, where more advanced forms of analysis and processing are performed on the device itself.

With the processing activity now happening at the network edge, this has reduced the need for high bandwidth links and continual connectivity back to a central datacentre environment.

Edge computing devices will benefit from low-power wireless network access (such as LoRa), as opposed to the relatively power-hungry, high power networks such as 5G.

Given the low power demands of IoT and edge devices, many telecoms operators are looking at a strategy of co-existence; deploying high-bandwidth, dense deployments of 5G sites; alongside long-range, ultra-lower power wireless technologies such as LoRa, NB-IoT and Sigfox. In the case of IoT – often less is more. The Isle of Man is a great example of how pervasive wireless networks can create opportunities in the economy. The Island was one of the first in the world to deploy 3G and it has near-total coverage for 4G.

The datacentre and IT industry have undergone a technological pendulum swing, with a recent shift towards cloud and centralisation, almost emulating the era of the mainframe. As computational power shifts to the network edge, we are seeing datacentre, storage and compute providers follow-suit.

Recognising the shift towards edge computing, many datacentres, cloud and hardware vendors have introduced micro-datacentre and micro-cloud solutions. Like their IoT counterparts, these micro-datacentre environments are also being deployed at the network edge; in containers, rooftops and public spaces.

The combination of edge-compute, low power WANs and micro-datacentres has allowed firms to deploy emerging services close to end-users. Gartner identified this trend in 2018, where they recognised that workload placement is now based on business need, not constrained by physical location.

 “By 2025, 80% of enterprises will have shut down their traditional data centre, versus 10% today.” [i]

The benefits of edge-compute are not just technical. As data can be collected, processed and formatted at the network edge, this can eliminate the need for personal data transmission and in the case of cloud – eliminate cross-border data transmission and storage, an important consideration in the age of privacy and GDPR.

While the ostensible benefits of hybrid cloud solutions are undeniably positive from the perspective of business value, we’ve seen a number of organisations who have had their IT modernisation strategies curtailed by issues of migration. For example, running mission-critical applications and infrastructure across multiple cloud environments runs the risk of creating hidden interdependencies between disparate systems. As a result, IT can become more difficult to control or fix in an instance of a failure, adding chaos and confusion to what can already be costly disruption.

But in the era of digital transformation, organisations cannot afford to be hesitant. Knowing how and when things can go wrong is the first step to mapping out a resilient hybrid cloud migration strategy. This starts with three simple questions: firstly, how can workflow streams be uninterruptable across two environments? Secondly, which applications should be hosted in a public cloud and which should stay on-premise? And finally, how can hybrid workloads ensure continued compliance, especially in the age of GDPR?

Multiple clouds, one uninterruptible business structure

At times, an organisation will need to migrate data from on-premise hardware to the cloud or vice versa. This requires a new IT governance model to be created, with policies and procedures attuned to where applications and data reside. An efficient migration strategy reduces the risk of data being lost during the process and the potential for other people to access information that they shouldn’t be able to see. A consistent toolset across hybrid IT deployments is needed to grant the ability to provision, view, access and manage public and private cloud resources with a single set of credentials.

The flexibility of a hybrid cloud service model also extends to options for provider or customer management of the on-premise private cloud environment. The most sophisticated cloud providers offer management solutions that span both cloud environments. A self-service portal enables the customer to manage their on-premise private cloud environment to reduce costs and to post service requests to the public cloud. In-house IT can also collaborate with operational support from public cloud service providers, taking full control of architecture, deployment, monitoring and change control in hybrid cloud solutions. They also resolve incidents to keep critical applications and workloads up and running.

Choosing which applications to run in private and / or public cloud environments

It’s often thought that applications and data that, if rendered inoperable or stolen, could affect the organisation’s ability to function are best suited to the private cloud. These so-called ‘mission-critical’ applications vary from industry to industry but are generally responsible for supporting the basic transactional activity between an organisation and any number of components in its network (i.e. customers and/or end users, products and services, network endpoints, etc.). On the other hand, that’s not to say that cloud providers should be discounted entirely for hosting mission critical applications. Cloud and managed service providers may layer their solutions with specific components that protect the stability of the applications they host, such as co-located data centres or managed security services.

When deciding which applications to move to the public cloud, an organisation should start with the less mission-critical ones (such as infrastructure services, messaging, web applications for collaboration, and database applications). These are good candidates for public clouds because they are less likely to cause widespread disruption to a business if they are knocked offline and can be cost-effectively maintained at the cloud provider’s data centre.

Fully understand and address the hurdle of regulatory compliance

In terms of business priorities, organisations endeavour to be more flexible, more available and more omnipresent in order to remain competitive. While hybrid and public cloud solutions are the natural choice for businesses seeking these benefits, a distributed model of data storage presents a challenge to one of the key facets of GDPR compliance: knowing exactly where data is. As a result, businesses looking to migrate data from on-prem data centres to the public or hybrid cloud must have the diligence to ensure visibility is not sacrificed in the process.

The need for visibility in distributed cloud systems is driving demand for so-called ‘sovereign’ cloud solutions, which provide the fundamental benefit of ensuring all data is stored on servers located on UK soil. Currently popular within the public sector due to enhanced security qualities, the GDPR is now also driving uptake of managed sovereign cloud solutions in the private sector, along with other factors such as cybersecurity and the uncertainty around data transfers around Brexit. These solutions will help close the widening gap between operational flexibility and regulatory compliance, and give businesses peace of mind when migrating to the cloud. 

Taking a resilient approach to migration

Fundamentally, there’s main question organisations need to answer: how do we stay resilient through periods of change? When it comes to hybrid cloud, only when the threats to Business Continuity have been addressed can migration processes begin and concerns surrounding performance, flexibility, and control be put to bed. Cloud computing is not a one-size-fits-all solution, and the implications of simply following suit and choosing the wrong solution can backfire, with potential to cause real damage to the bottom line for companies. Only through a thorough examination of the options and insight from qualified experts will organisations successfully embark upon the right cloud journeys for operations today, and beyond. 

Key digital propellers such as the Internet (as a ubiquitous reachability platform), applications and open source proficiency (as a skill set platform), cloud (as a pervasive computing and data platform), and, of late, AI/ML (as an insight discovery platform) help enterprise businesses to improve business productivity and customer experiences.

While the pace of digital transformation varies based on the business and the sector it is in, overall, the journey of digital transformation has three stages.

• Task Automation. In this stage, digitalization leads businesses to turn human-oriented business tasks to various forms of "automation," which means more applications are introduced or created as part of the business flow. This began with automating well-defined, individual tasks to improve efficiencies. A common example is IVR systems that answer common questions about a product or service but may need to hand off to a human representative. Individual tasks are automated, but not consistently integrated. 

• Digital Expansion. As businesses start taking advantage of cloud-native infrastructures and driving automation through their own software development, it leads to a new generation of applications to support the scaling and further expansion of their digital model. The driver behind this phase is business leaders who become involved in application decisions designed to differentiate or provide unique customer engagement. For example, healthcare providers are increasingly integrating patient records and billing with admission, discharge, and scheduling systems. Automated appointment reminders can then eliminate manual processes. Focusing on end-to-end business process improvement are common themes in this phase.   

• AI-Assisted Business Augmentation. As businesses further advance on their digital journey and leverage more advanced capabilities in application platforms, business telemetry and data analytics, and ML/AI technologies, businesses will become AI-assisted. This phase opens new areas of business productivity gains that were previously unavailable. For example, a retailer found that 10% to 20% of its failed login attempts were legitimate users struggling with the validation process. Denying access by default represented a potentially significant revenue loss. Behavioral analysis can be used to distinguish legitimate users from bots attempting to gain access. Technology and analytics have enabled AI-assisted identification of those users to let them in, boosting revenue and improving customer retention.    

The steady rise in leveraging application, business telemetry and data analytics enables organizations to scale digitally. Adopting an agile development methodology to quickly iterate modifications has shortened the lifecycle of “code to users.” In digital enterprises, the “code” embodies the business flow and the speed of change in “code to users” represents business agility. In this new era of digital economy, applications have become the life blood of the global economy. Every business is becoming an application business and every industry is becoming application-centric industry. 

As IT infrastructure automation and application-driven DevOps processes have been largely established across the industry, we envision that a layer of distributed application services that unifies application infrastructure, telemetry, and analytics services is emerging. The scale, agility, and complexity of digital enterprises demands their applications to have self-awareness and the ability to automatically adjust to operating and business conditions. This will breed a new generation of application services to collect, analyze, and act on the telemetry generated by apps and their infrastructure. These capabilities create new business uses. End-to-end instrumentation from code to customer will enable application services to emit that telemetry and act on insights produced through AI-driven analytics. These distributed application services will help application owners to improve application performance, security, operability, and adaptability without significant development effort. 

2020 tech forecast: what will cause blue skies versus perfect storms?   

2020 is just around the corner, and businesses everywhere are beginning to plan for the year ahead. There are many trends expected to grow next year, including contact centre technology, cloud, convergence and the Internet of Things (IoT) becoming a lot more widespread. But with this popularisation must come education. 

With this in mind, four experts have come together to give their advice and predictions on what trends will become more mainstream in 2020 and the years beyond.  

Steve Blow, Tech Evangelist at Zerto, thinks the biggest trend in 2020 will be the continuance of digital transformation:

“If you think of how much digital transformation has changed everyday life so far - such as being able to pay for your car tax online, rather than the post office - there’s no denying that it will continue to make a positive and valuable impact throughout 2020. However, there’s definitely a long way to go, and more that organisations could be doing to reap the benefits of digitising business operations. Yes, there is some fatigue around companies 'beginning their digital transformation journey’, but 2020 will be more than just moving to the cloud. Digital transformation is about how you deliver and provide services, and this is what will continue to drive organisations next year.”

One main driver, Steve believes, will be the ongoing adoption of cloud:

“In 2020 we will continue to see the adoption of cloud,” says. “As the old tech saying goes, “one cloud doesn’t fit all’, so I fully expect that businesses will continue to want more mobility and choice when it comes to their cloud. Microsoft and AWS will continue to go strong as more and more organisations will look to pursue their ‘cloud-first’ strategies, adopting the cloud and its services. Because of this, having the ability to move to a cloud, from a cloud, and back again will become more and more valuable.”

In order to do this, Steve thinks convergence will be the key:

“Next year will be the year of convergence. At the end of the day, people want less tools to do more things, reducing the overhead. IT teams don’t want to manage infrastructure anymore, they want to offload everything and are utilising the cloud to deliver that. On the flip side, though, they will want those applications they are still having to manage to be moving from a multi-point solution to a single-point solution that delivers multiple outcomes.”

He also has a word of warning around security concerns, however:

“It goes without saying that cyber threats, especially ransomware attacks, will continue to grow - especially as criminals are making considerable money from them,” says Steve Blow, Tech Evangelist at Zerto. “I predict we will see an increase in attacks that are more targeted than they are random. This will cost organisations money, not just from the ransom side of things, but from a data loss perspective. Data loss is money loss, and the only way businesses can prevent data loss is to make sure that they are constantly protecting it.”

“According to Statista, the global IoT market will explode from $2.9 trillion in 2014 to $8.9 trillion in 2020,” points out Alan Conboy, Office of the CTO at Scale Computing. “That means companies will be collecting data and insights from nearly everything we touch from the moment we wake up and likely even while we sleep. As evidence of this, technologists have seen that the rise of edge computing and IoT was accelerated by the birth of the iPhone. 

“Seeing what Apple has achieved, we are going to see a much broader perspective on this ability to put reasonable amounts of compute into a tiny form factor and move that into dedicated functions. In 2020, as a result, we can expect to see evolutionary expansion in the IoT space, not revolutionary. It will continue to evolve, driven by a need for more efficient, more compelling, cost effective solutions, with edge computing at the forefront.

“We are living in a world that is increasingly data-driven, and that data is being generated outside of the four walls of the traditional data center. With 2020 approaching, organisations are taking a much deeper look at their company’s cloud usage. Cloud was originally positioned as the answer to all problems, but now the question is at what cost? 

“More organisations are turning to hybrid cloud and edge computing strategies, turning to solutions that process data at the source of its creation. In 2020, organisations will rely on hybrid environments, with edge computing collecting, processing and reducing vast quantities of data, which is then later uploaded to a centralised data center or the cloud.”

2019 brought major reform for first responder technology due to growing public safety networks, the need for interoperability and the state of both man-made and natural disasters - plus the proliferation of 5G connectivity in the market. Estee Woods, Director, Public Sector & Public Safety Marketing at Cradlepoint, says “All of these factors combined have created a qualifying moment as we enter 2020.

“Public safety networks are considered mission-critical in enhancing interoperability, communications and successful team collaboration, since first responders are constantly on the move. Cellular has created an era of mobile broadband networks, leading to a proliferation of mobile offices and pervasive connectivity that have enabled a new standard in communication for emergency personnel.

“This draws a parallel to 2007 and 2008 when the smartphone was launched. The years following saw an explosion of new technology that was rapidly consumed and changed the way we live and work. It also changed the way we, as humans, interact with each other and see our world view.

“We believe that 2020 and 2021 will see a similar, accelerated impact on the public safety market. It will likely result in the largest rate of change in the industry since the smartphone boom. Some standout technologies will include:

- Unmanned aerial systems (UAS) will come into their own, for the safe and fast delivery of defibrillators and emergency medications. Legislation will need to be at the forefront to really eliminate agency risk and enable this untapped potential to be mapped out.

- BOT operations will help automate public safety responses. Integrations between human operations and computer operations form artificial intelligence. Automated workflows, called ‘BOTS’ can help public safety by serving as the virtual eyes and ears on the street. BOTS can be activated by spoken words and create alerts and workflows via the cloud. This topic will gain momentum in workplace automation in 2020.

- 5G, AI, LMR + LTE and UAS will be the biggest mover and shakers in public safety. Smart states will replace smart cities, and anything that can be connected will be connected. If there is no cellular/broadband connectivity, Private LTE networks will fill that coverage gap. Cloud and edge computing, along with 5G will enable AI technology and machine learning.

- MR systems – 20 years ago, most first responders relied on CAD and LMR ‘technologies.’ But that’s changing. New tech like LMR, LTE and PTT will need interoperability, which continues to be the biggest roadblock with the highest amount of risk if it can’t be overcome. Data interoperability needs to be mapped out, including LMR, P25, PTT, OTT, access control, 911 and data sharing, so these points can all intermingle. Integrating cellular networks into your overall mission-critical comms plan will be essential in making this possible.”

All in all, 2019 has been a great year in terms of developing technology. 2020, however, is set to kick up a much more of a storm, so it’s best businesses prepare. 

At the moment, we don’t see enough real results or use cases emerging, even though everyone agrees that there is huge potential. I polled some of our experts to find out why this might be happening and identified five critical barriers that need to be overcome for AI to move into the mainstream.

1: You need a lot of data to build models

AI-based models probably need even more data than most because they need to learn for themselves. The explosion in the volume of data available from the Internet of Things, and particularly the increase in streaming data, should have made AI models far more ubiquitous. However, far too many organisations have not really caught up with this.

Joao Oliveira: "Streaming data is still an untapped resource for many, meaning that they are missing out on the power of analytics.”

Arturo Salazar: “Many have failed to appreciate that they may need to go hunting for new sources of data."

Ivor Moan: "Data preparation is crucial for getting value from data. Skimp on the data preparation, and you will find that you cannot rely on your analytical results.”

In other words, organisations that do not pay enough attention to data, and especially data quality, will fail to capitalise on AI.

2: Many models fail to move into production

Developing a model is relatively straightforward. The process often involves a number of different individuals and departments. Indeed, development and deployment are so different that they almost look like two separate life cycles, a bit like a salmon’s move from river to sea (and back again), according to James Ochai Brown.

Different skills are required, both project management-related and technological.

3: Users need to be able to understand insights from models

The best model in the world is only useful if it leads to action. That means that users have to be able to understand and interpret the outputs from the model to provide useful insights. Data visualisation is a crucial part of this process.

Data scientists, therefore, need to think about how they will demonstrate the outputs from their models to maximise the impact on viewers, for example, by asking themselves about the audience, and the message they wish to convey.

4: The real benefit of AI is business model transformation – but that is a long-term project

According to Christer Bodell, any organisation can introduce a single AI-based project or model, and it will improve current business practices. Getting real benefits from digitalisation requires something more: a genuine change in philosophy and a commitment to innovation that is likely to result in business model transformation.

This requires a longer-term change in thinking, says Andreas Godde, and particularly a focus on how value is generated for customers.

5: You need more users to increase use of AI – but they need to see others using it first

There is a book by Geoffrey Moore called Crossing the Chasm. It describes the difficulty of moving from "early adopters," those who adopt a product because it is new and interesting, to the "early majority," who will use products 

because they are useful. The early majority need to see products being used by people like them, to solve real-world problems. AI faces a similar challenge – that at present, people do not see enough real-world examples of AI being used to solve problems.

Generate some of those, and particularly examples that show how AI can improve customer experience, and both companies and customers will be more prepared to accept AI and move across the chasm.

An efficient supply chain can benefit businesses in a number of ways, such as enabling a longer-term view of business costs or increased productivity. Therefore, enhancing the efficiency of digital processes within the supply chain can result in greater profits. However, the focus may soon shift to accuracy when supply chain companies fully realise the benefits that this factor can hold. Accuracy is a hugely valuable business metric that mustn’t be overlooked, as its importance only increases within the digital supply chain.

Increasing inventory visibility

Nobody can predict the future, and this rings true for predicting the demand for goods. Inventory management and the costs associated with it can prove a huge burden for all supply chains, and especially for those of retailers. However, by championing accuracy within inventory management, businesses can work towards maintaining balance and preserving the bottom line.

Of course, balancing inventory levels in just the right manner, not too high and not too low, is easier said than done. When inventory levels exceed justifiable consumer interest, businesses risk incurring excessive carrying costs through storage or perished and unsaleable goods, such as in the case of a grocery supply chain. However, having too few goods to hand is just as problematic. A stockout can lead to lost revenue and disgruntled customers, whose orders have not been satisfied in a timely manner. Even the most loyal buyers can be forced to rethink their commitment to a retailer if they are subject to issues stemming from poor inventory management.

Accurately managing the flow of inventory is core to avoiding such issues and maintaining a good relationship with customers. This can be achieved by capitalising on IT solutions that assist in the seamless convergence of supply chain systems. Order management systems (OMS) and more futuristic digital technologies, such as blockchain, can be used to minimise the siloes that cause friction within the supply chain. Unifying the end-to-end processes of a supply chain will not only allow goods to be more accurately tracked, traced, and monitored, but will also facilitate the sharing of data between partners. Seamless data sharing is crucial for allowing the clear visibility of goods up and down the chain, which is necessary for accurately predicting demand.

Aiming for perfect order accuracy

Performance metrics, such as Perfect Order Rates, which describe the number of orders that have been completed seamlessly, are hugely swayed by accuracy and a valuable form of measurement for businesses. By striving towards accuracy in order to achieve a higher Perfect Order Rate, businesses will be able to fully assess the productivity of the systems they have in place, providing them with cost control, increased customer satisfaction and greater efficiency.

Particularly successful in increasing transparency and accuracy are Order Management Systems and Enterprise Resource Planning (ERP). When connected with the work of supply chain employees, these systems can greatly reduce inaccuracies and improve the quality of employees’ work by minimising the likelihood of errors. In the simplest form, digitising data entry with barcode scanners and enhancing warehouse picking with voice-enabled technology is far more accurate than using a manual, paper-based system. When combined with RFID tags, continually scanned throughout the supply chain, the risks of missed orders or incorrect delivery locations will be greatly reduced.

Investing in the future

While investing in supply chain convergence and digital transformation can seem costly upfront, the associated benefits are unquestionable. Cost savings will be granted in the long-run and immediate accuracies will be experienced through the use of new technologies and mobile solutions within the supply chain. By standardising and converging key supply chain processes, such as transportation and warehousing, costs will be driven down by the resulting increased accuracy. Mistakes come at the detriment of time and money and investing in improving accuracy and mitigating potential issues is a great way to drive down costs, better satisfy customers and enhance productivity throughout the chain.

Increased visibility is just one benefit of this investment, allowing businesses to deliver an entirely demand-driven supply network by harnessing real-time and accurate data from all partners in the supply chain is also key. As soon as businesses update their mobile device fleet using technology that enables real-time collaboration and data-sharing between all aspects of the supply chain, they will experience a positive impact on the bottom line. Attaining this sort of flexibility and communication by integrating supply chain processes is the future of the digital supply chain and the most efficient way for businesses to gain an edge over their competition.

Modernising and digitising supply chain processes is a real possibility for businesses thanks to recent technological advancements. Now, each stage of the process can be recorded and tracked, with any errors being flagged immediately and rectified. Fully utilising this level of accuracy is necessary to not only effectively manage consumer demand, but to drive down costs and improve decision-making. 

Other trade-offs must be considered too, of course. Deployment in a new green-field site, designed to incorporate liquid cooling from the start, will be far lest costly in terms of capital expenditure (CapEx) than retrofitting an existing air-cooled facility.

However, servicing liquid-cooled systems presents certified data centre service partners or Managed Service Providers (MSP’s) with a new set of challenges. Handling procedures will be far more intricate as great care must be taken not to contaminate IT equipment with water, if that is the selected coolant, or to lose more expensive dielectric than is absolutely necessary through careless handling.

IT equipment immersed in fluid is inherently better protected from contamination, vibration and noise than air-cooled equipment, therefore overall system reliability is likely to be increased, especially in harsh environments. This also applies to unmanned edge computing facilities deployed in densely populated or urabanised environments as the requirement for data, digital services and technology increases.

In smart-cities, applications including real-time public transport information, public service announcement kiosks and in-time, autonomous driving systems, will require a preponderance of resilient, ultra-low latency and unobtrusive IT deployments, that must continue to work reliably without being seen or heard. For these environments, liquid cooling systems present a near perfect solution.

Although servicing liquid cooling systems can be expensive, it is well to remember that their inherent reliability due to immersion will result in longer times between service calls and fewer overall unplanned maintenance events.

As the sheer number of applications in edge computing environments increase, liquid cooling it seems, is a highly valuable, efficient and cost-effective way of meeting the demand for today’s digital services.  

Submer at Reetam Solution HQ

During the same month, Submer and Evocative had their first Open House and Immersion Cooling Demo event at Evocative Data Center, San José, California. Submer and Evocative (a leading provider of Internet infrastructure, colocation, hosting and managed services) partnership “is just the first step towards promoting the next generation of efficient and high-performance data centers, a mission Evocative is very proud to be a part of”, as Evocative’s CEO, Arman Khalili said.

Submer’s SmartPodX will be at Evocative Data Center for the next several months. “The SmartPodX is such a monumental leap in cooling efficiency, you have to see it to believe it. That’s why we are partnering with industry visionaries like Evocative to host educational demonstrations across the globe,” stated Jeff Brown, Submer’s Managing Director in North America.

Submer and Evocative Team

The Open House and Immersion Cooling Demo was also the occasion for Submer to present our new CTO: Scott Noteboom. The newly appointed CTO of Submer and former Head of Infrastructure Strategy at Apple and Yahoo, will bring his experience to help drive strategic innovation across Submer's line of immersion cooling systems and autonomous infrastructure platform.

"As soon as I met Scott, I knew he was the perfect fit,'' stated Daniel Pope, CEO of Submer. "Bringing more compute power in smaller footprints with dramatically reduced power consumption is more than good business strategy. It’s a practical, economic, and environmental imperative. Scott gets it, no one understands the challenges and possibilities better, and there's no one better to help us drive that innovation forward."

Scott was also at SC19 where, along with Diarmuid Daltún, he led Submer’s November Webinar, live directly from our booth.

At SC19, we launched the SubmerStrings, an exclusive, interactive initiative to help our audience check their knowledge around Immersion Cooling and related topics (such as what the PUE is, what the most important benefits of Immersion Cooling are, etc.) The SubmerStrings gave us some interesting results that confirmed:

1.     How Immersion Cooling is, literally, a technology on the rise. The demands of modern infrastructure have begun to surpass the capabilities of the traditional air-cooled rack and liquid cooling technologies appear to be the only possible way to:

a.     Guarantee high computational density.

b.     Dissipate greater quantities of heat per rack compared to air-cooling.

c.     Save on electricity and improve efficiency.

2.     The importance of education to debunk many myths around Immersion Cooling and prepare the ground for the HPC and datacenter industry to adopt a disruptive technology such as Immersion Cooling.