Cisco has unveiled a new computing platform designed specifically for AI workloads on the edge.

Announced at the company’s annual partner summit, Cisco Unified Edge will combine computing, networking, and storage capabilities in a single platform to provide “real-time AI inference” and support for agentic AI workloads.

Cisco said the new platform is aimed primarily for organizations operating in data-intensive sectors, such as healthcare, manufacturing, and retail.

The networking giant noted it has “partnered closely” with customers across the aforementioned industries to design the platform.

"Today’s infrastructure can’t meet the demands of powering AI at scale,” said Cisco president and CPO, Jeetu Patel.

“As AI agents and experiences proliferate, they will naturally emerge closer to where customers interact and decisions are made – the branch office, retail store, factory floor, stadium, and more.

“That’s where compute needs to live. With our Unified Edge we’re making it easier to power AI in the real world with flexible, secure systems that are simple to deploy, operate, and scale as demand grows.”

So what can customers expect from the new edge AI platform?

Under the hood of Cisco Unified Edge

Cisco Unified Edge is designed primarily for enterprises looking to run AI workloads and inferencing in a localized setting, removing the need for costly cloud-based infrastructure.

The platform can be scaled based on changing storage needs, which Cisco said will remove the need for “rip-and-replace upgrades”.

“The modular chassis offers CPU and GPU configurations, redundant power and cooling, high-performance SD-WAN networks, and pre-validated designs to support today’s applications and those yet to be imagined,” the company said in a statement.

Notably, Cisco aims to simplify integration of the platform, describing it as a “zero-touch deployment” system that can be easily managed through Cisco Intersight. This means considerations such as scaling and upgrades can be carried out without the need for “on-site specialist skills”.

ThousandEyes and Splunk integrations will also be available for Cisco Unified Edge, the company added, as well as built-in security features.

“Security is built-in at the device level and can extend to applying zero trust to every access, segmentation, and protection applications and AI models,” Cisco explained.

“This approach addresses the expanded attack surface at the edge, helping secure AI operations from physical and cyber threats.”

AI at the edge gains momentum

The announcement from Cisco marks the latest in a string of moves from big tech providers to bring AI closer to the edge, meaning data is processed closer to the source as opposed to relying on cloud infrastructure services.

There are a number of key advantages for businesses in this regard, according to Forrester, particularly with regard to latency and processing speed.

“Moving AI processing to edge devices enables rapid insights that traditional cloud-based setups can’t match,” Forrester VP and principal analyst Michele Goetz noted in a 2024 blog post.

“For sectors like healthcare and manufacturing, architects should prioritize proximity to offset latency. Low-latency, highly distributed architectures allow endpoints (e.g., internet-of-things sensors or local data centers) to make critical decisions autonomously.”

As ITPro noted in February 2025, hosting AI workloads at the edge also offers distinct advantages in terms of security.

In hosting data on localized devices, this essentially allows enterprises to keep a closer eye on storage and reduce exposure to unauthorized access.

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Eight European tech organizations have teamed up to launch a sovereign edge cloud platform aimed at providing portability and interoperability across multiple cloud providers.

Virt8ra, coordinated by OpenNebula Systems, includes backing from Arsys, BIT, Gdańsk University of Technology, Infobip, IONOS, Kontron, Mondragon, and Oktawave, and will provide computing and storage resources in a host of countries across the region.

This includes services in Croatia, the Netherlands, Poland, Germany, Slovenia, and Spain.

"Through this collaboration, we are contributing to strengthening Europe’s digital sovereignty and driving innovation across the continent," said Jože Orehar, head of the cloud platform department at Kontron.

"This distributed environment will enable further research and development on a cloud continuum made of heterogeneous, country-oriented clouds."

The move forms part of the Important Project of Common European Interest on Next Generation Cloud Infrastructure and Services (IPCEI-CIS), approved by the European Commission in December 2023 and supported by 12 EU member states.

The initiative aims to bolster research and investment in edge and cloud computing technologies across the union, and create a decentralized edge computing framework.

As part of the virt8ra integration cluster, more than 30 European companies are defining an open source software stack for virtualization - a home-grown, vendor-neutral solution for managing the cloud and edge computing.

The IPCEI Cloud, with more than €3 billion of investment, represents the largest open source project in the history of the EU.

Alberto Martí, chair of the IPCEI-CIS Industry Facilitation Group, welcomed the move as a positive step toward bolstering sovereign infrastructure across the region.

“I’m proud to see the EU industry finally taking the lead in developing strategic open source technologies and delivering tangible solutions for creating sovereign digital infrastructure across Europe."

The virt8ra infrastructure is being seen as a way of reducing the dependence of EU businesses and public organizations on US-based hyperscalers.

Group members said the initiative represents the first step toward building a European alternative for next-generation use cases demanding ultra-low latency, on top of a computing continuum ranging from 5G cell towers to cloud providers and data centers.

"The virt8ra testbed is our first step at Arsys towards the development of the meta-orchestration software that will enable a multi-vendor solution from technology providers across Europe," said Miguel Martínez Vélez, chief product officer at Arsys.

"It is also the kick-off for future cloud-edge continuum solutions that will boost the European data economy, digital sovereignty, and competitiveness."

The current version of the virt8ra infrastructure already supports interoperability — managing physical resources, virtual machines, and Kubernetes clusters through a single control plane — and portability, allowing applications to be easily deployed, executed, and migrated across different locations and cloud providers.

The group says it plans to add more locations and new features to meet the evolving needs of the cloud market, including the deployment of distributed AI applications at the edge.

"The virt8ra testbed represents a turning point in the way in which EU tech champions are coming together to fix the cloud market," said Ignacio M. Llorente, CEO of OpenNebula Systems and chair of the Cloud-Edge working group of the EU Cloud Alliance.

"We are finally building a sovereign cloud-edge continuum based on vendor neutrality and European open source."

Edge computing is becoming an essential part of IT infrastructure for business leaders and IT managers as they support the Internet of Things (IoT) and on-premise applications, as well as bring high bandwidth content closer to data sources. With this comes the need for better uninterruptible power supply (UPS).

This eBook from Schneider Electric discusses the challenges that UPS can come up against at the edge, and explains the benefits of three technologies that can help mitigate them, including cloud-based management and monitoring technologies.

Download now to learn more about how wide-bandgap technology works, how lithium-ion battery technology can help reduce carbon footprints, and how cloud-based software can help with staffing.

Provided by  Schneider Electric

The corporate networks of today are not your grandmother’s corporate network, to coin a phrase. Where once everything was limited to a single primary site and perhaps a couple of branch offices, business footprints have steadily grown to incorporate numerous non-traditional environments. This could be something as mundane as a user’s home or a coworking space, to more exotic locations like oil rigs or research vessels.

This is what is meant by computing at the edge, and this is often where vast amounts of useful – even critical – data is generated.

Edge computing is intimately entwined with the Internet of Things, notably devices like sensors, robots, and computer vision systems. These can generate a constant stream of data that in a traditional network environment is transferred to the public cloud or a private data center for storage and processing.

While this doesn’t pose a technical problem, it can decrease productivity due to the time taken to transfer data from one location to another for analysis, and potentially back the other way for action. In a busy environment such as a manufacturing floor or transport hub, milliseconds of processing time can mean the difference between a slow operation and one defined by efficiency.

By 2025, 80% of data is expected to be processed at source, according to the European Commission, and the majority of this will come through edge computing. However, businesses need to implement networks that can support this if they want to make full use of the data they generate.

Edge computing in practice

Often, edge computing is talked about from a very high level, abstract point of view, so it’s worth considering some concrete examples of where the technology can make a real difference.

Consider a standard warehouse environment, where the stock it contains must be kept within a certain temperature range. Smart thermostats could monitor the temperature, analyze if it’s within the defined parameters and, if needed, engage the heating or cooling system to warm the air up or cool it down. If there’s a regular problem, such as the temperature always going out of range at 2pm on a Wednesday, an alert could be automatically generated for an engineer to come and investigate the cause.

Another widely used example is monitoring machinery on a production line, wind turbine, oil rig, or another situation where failure or degradation could be disruptive or even dangerous. Analyzing data from sensors and other monitoring equipment in real time means alerts can be raised as soon as parts start to weaken and before a complete failure occurs. This in turn minimizes risk to both the facilities and the people working there, as well as reducing the cost associated with unscheduled downtime.

While these possibilities are exciting, an intelligent edge is only possible when the right infrastructure is in place.

The right infrastructure in the right place

The basics of creating an intelligent edge network are largely predictable. Wireless access points, which can be installed both indoors and outdoors, are needed to provide wireless capacity across a site with low-latency connections.

A software-defined wide area network (SD-WAN) can be an excellent solution for edge connectivity. This is a virtual service for connecting disparate devices and locations using network technologies such as broadband, 5G, and LTE, and is more suitable for cloud-based applications.

SD-WANs can be especially useful for edge networks as they reduce latency compared to legacy WANs, and allow IT teams to remotely manage routing protocols.

As well as SD-WANs, a network of capable wireless switches will also be necessary for the infrastructure to function.

For real time analytics, though, specialist infrastructure is required. Hewlett Packard Enterprise (HPE) has an array of products and services that can help businesses achieve the advantage they need through edge computing.

HPE Edgeline converged infrastructure, for example, are optimized for use in edge settings, while Aruba Edge Services Platform (ESP) can help with automation and analytics.

To make the most of their intelligent edge, organizations should also consider using HPE GreenLake, the company’s hybrid cloud platform.

An edge-to-cloud approach

HPE GreenLake allows you to take advantage of public cloud features like scalability, automation, analytics and artificial intelligence (AI) while still maintaining the benefits of private cloud such as data sovereignty and security.

Data protection is an important part of any edge strategy that should not be overlooked. The data generated and analyzed at the edge should be treated as sensitively as intellectual property (IP) or personally identifying information (PII) such as payroll details, as it could both give away details of how a business operates and open it up to disruption from malicious actors.

HPE GreenLake allows organizations to keep control of their sensitive data and offers protection such as identity and access management, as well as  providing controls for data location and movement. Through HPE GreenLake Platform, IT professionals can manage all elements of their edge network and hybrid cloud in one place. This includes networking services from Aruba, an HPE company, which can be managed through the Aruba Central console, as well as data analytics applications like Splunk that can be provisioned through this single pane of glass.

Additionally, when the data that’s being created at the edge no longer needs to be analyzed immediately, it can be moved to another part of the organization’s hybrid cloud estate for warm or cold storage. Thanks to HPE GreenLake’s elasticity and quick provisioning, it’s easy to increase storage capacity in the business’ private cloud as needed without having to worry about overprovisioning or running out of space.

Edge computing offers up a new world of insights and possibilities. With HPE GreenLake, businesses can make the most of their data in a way that suits them with a true edge-to-cloud hybrid platform.

For more information on edge computing, visit  Connect your edge with HPE GreenLake

Splunk has launched new AI tools for its security and observability platform as well as its new Edge Hub for more streamlined edge data analytics. 

The Splunk AI Assistant - now in preview - is designed to assist users with the authoring of Splunk Processing Language (SPL) queries.  

Generative AI is leveraged via an AI chatbot to write or explain SPL, something the company says will improve time to value and make SPL more accessible. 

Mark Woods, chief technical advisor EMEA at Splunk, told ITPro that training for the model behind the generative AI was based on the company’s own knowledgebase and that the limited release preview had been based on the company’s own internal experts. 

Woods’ words stand to reassure customers concerned that sensitive data might turn up in the AI. 

He said: “We wouldn’t have any visibility of the actual query that you’re putting in place, nor of any of the data that you are taking”. 

As well as the Generative AI tooling, Splunk also previewed ML-Assisted Thresholding to use historical data and patterns to create dynamic thresholds.  

Its IT Service Intelligence also features greater detection accuracy, with the Outlier Exclusion for Adaptive Thresholding aimed at detecting and omitting abnormal data points and outliers. 

A preview of the OpenTelemetry Collector was also announced, aimed at providing a unified view of an enterprise’s infrastructure and services.  

Splunk Edge Hub 

The new Edge Hub device was also shown off and is aimed at simplifying the ingestion of data into Splunk’s analytics platform. 

The compact device weighs in at just over 600g and designed to be mounted in a variety of customer environments. Splunk envisages customers simply plugging it in and using the device to stream environmental data back for analysis. 

Onboard sensors comprise temperature, humidity, light, and sound. The device also features an accelerometer and gyroscope, and it can monitor air pressure and air quality. Typical applications of the latter sensor - according to its manufacturer, Bosch - include spotting unusual gases - indicating a possible leak - and spoiled food detection. 

The device also features a screen with a dashboard showing the current sensor readings and can be connected via WiFi, Bluetooth, LTE, or Ethernet. Power is supplied by either USB-C or Power-Over-Ethernet. 

The Cortex-based processor within the device - a Verdin IMX8M+ Quad with 8GB of RAM - has sufficient power for collection and collation of data from the sensor suite. 

Woods said to ITPro that he expected the device would open customers’ eyes to the data in their OT and IoT environments: “They suddenly start to see the data that they already have all around them”. 

“All those functional domain-specific environments, they become really tangible and valuable to customers.” 

Who is Splunk’s Edge Hub for? 

Woods identified three main user groups for the device. Compared to fitting out an environment with sensors, Splunk feels the Edge Hub represents a relatively low barrier to entry, so the first user group targeted is the one that has yet to use sensors and the data does not exist. 

The second group, according to Woods, might have some sensors installed, but the systems are closed and Splunk’s device represents a useful bridge. 

Finally, there is the group that is already equipped with sensors in their environment - (Woods cited Mars as an example - and the Edge Hub provides additional resilience or a way to experiment without adding a toll to an operation system. 

Splunk said that data from the device could be used as part of its predictive analytics platform to spot anomalies in manufacturing processes as well as detect, investigate and remediate physical threats from a single platform. 

The Splunk Edge Hub is US-only for now - although the company plans to roll it out in EMEA and APAC. It is also only available through the company’s partners. 

For over a decade, cloud computing has revolutionized the way we work, and public cloud services from hyperscalers, SaaS companies such as Dropbox, Salesforce, and more changed the way compute, storage and software were consumed. 

The use of SaaS, PaaS, IaaS and myriad other ‘as a service’ offerings has only grown since then, with organizations steadily testing and adopting more and more cloud services. In 2020, with the arrival of the global COVID-19 pandemic and shift to widespread remote working, businesses that had been lagging behind quickly took the plunge as well.

Yet for many, there remain nagging concerns around security. In the early days of public cloud, the phrase “shadow IT” came to encapsulate the worst fears of many IT decision makers: People working outside of the IT department were directly purchasing services such as cloud-based ERP systems or document storage for corporate use without involving IT . In doing so, the purchaser put potentially sensitive company data at risk and obscured it from any oversight and governance that had previously been put in place by the IT team. Costs could also quickly mount up, as this lack of transparency left the door open to duplicate purchases and less favorable terms than if the contracts were centrally managed.

While we hear less about shadow IT these days, the issue of data ending up where it shouldn’t and exposing businesses to security risks hasn’t gone away. Sensitive information – be it customer data, confidential financial documents, or intellectual property – can easily be leaked through a misconfigured public cloud storage service, for example.

The challenge for IT decision makers, then, is this: How to make best use of everything that hybrid cloud has to offer, all the way to the edge, without putting sensitive information at risk.

Hybrid: the winning strategy

Hybrid cloud, which allows for a mixture of on premises private cloud, public cloud and colocation, has come out on top as the best strategy for most enterprises. For non-sensitive data or documents, such as user guides, manuals or anything else that’s supposed to be accessed by those outside the business, public cloud is an obvious choice. Details of personnel, and sensitive business critical data on the other hand, are best kept as tightly guarded as possible on premises.

This may seem straightforward, but it’s not as simple a solution as it may first appear. One major hurdle is that data may need to move from where it’s generated to where it’s consumed. This could be from hot to warm to cold storage, from public cloud storage to private (or vice versa), between different public cloud providers, or any other strategic or business need. Navigating data between these environments and ensuring it’s secure in transit and at rest is something that can’t be taken for granted.

It’s also important not to overlook edge computing, where data is created, analyzed, and acted upon at a node on the edge of a network – such as a robot in a factory, sensors measuring performance of specialist industrial equipment, or even a remote worker’s laptop. These devices are generating huge volumes of data, while communicating with and sending data to other parts of this hybrid network, and it all needs to be secure and protected from cybersecurity threats.

Securing such a diverse environment can be incredibly complex, as each different element may need its own configurations, its own layers of security, user access and authentication, and its requirement for cyber skills sets that may not be easy to find. Consequently the cost, both in terms of money and time, can be high.

Zero Trust

HPE GreenLake is known for bringing the flexibility and agility of the public cloud to the data center, but it can also  help enterprises keep their data and environments secure in a hybrid world.

HPE takes a zero trust approach to security, which focuses on identity and access management (IAM). It starts from the assumption that anything or anyone trying to connect to the corporate environment hosted in HPE GreenLake – whether that be users, applications, devices or something else – is compromised. This removes the reliance on perimeter security systems, such as firewalls or VPNs, and instead puts the security of individual software systems front and center.

"Zero Trust is not about implementing one or another security or networking technology,” says Simon Leech, deputy director in HPE’s Cybersecurity Center of Excellence. “It's a completely new approach to the way you do security architecture."

This approach really takes into account the realities of modern business networks and the triumph of hybrid computing: Protecting your on-premises infrastructure is no longer enough when so many interactions have to take place outside the corporate firewall.

It also means that a single point of failure is no longer enough for a cyber attacker to gain access to your data – just because someone or something is connected to the network or has been in the past doesn’t mean it’s automatically trusted.

Security isn’t just about protecting data from attackers, though – it’s also about ensuring you have the right backup and recovery in place should the worst happen. Traditional backup and recovery systems are certainly better than nothing and have worked well for many years, however they are vulnerable to errors and attacks themselves. If your backup is unavailable when you need it, you may as well not have it at all.

HPE GreenLake offers continuous data protection (CDP), which delivers always-on data replication and detailed journaling. In a recovery situation, IT professionals can roll back to a particular point in time or even all the way to a backup in a known good state – a gold backup – if need be. It also uses spinning disk or SSD hardware to ensure restore processes are quicker than they could ever be with traditional tape media.

If you’re worried about the time and skills involved in setting up and managing all of these security systems, managed security offered through HPE GreenLake Management Services can help. Services such as security monitoring, vulnerability management, and assigned security officer to liaise between your organization and HPE, can help lift some of the burden of securing your growing data pool.

Managing and securing hybrid IT in a way that can adapt to the changing needs of your business can seem daunting. With the right tools and partnerships in place, however, it can be a pain free and productive experience.

Learn more about HPE GreenLake.

Global businesses running cloud, data center, and infrastructure operations have been urged to spend time reshaping their capabilities amid challenging economic conditions.

Pressure on infrastructure and operations (I&O) teams is expected to grow over the next year as organizations contend with rising costs, acute macroeconomic strain, and a rapidly evolving business landscape, according to experts at Gartner. 

Paul Delory, VP analyst at Gartner, said that 2023 will be a year for organizations to “refocus, retool, and rethink” their infrastructure capabilities and technology stack as many seek to optimize operations and work around tightening budgets. 

“In the current economic climate, the biggest problem companies face in 2023 may not be IT infrastructure,” he said. “I&O teams, however, will be impacted by economic and geopolitical forces and will have a vital role to play in ameliorating their effects.”

“This won’t be a year to realize grand ambitions, but it marks a moment to refocus, retool and rethink your infrastructure. In every crisis lies opportunity, and in this case, the chance to make positive changes that may be long overdue.”

Gartner’s claims were revealed at its IT Infrastructure, Operations & Cloud Strategies Conference, hosted in Sydney. 

Analysts highlighted four key areas in which business operations are being transformed amid a period of economic uncertainty and re-evaluation for firms. 

1. Optimizing and ‘refactoring’ cloud infrastructure

Despite a rapid uptake of public cloud in recent years, Gartner warned that “many deployments are ad hoc and poorly implemented", which is having an adverse effect on organizations’ ability to maximize their cloud estate. 

Across the year, the consultancy said I&O teams will “have an opportunity to revisit assembled or poorly architected cloud infrastructure” as firms scramble to get the most out of their IT estate. 

“The focus of refactoring cloud infrastructure should be on optimizing costs by eliminating redundant, overbuilt or unused cloud infrastructure; building business resilience rather than service-level redundancy; using cloud infrastructure as a way to mitigate supply chain disruptions; and modernizing infrastructure,” Gartner said. 

This sharpened focus on optimization will deliver cost savings and efficiency improvements long-term if done correctly, Gartner added. Research from the firm found that 65% of application workloads will be “optimal or ready” for cloud delivery by 2027, marking a significant increase from 45% in 2022. 

Underused cloud infrastructure is an issue that’s emerged in organizations in recent years due to a surge in pandemic-related cloud adoption.

However, with rising cloud costs impacting businesses globally in the last 15 months, this issue has come to the fore for many. 

Spiraling costs have prompted organizations to ‘reassess’ their relationship with the cloud and cut back on spending.  

2. New application architectures driving infrastructure changes

I&O teams are under intense pressure to meet evolving demands for new types of infrastructure, Gartner said. This includes an increased focus on edge infrastructure for “data-intensive” applications, serverless edge architectures, and 5G mobile services. 

By 2026, Gartner predicts that 15% of on-premises production workloads will run in containers, up from less than 5% in 2022. 

This highlights the need for more flexible infrastructure, however, the consultancy warned that teams “must evaluate options with” care and consider their ability to manage and integrate new workloads while working in the face of time constraints.

“Don’t revert to traditional methods or solutions just because they’ve worked well in the past,” said Delory. “Challenging periods are times to innovate and find new solutions to meet business demands.”

Containers have increasingly become a go-to way for developers to build, test, and deploy applications across multiple environments, including on-prem data centers and in the cloud. 

Research from NetApp, for example, shows that containers require less system resources than traditional or hardware-based virtual machine environments.  

Greater efficiency, enhanced application development, and increased portability are also among key benefits of containers highlighted by NetApp. 

3. Data center teams adopting cloud principles on-prem

According to Gartner, 35% of data center infrastructure will be managed from a cloud-based control plane by 2027, from less than 10% in 2022. 

This increase is being propelled by the fact that “data centers are shrinking and migration to platform-based colocation providers”, the firm noted. This, combined with new as-a-service models for physical infrastructure is providing organizations with “cloud-like service-centricity” to on-prem infrastructure. 

In the year ahead, Gartner said I&O professionals should focus on “building cloud-native infrastructure within the data center” to optimize and streamline operations. 

Gartner’s research also urged teams to focus heavily on migrating workloads from owned facilities to co-location facilities, or embrace as-a-service models for physical infrastructure. 

Migrating and integrating workloads poses challenges for businesses, however. 

With firms facing an increasing array of cloud-related options spanning public, private, and hybrid cloud, making the correct decision based on their individual circumstances, needs, and financial capabilities could make or break a successful migration. 

4. Skills growth a key priority for businesses

The pervasive issue of skills deficits will continue to plague businesses in the year ahead, meaning that attracting and retaining talent will be critical to ensuring success in infrastructure modernization projects. 

“Lack of skills remains the biggest barrier to infrastructure modernization initiatives, with many organizations finding they cannot hire outside talent to fill these skills gaps. IT organizations will not succeed unless they prioritize organic skills growth,” Gartner said. 

To tackle this growing issue, I&O leaders must make operations skills growth their “highest priority” in 2023. This includes encouraging I&O staff to “take on new roles”, expand skills through training programs, and encourage cross-functional training to ensure a broader range of applicable skills throughout teams. 

This heightened focus on cross-functional training could be key for organizations moving forward, with the consultancy’s own research predicting that 60% of data center infrastructure teams will have “relevant automation and cloud skills” by 2027. 

This marks a significant increase from just 30% in 2022, highlighting the growing appetite for firms to develop more multi-skilled teams. 

Sony’s semiconductor arm has announced a “strategic investment” in Raspberry Pi - a move that will see users given access to its edge AI platform Aitrios.

The minority stake investment, details of which remain undisclosed, “cements the relationship” between the two companies and will provide a development platform for Sony Semiconductor Solutions’ (SSS) AI devices to Raspberry Pi’s global user base, the company said. 

This means Raspberry Pi users will be able to leverage Sony’s Aitrios edge computing AI platform to develop a range of AI-based visual sensing applications. 

 “Our goal is to provide new value to a variety of industries and support them in solving issues using our innovative edge AI sensing technology built around image sensors,” said Terushi Shimizu, president and CEO at SSS. 

 “We are very pleased to be partnering with Raspberry Pi to bring out Aitrios platform - which supports the development of unique and diverse solutions utilizing our edge AI devices - to the Raspberry Pi user and developer community, and provide a unique development experience.” 

Eben Upton, CEO at Raspberry Pi, said the partnership builds on longstanding ties between the two companies and will help Sony embed AI products within the firm’s developer ecosystem.  

“This transaction will allow us to expand our partnership, bringing Sony Semiconductor Solutions’ line of AI products to the Raspberry Pi ecosystem, and helping users to build exciting new machine learning (ML) applications at the edge,” he said in a statement. 

What is Sony Aitrios?

Aitrios is an edge AI sensing platform developed by Sony and launched in 2021. 

The platform runs directly on chips, which Sony says provides users with a range of benefits in developing machine learning and AI applications and creates “synergy between edge and cloud”. 

Since its launch, Sony has positioned Aitrios as a go-to platform for developers creating AI camera-driven and edge sensing solutions. 

Aitrios use-cases cited by Sony span a number of sectors, including surveillance, security, retail, logistics, and manufacturing. 

The platform could be used to develop solutions aimed at detecting vehicle license plates or monitoring footfall in retail venues, for example. 

Capitalizing on AI hype

This partnership with Raspberry Pi could signal a move from Sony to capitalize on recent excitement in the AI space. 

Developers have already been experimenting with generative AI systems such as ChatGPT on Raspberry Pi 4 devices, for example. 

Long-term, Upton told CNBC that he envisages the partnership helping young developers learn how computers work in their modern form, rather than how they did 30 years ago. 

He added that Raspberry Pi has been used for ML development for some time now, and that the Sony partnership will allow this to evolve further.

The Raspberry Pi 4 device is largely compatible with several AI and ML frameworks, such as TensorFlow or PyTorch, making it a go-to device for both hobbyists and students experimenting with ML applications. 

However, when speaking to CNBC Upton noted that while the company has traditionally appealed to hobbyists, its popularity among enterprises has been growing steadily. 

Around 70% of its sales now come from commercial clients looking to embed products within consumer devices or general operations. 

Many businesses today are rethinking their network security solutions since the adoption of remote and hybrid work, and considering the multiple cyber security options now available. For the majority, the best solution would be to introduce new elements - like Zero Trust - that can be implemented alongside legacy infrastructure.

This study shares how converged network security - Security Services Edge (SSE) - could be the solution to achieve this, offering integrated cloud-based abilities without compromising existing environments.

Download now for the full results of this study, discover the main challenges in managing network security, including remote access, and realise the numerous drivers for adopting SSE.

Provided by

Many hybrid working environments have been adopted industry-wide since the global pandemic, with employees using collaboration tools when working from home. IT managers are therefore tasked with, not only the security of internal infrastructure, but also those collaboration solutions on the edge.

This study delves into how employees use collaboration channels, as well as how sensitive information and data is shared via these solutions, and discusses the risks and challenges when it comes to using them.

Download now to learn the risk factors when it comes to collaboration solutions, and why back ups are critical to success.

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Every security leader understands the challenges that cloud migration and distributed workforces pose to their corporate network and endpoints, and the importance of moving to a Zero Trust architecture. But the journey to Zero Trust can seem complex and difficult.

This recorded session shares how Cloudflare offers one uniform, composable platform to make this journey extremely simple and effective for organisations of all sizes.

Watch now to discover how joint customers of Cloudflare and CrowdStrike use both platforms to achieve end-to-end protection across endpoints, networks, and applications.

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With the way organisations are now operating post-pandemic, the flexibility of agile IT infrastructures has proved significantly valuable to business continuity, with this shift to cloud and subscription-style technology models paving the way forward.

The IDC predicts that by 2024, three quarters of edge infrastructure will be operated by as-a-Service solutions, yet there can be challenges when it comes to skills shortages and limited budgets to support day-to-day operations.

Download this resource to learn how HPE GreenLake’s Everything-as-a-Service platform can give your a competitive edge offering:

• Scalable IT provision
• Centralised operations
• and Automated routine management

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Join Roger Lopez and Phil Griffiths, Technical Marketing and Product Managers at Red Hat as they discuss automation controllers and automation mesh, which are new features to scale automation.

Learn what you can do to get started with scaling automation on the edge and get a better understanding of Red Hat’s new features and how they work together, with examples.

Watch now to discover how automation mesh can provide you with a mechanism for global scaling and what’s next for the platform.

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Those organisations that are becoming more data-driven are gaining a competitive advantage and solving business problems at a great pace. But this isn’t happening in the data centre or in the cloud.

Companies that need to deliver applications at scale, and solve challenges fast are doing so with an edge computing solution that enables them to reduce costs, connect existing infrastructure and support continuous innovation.

Download this resource to learn how containers and Kubernetes can help deliver edge computing benefits, as well as what to consider when building a modern edge infrastructure.

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Join Michele Null and Brian Coursen, product managers in edge-to-cloud technology, as they talk about the complexities of edge computing, how to define edge infrastructure locations, and what’s being done today.

Learn how edge computing can help organisations achieve improved operational efficiency in this 20 minute webinar sharing use cases and benefits of current edge technologies.

Watch now to discover how to extend automation to the edge with example deployments, and how a consistent edge platform can help you meet your needs.

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With the shift to the cloud, businesses have looked to enhance their performance and security, but with organisations now becoming more data-driven to get ahead of the competition, there is still room for improvement.

Edge computing offers more than gathering and processing data, with companies able to deliver enhanced customer experiences through latency sensitive apps like AR/VR. So for organisations across all sectors and sizes, investment in edge commuting can bring great value.

Download this whitepaper to learn how edge computing can:

• Increase performance
• Help your business adopt apps of new opportunities
• Meet regulatory and compliance framework
• and Enable AI/ML use cases

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As businesses continue their digital transformation journey, IT leaders are taking advantage of the benefits of cloud-hosted applications and software-defined infrastructure, with edge solutions as the driving force behind the latest innovations..

With the shift to hybrid cloud and the inclusion of edge locations - along with infrastructure and apps across multiple providers - organisations need an operating system that’s not only secure, but one that’s flexible and optimised for remote management.

Download this report to learn the key reasons for deploying edge solutions, the benefits of edge computing, and how Red Hat Enterprise Linux can ensure success.

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When it comes to security, enterprises must be increasingly agile—especially as the threat landscape continues to evolve.

This eBook serves as a practical guide to adopt a secure access service edge (SASE) in a cloud-first world.

Download now to understand why your organisation needs to retain agility and adopt new security solutions quickly and cost-effectively in today's world.

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The development of Industry 4.0 has meant that those in manufacturing can gain increased productivity and performance through technology innovations, including AI, data analytics and machine learning. However, in order to enable these emerging technologies, production and manufacturing environments need new IT systems in support, which then raises concerns about reliability, security and continuity.

This whitepaper looks at how new IT systems could be introduced “in series” with other manufacturing applications and how they could be deployed as on-premise edge computing, to add value.

Download this resource now to see how technology innovations are enabling “smart” factories with different edge computing solutions, and read best practices for mitigating downtime.

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Jacobs has announced its intent to acquire enterprise software solutions provider BlackLynx.

Jacobs' ability to deliver real-time, actionable insights addressing national security and mission-critical requirements will be strengthened by BlackLynx's software-enabled offerings and products in edge computing, hybrid cloud infrastructure, and collection automation.

Specifically, the acquisition will complement Jacobs' suite of cyber intelligence and digital services.

"As edge computing proliferates across all domains, rapidly gaining actionable insights from the vast volumes of data becomes essential," said Steve Demetriou, chairman and CEO of Jacobs.

"BlackLynx's embedded analytics platform provides real-time AI and ML image and data classification in the cloud and at the edge. The combination of Jacobs' deep domain knowledge and BlackLynx's next-generation technology will unlock new opportunities to create a more connected and sustainable world."

BlackLynx’s BlackStack software accelerates processing speeds for sensors deployed within ground, naval, and aerial systems. Additionally, Enterprise scale automation helps businesses automate application development, manage DevSecOps environments, and provide data ingestion, transport, and security solutions at scale.

In addition to expanding Jacobs' position to 14 of 18 US Intelligence Community agencies, the merger will align BlackLynx with Jacobs' Cyber and Intelligence business unit led by senior vice president Caesar Nieves.

Jacobs plans to use BlackLynx's software systems to support government services, including transportation, water, and smart city infrastructure.

"With our shared values and strong cultures of performance excellence and innovation, our combination creates new opportunities for our people, our clients, our industries and the communities where we live and work," said Doug Wolfe, BlackLynx CEO.

"Gaining real-time insights from data is a key ingredient in modernizing and securing our global infrastructure. Jacobs' strategic position supporting the United States' most critical missions and infrastructure creates a new trajectory for our leading software-enabled services."

Ori Industries has teamed up with VMware to assist enterprises with edge computing deployments on hybrid, telco, and multi-cloud platforms.

"Edge computing is entering the mainstream", according to a 2021 Gartner report. “However, many enterprises struggle with their existing cloud deployments proving to be a barrier to edge adoption.”

Ori Global Edge on VMware Telco Cloud Platform enables a multi-connected edge by leveraging multiple points of presence (PoPs) that connect to teleco and communications service provider (CSP) infrastructure on one end and cloud services on the other.

Additionally, interoperability between VMware Telco Cloud Platform and Ori Global Edge will help reduce complexity, accelerate service velocity, and enhance cloud-native service management at the edge.

The fully functioning edge platform will connect to any cloud environment in telco, hybrid, or multi-cloud. Furthermore, customers can enjoy more reliable service at the edge with low latency, high-availability applications that generate and process data locally, eliminating the need to transfer data back to the cloud.

Ori Global Edge’s Workload Placement feature orchestrates application requirements on-demand and can scale up workloads to meet traffic spikes in real time. With zero-touch provisioning, VMware Telco Cloud Platform simplifies Kubernetes operations for multi-cloud deployments.

“Enterprises are looking for new ways to engage customers and deliver next-generation experiences. That means having the right application deployed where the user is,” explained Stephen Spellicy, vice president of product marketing, service provider and edge at VMware.

“Edge computing is the final piece of the puzzle and working with Ori Industries’ multi-access edge computing platform will give mutual customers the ability to deploy a solution that helps cover all their environments – whether telco, hybrid, multi-cloud or edge – to meet their business needs. ”

MicroSys and Hailo have entered a strategic alliance to release MicroSys' miriac AIP-LX2160A embedded platform, featuring up to five Hailo-8 artificial intelligence (AI) accelerators.

The new edge server-grade AI solution, equipped with NXP QorIQ Layerscape LX2160A processor, brings high-performance and scalable AI inference capabilities at the edge, benefiting a wide range of Industry 4.0 applications. Up to five parallel Hailo-8 AI accelerators deliver massive processing speeds of up to 130 tera operations per second (TOPS).

The combined solution boasts exceptional AI computing performance against standard neural network (NN) benchmarks, with over 6000 frames per second (FPS) on Resnet-50, over 5000 FPS on Mobilenet-V1 SSD, and close to 1000 FPS on YOLOv5m.

"Our strategic partnership with Hailo is an important milestone, helping our customers reap the enormous benefits of AI and neural networks," said Ina Sophia Schindler, managing director at MicroSys Electronics.

Schindler added, "Hailo's AI processor allows edge devices to run full-scale deep learning applications more efficiently, effectively, and sustainably while significantly lowering costs. In combination with our NXP processor-based platforms, our customers get one of the most powerful AI solutions that can be developed for edge applications."

MicroSys Electronics’ AI starter kit is applied in predictive maintenance, collaborative robotics, distributed surveillance infrastructures, and more. Also included with the AIP-LX2160A embedded platform is a carrier board, cable set, and cooling solution.

Developers will also be able to access comprehensive AI toolchains offered by MicroSys within Hailo's developer zone.

"We are excited to partner with MicroSys, a world-leader in embedded systems," said Orr Danon, CEO and co-Founder of Hailo.

"This collaboration strengthens our position in the edge computing sector, enabling us to further address the rapidly growing market seeking embedded edge platforms with robust AI capabilities. We look forward to continuing to work with MicroSys to bring unmatched edge processing solutions to a broad range of automotive and industrial automation applications."

Cellebrite has announced its new remote mobile data collection solution for handheld devices and computer systems.

Integrated into Cellebrite’s Endpoint Inspector, the new solution streamlines corporate investigations, e-discovery, and incident response. It can retrieve data from iOS and Android mobile devices and computers running Windows and macOS.

"We focused on simplifying the employee experience during data collection and deployed our domain expertise to engineer Endpoint Inspector to automate the complexity of the collection process and limit business interruption," said Ken Basore, general manager of enterprise solutions at Cellebrite.

Basore continued, "In Enterprises that deploy Endpoint Inspector, employees no longer need to hand over their device or spend hours with internal support personnel to follow complex procedures. We are pleased to be able to bring this value to our enterprise customers across life sciences, banking, insurance, and other industries.”

Commenting on scope, Cellebrite said its remote solution could gather evidence from devices inside or outside an organization's IT network. The capability adds to the firm’s Endpoint Intelligence solution that integrates data from disparate sources to provide a 360-degree view of employee communications.

Additionally, a Smart Collections feature within Cellebrite's remote data collection solution ensures only pertinent data is collected on any device. Data collection occurs with the explicit consent of employees, and an audit record is automatically generated upon confirmation.

Together, Cellebrite’s Endpoint Intelligence platform and remote data collection solution help businesses counter fraud, detect intellectual property theft, investigate claims of employee misconduct, and more.

“Corporate investigators are under serious pressure, now having to face the additional challenge of sourcing data to support cases from a geographically scattered hybrid workforce, who are using more devices and messaging services than ever before for professional communications. Today's announcement underscores the strategic importance of Cellebrite's cloud capabilities and our commitment to ensure enterprise investigators can adapt to a hybrid workforce, " added Basore.

Vecow has announced its new artificial intelligence (AI)-powered edge computing solution: ECX-2400 AI.

Developed in partnership with Blaize, Vecow ECX-2400 AI features programmable GSP architecture, ensuring low latency and high performance.

Powered by 10-core 10th Gen Intel Xeon/Core i9/i7/i5/i3 processor and built on Blaize Xplorer X1600P PCIe series AI accelerator card, Vecow ECX-2400 AI also delivers increased system reliability, reduced power consumption, and faster time-to-market at a lower total cost of ownership.

The system is geared toward Industry 4.0 applications, including smart AOI, traffic vision, robotic control, and more.

The compact and rugged Vecow ECX-2400 AI also pairs Blaize Picasso SDK with VHub AI developer software. This allows users to build, deploy and manage edge AI inference systems with single-core or quad-core Blaize Xplorer AI Inference Accelerators.

Vecow global sales director Joseph Huang said, “It’s our honor to carry a new powerful and lower power consumption AI accelerator solution to the market. Industrial users have stringent requirements for trusted and reliable AI computing engines with longevity support and less total cost of ownership. This collaboration with Blaize contributes our global partners and customers closer to their success with faster time-to-market consideration. We will keep engaging advanced AI technologies to benefit to our global partners and customers.”

Vecow’s AI computing system also addresses industrial demands with its smart system protection functions, including 12V to 50V wide range DC input, 80V surge protection, and software ignition control.

Optional VHub Artificial Intelligence of Things (AIoT) solution offers support for OpenVINO based AI accelerator and advanced edge AI applications.

“We look forward to jointly engaging with end customers and channel partners to deliver the new levels of efficient and cost-effective AI inference systems enabled by the Vecow ECX-2400 AI,” said Barrie Mullins, senior director of product marketing at Blaize.

Mullins added, “Industrial customers using vision analytics in use cases such as industrial inspection, manufacturing production line anomaly, human-robot interaction, employee safety and smart camera systems can utilize the ECX-2400 AI to advance operational efficiencies and processes.”

Myriota has struck a new deal with Spire Global to enhance its global satellite network.

Myriota’s low-cost yet robust internet of things (IoT) connectivity helps customers track, locate, and monitor a wide range of assets, including vehicles, wind turbines, shipping containers, and more.

In addition to providing affordable IoT connectivity, Myriota also eliminates the need for ground-based satellite infrastructure. As part of the new deal, Myriota will employ Spire’s space services and low-earth orbit nanosatellites to develop a global, low-latency constellation.

Spire’s constellation of low-earth orbit nanosatellites features software-defined radio (SDR) technology, enabling partners to test, deploy, operate, and scale custom applications. Over 110 satellites measure temperature, pressure, and humidity at over 10,000 intervals per day, allowing for a holistic 3D weather profile.

Leveraging the firm’s 300 years of space flight heritage, Spire’s in-orbit-reprogrammable platform ensures flexible operations in space. Building on Spire’s space-as-a-service capabilities, Myriota plans to scale its IoT services swiftly and efficiently to meet global demand.

The Myriota-Spire Global partnership is also geared toward growing Myriota's customer base beyond North America, Australia, and New Zealand.

“We’re proud our satellites and technology are ready to seamlessly help Myriota make smart devices more accessible to everyone,” said Theresa Condor, executive vice president and general manager of space services and earth intelligence at Spire.

“Australia is a hotbed of innovative companies, and it’s gratifying to help a leading satellite connectivity provider go to market quickly and scale up efficiently.”

Myriota is Spire's first large-scale, commercial IoT customer.

“With high demand for the Myriota Network from our partners, who are rolling out products at an ever-accelerating rate, this agreement is a game-changer for our business,” said Dr. David Haley, CTO and co-founder of Myriota.

“By leveraging Spire’s constellation, Myriota will rapidly improve its services, and enter new markets such as Europe. Spire is a perfect partner for extending our global reach.”

DevOps software company JFrog has acquired Israel-based Upswift, a firm that makes software to manage internet of things (IoT) devices. JFrog will use Upswift's software to extend its DevOps management capabilities to edge devices.

The Upswift acquisition brings new capabilities to JFrog customers, including dependency scanning, CI/CD, artifact management, and device software updates. It will also help to make connected devices more secure, JFrog said. IoT security continues to be a problem for enterprises.

The integrated platform will enable developers to manage the software development pipeline for IoT devices from coding through deployment at the edge. It will also track software releases, including incremental updates, and will include the ability to update large numbers of devices, which are common in edge and IoT environments.

Developers and engineers will be able to monitor device health in real time and access individual IoT devices from a browser or via an application programming interface (API) for remote control purposes.

JFrog offers its DevOps management platform as a self-managed service or as a software-as-a-service (SaaS)-based cloud system. It uses separate components, including the VCS code repository, the Artifactory software package manager, the XRay security and compliance monitoring system, and a container registry. It also features a distribution system and a software pipeline manager.

JFrog plans to integrate Upswift's platform into its own over time. It brings other features including a software container management system, data and resource monitoring for edge devices, hardware log management, and a map administrators can use to see edge and IoT device locations.

Upswift, which uses device-side agents for its edge and IoT-based management, claims it can connect Linux hardware to its management system in under a minute.

Edge computing is a buoyant market. IDC has predicted a 43.5% growth in managed edge services this year alone.

Lenovo Infrastructure Solutions Group (ISG) and VMware have teamed up to enable resilient edge computing.

As part of the new partnership, Lenovo ISG will integrate VMware's edge software with its ThinkSystem SE350 Edge Servers.

The preloaded software will be directly accessible to customer edge sites via two ruggedized ThinkSystem SE350 servers. Lenovo has also announced enhancements to its Open Cloud Automation software, enabling customers to plan, deploy, and manage data center cloud and edge infrastructure simultaneously.

“For better business continuity, improved applications and user experiences, hybrid cloud models are being deployed both in the cloud and at the edge,” stated Charles Ferland, vice president and general manager of edge computing and communication service providers at Lenovo ISG.

Commenting on the firm’s hybrid solution, Ferland said the new software can reduce the number of servers required at the edge by half. Additionally, ThinkSystem SE350’s integrated networking features will eliminate the need for additional networking elements at edge sites.

Lenovo will reportedly be the first to market with VMware and its upcoming software solutions for the edge. The solutions will include built-in switching and wireless connectivity to simplify network configuration.

Most notably, the integrated VMware bundle on ThinkSystem SE350 Edge Server will help customers recreate the environment they have in their data centers at their edge locations.

Thanks to its rugged chassis, the ThinkSystem SE350 Edge Server can endure high temperatures, shocks, and vibrations, making it ideal for harsh environments. Its encrypted hard disks, along with motion and tamper detection, guarantee data and device security at all times.

“Deployment of distant edge sites requires a management toolset that seamlessly allows organizations to automate tasks, without requiring specialized staff on-site. Lenovo has enhanced its Lenovo Open Cloud Automation software solution to now include edge-supported features, driving accelerated time to value for customers with cutting-edge management capabilities,” added Lenovo.

IBM has unveiled a set of secure access service edge (SASE) solutions to help customers secure complex distributed work environments.

SASE is a concept first articulated by Gartner in a 2019 white paper. It combines security and SD-WAN in a cloud-based approach designed to embed security directly into the network. This enables companies to apply security policies in the cloud that govern users no matter where they are.

Because the network and security are software-defined, administrators can manage them programmatically, making it easier to update these policies across the organization.

IBM Security Services for SASE is an end-to-end offering covering strategic consulting, design and integration, and application onboarding. It also encompasses a set of managed security services in the cloud to protect user sessions and data, such as secure web gateways, cloud-based firewalls, cloud access security broker services and data loss prevention.

Zero-trust security is another big component of SASE. This part of the solution removes implicit trust for people that access the network and verifies their identity when accessing resources inside the company's infrastructure. Zscaler, with which IBM partnered in May, will provide the zero-trust functionality for IBM's SASE portfolio.

IBM sees potential for its SASE services in areas such as hybrid workforce access, contractor and third-party access, and edge computing scenarios. It can also help to secure businesses undergoing mergers and acquisitions, the company said.

IBM commissioned a study from Forrester to support its SASE roll-out, and it found 60% of companies lacked a clear security strategy spanning their entire cloud deployment.

Most companies (70%) found it challenging to implement centralized security controls across multi-cloud environments, while almost two-thirds found it difficult to secure their remote and in-office employees across multiple devices and locations.

IDC has predicted a bright future for the managed edge computing services market as multiple drivers compel businesses to rethink their computing architectures.

The market research company forecasts worldwide revenues of $445.3 million for the managed edge services market this year, up 43.5% compared to 2020. This positive trend will continue until at least 2025, with a compound annual growth rate of 55.1% during that period.

Managed edge services are low-latency services that process data near the edge of a network, closer to where it is consumed and produced. Services in this emerging market range from content distribution through to edge application hosting and real-time data analytics.

IDC has identified three types of managed edge services environments. On-premises or private deployments located at the customer's facilities, such as production plants or health care facilities, will be the fastest-growing use case with a five-year CAGR of 74.5%. An example might be augmented reality services or industrial automation.

Service provider deployments in a public cloud service or telco's premises will enjoy the second-fastest growth. IDC added that this use case will involve fixed and mobile deployments and would be significant for sector-specific applications. It expects a CAGR of 59.2%, making it the largest market segment by next year.

Finally, IDC singled out content distribution network (CDN) services as a specific use case. CDNs will continue to refine their services with new edge technologies. IDC expects more personalized and interactive media experiences from the CDN managed edge services segment, enjoying a 41.9% CAGR over five years.

A key driver for the deployment of managed edge services is the need for process efficiencies. Analysts also pointed to new consumer applications, such as augmented and virtual reality.

Data sovereignty and security measures will also be big drivers as companies strive to maintain regulatory compliance while pursuing better customer experiences.

5G will also play a big part in managed edge services, the company said. Cloud service providers will partner with 5G infrastructure companies — typically telcos. Data center operators will also be eager to participate, as will network equipment vendors and software companies.

The US Air Force has enlisted Novetta's platform for integrated C3 and responsive defense (PICARD) for base military operations at Seymour Johnson Air Force Base.

Novetta designed PICARD to meet USAF's need for a platform to connect forces with intelligent systems for rapid decision making. By integrating internet of things (IoT) principles into sensor fusion, Novetta created a hybrid edge-cloud system that combines DevSecOps with non-traditional operational technologies, including electronic security, control, and weapons systems.

This way, PICARD uncovers data hidden in disconnected, proprietary, and legacy systems. Operators receive actionable insights regardless of where they are or how they access the data.

Thanks to its open architecture, the platform seamlessly integrates with sensors, control systems, connected devices, weapons systems, and more.

"It has been a pleasure seeing the partnership between our team and the Air Force yield truly transformative results," said Kevin Heald, senior vice president of information exploitation at Novetta.

"PICARD is a key part of a grander vision to contribute to the Air Force Advanced Battle Management System (ABMS) and the DoD Joint All-Domain Command and Control (JADC2) initiatives."

"We are proud to partner with the Air Force and the hard-working, innovative people at AF/A4S, LCMC/HBU, and SAF/CDM modernizing Security Forces capabilities and operations," commented Steven Adelman, senior director of sensor fusion and IoT portfolio at Novetta.

Adelman added, "PICARD begins to deliver on the promise of Integrated Base Defense and all-domain data sharing. We look forward to continuing to evolve the platform and deliver for the career field and the Air Force."

Per reports, the Air Force will extend PICARD to 11 military bases by 2022 and across the entire branch by 2026.

IBM and Verizon have expanded facilities at their Industry Solution Lab in Coppell, TX to include an environment for developing and testing 5G-enabled use cases for Industry 4.0 applications.

The new capabilities will enable enterprise customers to develop and test how 5G Ultra-Wideband can combine with hybrid cloud, edge, and artificial intelligence (AI) technologies to enhance next-gen use cases like robotics, guided vehicles, manufacturing process automation, visual quality inspection, data analytics, and more.

Verizon has installed 5G ultra-wideband and multi-access edge computing (MEC) to trial use cases, alongside IBM’s hybrid cloud and AI technologies, which run on Red Hat OpenShift.

The lab will offer customers a pre-commercial, standalone 5G network and all the technical resources needed to test and optimize products. Customers can co-create business-specific use cases and jointly work with IBM Global Business Services and ecosystem partners to leverage these technologies in solving current business challenges and bring new solutions and services to market.

The lab will focus on three priority areas that take advantage of 5G networks.

The first area is asset monitoring and optimization. IBM and Verizon said major shipping companies with ground and package-handling facilities could use the IBM Maximo Application Suite and IBM Acoustic Insights to trial how they can use ultrasonic technology to anticipate and prevent their package handling machinery from malfunctioning.

The second area is in field worker productivity and safety. By using Maximo Mobile on devices on the Verizon 5G Network, a utility company could trial scenarios where it uses AI, remote human assistance, and real-time data to “improve the on-the-job safety and enhance the quality and efficiency of fieldwork with guided workflows, reducing multiple repeat inspections and repairs of the same equipment.”

The third area is visual inspection. IBM said industrial product manufacturers could leverage IBM’s suite of visual inspection products, including IBM Maximo Visual Inspection.

“Mobile devices running the suite could be mounted on assembly lines, robotic arms, or even held or worn by the user to inspect components and finished goods for defects using near real-time insights to improve manufacturing processes,” said Steve Canepa, global GM & managing director at IBM’s Communications Sector.

He added that the joint 5G test bed with Verizon “serves as a signal of IBM’s ongoing investment in capabilities that include, among others, centers of excellence and labs around the world.”

IBM and Scale Computing have inked a new deal to help enterprises optimize their edge computing strategies.

In a recent IBM study, 91% of the respondents stated their organizations plan to implement edge computing within the next five years. Along these lines, IBM is expanding its Edge Application Manager to include Scale Computing’s HC3 Edge Computing platform.

An all-in-one solution, HC3 Edge Computing lets businesses run modern containerized workloads alongside legacy applications. Powered by patented HyperCore technology, HC3 systems can self-heal to keep applications running at all times.

From deployment to maintenance and remediation, users can centrally monitor and manage their distributed infrastructure and applications fleet.

This adds to IBM’s Edge Application Manager, an autonomous management solution to create, deploy, run, monitor, and scale analytics applications at the edge.

“We look forward to collaborating with Scale Computing to help clients deploy, operate and manage thousands of endpoints throughout their operations with IBM Edge Application Manager. Together, we can help enterprises accelerate their digital transformation by acting on insights closer to where their data is being created, at the edge,” said Evarisitus Mainsah, general manager at IBM Hybrid Cloud and Edge Ecosystem.

According to Scale Computing, deploying HC3 Edge Computing doesn't require VMware or any additional hypervisor licenses.

“We believe that Edge computing is critical for the future of many organizations, and organizations of all sizes across all industries can take steps now to help simplify the deployment and management of localized compute infrastructure in a secure and resilient manner,” said Jeff Ready, CEO and co-founder of Scale Computing.

Ready continued, “We are excited to team our HC3 Edge Computing solutions with IBM Edge Application Manager in an effort to help organizations optimize their operations across the globe with infrastructure designed to be self-healing and automated, as well as added containerized application management that can help them grow into the new reality of edge computing.”

Akamai has announced several enhancements to its EdgeWorkers platform to make it more developer-friendly.

EdgeWorkers by Akamai offers support for multiple uses, including ‌microservices,‌ ‌request processing, ‌and‌ ‌Akamai-as-code management. In its latest release, Akamai provides developers with even more control and capabilities ‌at‌ ‌the‌ ‌edge. In addition to a new free tier, the platform now offers rapid data access‌ ‌and‌ ‌API‌ ‌traffic‌ ‌acceleration.

A‌ ‌total‌ ‌of‌ ‌60‌ ‌million‌ ‌EdgeWorker‌ ‌events - up‌ ‌to‌ ‌30‌ ‌million‌ ‌per‌ ‌tier - are‌ ‌included‌ ‌for‌ ‌free‌ ‌as part of the new Basic and Dynamic Compute levels.

Akamai's Basic Compute tier caters to applications that need only a small amount of‌ ‌CPU‌ ‌or‌ ‌memory. The Dynamic Compute tier is for extensive workloads with high CPU or RAM requirements.

Additionally, the new EdgeKV capability enables high-availability and low-latency access‌ ‌to‌ ‌data‌ ‌at‌ ‌the‌ ‌edge. A globally distributed key-value store, EdgeKV bridges the gap between edge applications and databases.

Also included in the service is a JavaScript Helper Library that simplifies read, write, and update operations within the EdgeWorkers code. Role-based access controls prevent unauthorized access to EdgeKV databases.

Lastly, Akamai's API Acceleration solution ensures API transactions are efficient by prioritizing routing and reserving‌‌ ‌‌capacity. The service is optimized for API traffic and utilizes purpose-built hardware to offer increased reliability and performance at scale.

With‌‌ ‌‌Akamai‌‌ ‌‌Sandbox,‌‌ ‌‌developers can create parallel yet isolated sandbox environments to test new configurations ‌quickly while‌ ‌still‌ ‌accessing local‌ ‌origins‌.

"Since introducing EdgeWorkers, we have been inspired by the creative ways customers are using the Akamai Intelligent Edge to deliver amazing user experiences,” said Lelah Manz, senior vice president of edge technology group at Akamai.

“With this latest platform release, we hope to accelerate this innovation by giving developers the ability to build truly transformative applications at the edge. We know that we're just scratching the surface and can't wait to see what new ideas take shape using EdgeWorkers and the Akamai platform."

VMware‌ ‌and‌ ‌Vapor‌ ‌IO‌ ‌are‌ ‌collaborating on a Multi-Cloud Services Grid to help developers and service providers deliver on-demand custom grid services.

The collaboration's key objective is to simplify the deployment of distributed 5G systems and real-time applications by weaving cloud and edge environments together into a unified framework that allows for resource distribution across shared infrastructure on demand.

"Today's internet is too static, too siloed, and too unpredictable to deploy latency-sensitive applications, such as immersive gaming," said Kaniz Mahdi, vice president of advanced technologies at VMware.

"What we need, instead, is a grid that can virtualize and stitch together edge resources across multiple clouds and locations for any given set of latency and jitter constraints at any given time."

With Multi-Cloud Services Grid, resources are hyper-composed at the exact moment the application requires them. If, for example, an application requests to traverse the least expensive resources in the fastest possible manner, the grid will assemble those resources when it is used and return them to the grid when it is not, dismantling them in the process.

The Multi-Cloud Services Grid is backed by VMware's Telco Cloud Platform and Vapor IO's Kinetic Grid platform.

"Vapor IO's Kinetic Grid architecture, which connects across markets with Zayo's dark fiber backbone, gives us the potential to span the continental U.S. and become a platform to engage the full edge-to-core ecosystem," said Cole Crawford, founder and CEO of Vapor IO.

"The Vapor IO and VMware teams will deploy bedrock capabilities that serve the entire community, growing opportunities for providers and consumers across the entire stack. We want this to be the catalyst for other organizations to co-create and co-innovate with us, developing the new technologies and go-to-market business models that will enable us to collectively deploy the Open Grid at scale, worldwide."

Las Vegas, Atlanta, and Dallas will be the first cities to use the Multi-Cloud Services Grid as a platform for crowdsourced innovation this year. The‌ ‌service‌ ‌will‌ ‌cater to the needs of mobile service providers, cloud providers, infrastructure owners, hardware and software developers, municipalities, and enterprise businesses, among others.

CloudFront Functions, Amazon Web Service’s (AWS) new serverless scripting platform for running lightweight JavaScript code at the edge, is now generally available.

Amazon CloudFront provides customers with the ability to deliver content, such as data, videos, and APIs, securely with low latency and high speed.

To help ease complex and compute-heavy operations and customizations, AWS introduced Lambda@Edge functionality as part of Amazon CloudFront in 2017. Due to faster processing power in data centers, Lambda@Edge functions are typically executed from regional data center cache instead of edge locations.

“When you’re streaming video or audio, you can use Lambda@Edge to create and serve the right segments on-the-fly reducing the need for origin scalability,” explained Amazon.

CloudFront's second category of use cases involves handling simple HTTP(S) request/ response manipulations via short-lived functions.

The new CloudFront Functions from AWS offer the performance and speed required to process millions of requests per second. A process-based isolation model combined with specific network and file system access restrictions enables scalability. This is in stark contrast to Lamda@Edge, which relies on virtual machine-based (VM-based) isolation.

According to AWS, CloudFront Functions are best-suited for lightweight web request processing, including cache-key manipulations and normalization; URL rewrites and redirects; HTTP header manipulation; access authorization; and more.

CloudFront Functions, like Lambda@Edge, respond to events generated by CloudFront. In particular, CloudFront Functions can be triggered upon receiving a viewer request or delivering a viewer response.

“Lambda@Edge can also be triggered before CloudFront forwards the request to the origin (origin request) and after CloudFront receives the response from the origin (origin response). You can use CloudFront Functions and Lambda@Edge together, depending on whether you need to manipulate content before, or after, being cached,” said Amazon.

Using Lambda@Edge before or after CloudFront caches content is an option if you need certain features of Lambda@Edge that aren't available in CloudFront Functions.

Verizon and Amazon Web Services (AWS) are extending their 5G collaboration to deliver private mobile edge computing (MEC) for enterprises requiring a dedicated edge compute infrastructure on-premises.

Designed to support low-latency data transmission, the new Verizon-AWS-powered private MEC combines Verizon’s Private 5G networks with AWS Outposts. This fully managed service offers identical AWS Infrastructure, AWS services, APIs, and tools to virtually any data center, co-location space, or on-premises facility for a consistent, hybrid experience.

Corning Incorporated, one of the world's leading innovators in materials science, will reportedly be the first company to leverage the private MEC solution.

Corning already uses AWS Outposts to run computer vision software from Gestalt Robotics to enable autonomous navigation and advanced environmental sensing at its optical cable plant in Hickory, North Carolina.

The addition of Verizon’s ultra-low latency, high-throughput 5G network “will provide a powerful platform upon which Corning will innovate with applications never before possible, such as real-time analysis of large volumes of high-resolution video streams from across the factory and integration of high-data-rate automation systems,” said George Elissaios, director of product management at AWS.

Private MEC can also enable real-time monitoring of autonomous mobile robots (AMRs) that roam the factory floors, adds Elissaios.

“Full managed Private MEC can guide AMRs safely and speedily through a factory, avoiding people and obstacles while ferrying their payloads from point to point. The Private 5G network enables reliable, low-latency transmission of rich sensor data (lidar, vibration, temperature, audio) from these AMRs and other industrial devices located throughout the factory,” explained Elissaios.

Despite its many different use cases in factories, Private MEC is not limited to them. For instance, the platform can provide enhanced experiences during live concerts through augmented reality (AR), information overlays, multiple angle views, and personalized instant replays. Health care providers can also use Private MEC for real-time diagnostics over 5G for rapid access to radiological scans on-site and local processing of sensitive patient data.

“Private MEC is a natural expansion of our collaboration with Verizon,” said Dave Brown, vice president of Elastic Compute Cloud (EC2) at AWS.

“Customers are already leveraging AWS Wavelength's ability to provide ultra-low latency access to end users for use cases like video distribution, inference at the edge, AR/VR, and connected vehicles. Now, Private 5G MEC from AWS and Verizon brings ultra-low latency to dedicated, closed, on-premises environments for use cases such as autonomous mobile robots, quality assurance, and hazard alerting.”

IBM has announced that it will make its hybrid cloud available on any cloud, on-premises, or at the edge via its IBM Cloud Satellite.

Big Blue said it’s worked with Lumen Technologies to integrate its Cloud Satellite service with the Lumen edge platform to enable customers to use hybrid cloud services in edge computing environments. The firm also said it will collaborate with 65 ecosystem partners, including Cisco, Dell Technologies, and Intel, to build hybrid cloud services.

It said that IBM Cloud Satellite is now generally available to customers and can bring a secured, unifying layer of cloud services to clients across environments, regardless of where their data resides. IBM added that this technology would address critical data privacy and data sovereignty requirements.

IBM said customers using the Lumen platform and IBM Cloud Satellite would be able to deploy data-intensive applications, such as video analytics, across highly distributed environments and take advantage of infrastructure designed for single-digit millisecond latency.

The collaboration will enable customers to deploy applications across more than 180,000 connected enterprise locations on the Lumen network to provide a low latency experience. They can also create cloud-enabled solutions at the edge that leverage application management and orchestration via IBM Cloud Satellite and build open, interoperable platforms that give customers greater deployment flexibility and more seamless access to cloud-native services like artificial intelligence (AI), internet of things (IoT), and edge computing.

One example given of how this would benefit customers is using cameras to detect the last time surfaces were cleaned or flag potential worker safety concerns. Using an application hosted on Red Hat OpenShift via IBM Cloud Satellite from the proximity of a Lumen edge location, such cameras and sensors can function in near real-time to help improve quality and safety, IBM claimed.

IBM added that customers across geographies can better address data sovereignty by deploying this processing power closer to where the data is created.

“With the Lumen Platform’s broad reach, we are giving our enterprise customers access to IBM Cloud Satellite to help them drive innovation more rapidly at the edge,” said Paul Savill, SVP of enterprise product management and services at Lumen.

“Our enterprise customers can now extend IBM Cloud services across Lumen’s robust global network, enabling them to deploy data-heavy edge applications that demand high security and ultra-low latency. By bringing secure and open hybrid cloud capabilities to the edge, our customers can propel their businesses forward and take advantage of the emerging applications of the 4th Industrial Revolution.”

IBM is also extending its Watson Anywhere strategy with the availability of IBM Cloud Pak for Data as a Service with IBM Cloud Satellite. IBM said this would give customers a “flexible, secure way to run their AI and analytics workloads as services across any environment – without having to manage it themselves.”

Service partners also plan to offer migration and deployment services to help customers manage solutions as-a-service anywhere. IBM Cloud Satellite customers can also access certified software offerings on Red Hat Marketplace, which they can deploy to run on Red Hat OpenShift via IBM Cloud Satellite.

Spurred by a reliance on IT housed outside the traditional data centre and trends like edge analytics, 5G, and IOT, businesses are being pushed closer to edge computing. Through a new architecture based on interconnection and colocation in multi-tenant data centres, enterprises can regain control over their networks and improve performance while also reducing transport cost.

This strategy of private connections provides the lowest latency to the largest number of destinations as well as better reliability. This Pathfinder paper provides decision makers with an overview of the business value of adopting a hybrid IT strategy.

Download your free pdf to discover the next steps to gaining a digital advantage for your organisation.

Verizon and Unity are teaming up to develop high-speed, low-lag digital experiences ranging from entertainment applications to enterprise toolkits.

The collaboration is part of Verizon’s broader business strategy to align with enterprises, startups, universities, and the government to explore how 5G and mobile edge computing (MEC) can disrupt and transform nearly every industry.

“We are entering an era of technology-led disruption where 5G and MEC will not only transform the full enterprise lifecycle, it will change the way consumers experience gaming and entertainment,” said Tami Erwin, CEO of Verizon Business.

“Every business is accelerating the shift to digital for their employees, supply chain or end-customer experience. So whether you’re an enterprise reimaging how you do business using predictive real time insights, computer vision, machine learning and artificial intelligence, or a mobile gamer who simply wants to download the hottest new game in seconds and enjoy data intensive, multiplayer games conventionally reserved for consoles, the future is happening right now.”

As part of their partnership, the companies will combine Verizon’s 5G and MEC technology with Unity’s real-time 3D development platform to enable various high-performance 3D applications without expensive hardware. The rich 3D environments can be significant for gaming, retail, and sports industries that demand instantaneous content for consumers.

The companies will also capitalize on the faster speeds, higher bandwidth, and ultra-low latency of 5G Ultra Wideband and MEC to enable interactive 3D applications for enterprises.

Unity solutions VP Ryan Peterson adds, “We know the world is demanding high-speed, AAA content, whether it’s an educational augmented reality application or a robot running a simulation of a digital twin.”

“5G is the key piece for us to facilitate these real-time 3D experiences broadly and to better meet the demands of the real-time economy.”

IBM and Samsung have announced plans to develop open hybrid cloud solutions that enable enterprises to use 5G and edge computing to process large amounts of data from edge computing workloads.

The collaboration will combine Samsung’s Galaxy 5G mobile devices and advanced end-to-end enterprise network solutions with IBM’s network management, hybrid cloud, and edge computing offerings. It’ll also include IBM’s industry solutions that integrate artificial intelligence (AI) and Red Hat’s open architecture.

IBM and Samsung said the goal is to develop “open, hybrid cloud solutions that enable enterprises to draw greater insights from data at the edge – from the factory floor to an oil rig or a regular office space – to improve operational performance, increase worker safety, and minimize downtime.”

The companies are also looking to help enterprises use 5G in public and private networks through cross collaborations with global mobile operators. Earlier this year, Samsung announced a project with IBM, the Singapore Infocomm Media Development Authority, and telecom provider M1 to showcase Smart Factory advancements, including 5G-enabled AI analytics and AR capabilities.

Additionally, Samsung and IBM’s collaboration in private 5G networks will enable enterprises to adopt emerging technologies crucial to Industry 4.0, such as the internet of things (IoT), AI, cloud, edge computing, and augmented reality (AR). It’ll also introduce innovations across businesses that can enable employees to identify faults in manufacturing lines using AI-powered image recognition, employ thousands of sensors to build smart agriculture solutions, or facilitate employee training and productivity using AR.

As part of this collaboration, Samsung, IBM, and Red Hat plan to deliver AI-powered solutions for industry using 5G devices, cloud-native 5G networks, and edge computing platforms. Specifically, the companies intend to explore Samsung hardware and software’s interoperability and integration with IBM Edge Application Manager, which runs on Red Hat OpenShift and AI to enable computing workloads to be managed and deployed to Samsung’s portfolio of mobile devices at an industrial scale.

Steve Canepa, global GM and managing director, communications sector at IBM said the communication networks’ transition from proprietary architecture to intelligent, software-defined hybrid cloud platforms enables the creation of enormous new value in the 5G and edge era.

“5G devices and network solutions from Samsung, along with IBM and Red Hat’s open, hybrid cloud capabilities, can help organizations across all industries accelerate their transformation and solve real business problems while unlocking the true power of 5G and edge,” Canepa added.

The Dell EMC PowerEdge brand name may have first appeared way back in the mid-90s but for the XE2420, it’s never been more appropriate. This 2U rack server is, quite simply, designed to deliver some serious computing power to the network edge.

The XE2420 targets a wide range of edge computing applications including 5G adoption, retail, analytics, transport, plant automation, automotive industry in-car testing, shopping malls, VSANs, energy production and much more. It’s designed to work in harsh environments in temperatures of between 5 and 40 degrees C and its large bezel accepts an optional dust filter.

A striking feature is the short-depth chassis, which measures only 557mm with the bezel attached, allowing it to go where normal rack servers can’t. Don’t be fooled by this shortness through; the XE2420 is capable of packing a mighty specification.

It supports dual Xeon Scalable CPUs including the Cascade Lake models, while memory can be boosted to a maximum of 1TB with RDIMMs and 1.75TB using LR-DIMMs. Storage options are plentiful as well, but a key feature is its facilities for up to five PCI-E expansion slots, with GPU cards a high priority.

Dell EMC PowerEdge XE2420 review: System design

The XE2420 employs a reverse system design with all expansion slots, drive bays and network ports accessible from the front. All system cooling is handled by a bank of six high-performance hot-plug fans arranged across the rear of the chassis.

Our system was supplied with two meaty 2kW Platinum hot-plug PSUs, which are also accessed from the front and use a reverse air-flow design. The bezel is a chunky lump of steel and along with the removable dust filter in the front, it has apertures with dust brushes on each side for cable connections.

There’s a lot going on underneath the lid and Dell EMC has packed a lot of hardware into this server. You can’t miss the two reinforced GPU expansion cages, which run the full length of the chassis and have two 16X Gen 3 PCI-E slots apiece - all supporting full-height (FH), full length (FL) cards.

The motherboard lurks underneath these cages and presents dual CPU sockets accompanied by a total of 16 DIMM slots. The system on review is well-specified; the price we’ve shown includes a tasty pair of 2.7GHz 12-core Intel Xeon Scalable Gold 6226 CPUs, partnered by 192GB of 2,933MHz DDR4 memory.

Dell EMC PowerEdge XE2420 review: Storage and expansion

Dell EMC offers three versions of the XE2420 and on test we have the 1A model, which supports two SFF drives. You can opt for SATA drives, but our system has the NVMe riser card installed and includes a pair of 3.84TB NVMe SSDs.

The 2C model supplants the leftmost PCI-E riser with a second dual-drive SFF cage, while the 3A version brings EDSFF (Enterprise & Data Center SSD Form Factor) into the storage equation. Remarkably, there’s enough room inside for an EDSFF switch backplane and full-length cage, which supports six E1.L (long) SSDs allowing storage capacity to be pushed to 92TB.

Graphics options are extensive, and the server supports two x16 300W or four x8 75W passive GPU cards. The XE2420 has an upper 150W TDP threshold for CPUs but this does cover all the Bronze, Silver and Gold 5200 Gen2 models, along with a fair few Gold 6200s.

Expansion options don’t stop here - the motherboard offers an OCP slot which, although it’s the older 2.0 variety, accepts dual-port 10GbE or 25GbE mezzanine cards. A fifth PCI-E slot sits above this as the centre slot riser has an interposer board cabled to it and its slot supports a half-width, half-length card.

We also have Dell EMC’s trusty BOSS (boot optimized storage solution) card, which is tucked neatly away in a dedicated slot underneath the central drive cage. This was fitted with dual 480GB M.2 SATA SSDs in a mirrored array allowing us to run an OS without using any front bays.

Dell EMC PowerEdge XE2420 review: Remote management

The XE2420 sports a full-strength embedded iDRAC9 remote management controller, which presents a smart web interface offering a wealth of information on system and component status, power usage and cooling efficiency. Along with full hardware inventory, it provides direct access to the server’s BIOS plus storage configuration, and the Enterprise license included in the price activates OS remote console and virtual media services.

Deployment is a cinch; we just used the remote console to map a Windows Server 2019 ISO to the XE2420 as a virtual drive. We then handed this over to the Lifecycle Controller feature for installation and selected the BOSS card as the destination.

The iDRAC9 has a sharp focus on security, with a System Lockdown mode stopping users making any configuration changes, while full supply chain security is assured by cryptographically signed firmware packages. Upgrading to the Datacenter iDRAC9 license enables telemetry streaming of over 20 hardware metrics for analytics, plus thermal and airflow management and tighter access security with automatic certificate enrolment.

Sadly, the XE2420 doesn’t support the Quick Sync 2 module, which enables mobile connections over Bluetooth for walk-up diagnostics using the OpenManage Mobile (OMM) app. All is not lost though, as we could use the OMM app to access the server over the LAN, and also plug a USB cable into the small control panel at the front and connect directly to a Windows laptop for accessing the iDRAC9 web interface using the standard RNDIS driver.

Dell EMC PowerEdge XE2420 review: Verdict

You do pay a premium for its compactness, but the PowerEdge XE2420 is perfect for enterprises that want to push some serious compute and data analytics power out to the network edge. The space-efficient short-depth chassis is surprisingly expandable, it supports a high GPU density and offers a wide range of storage options including the latest high-capacity EDSFF SSDs.

Dell EMC PowerEdge XE2420 specifications

Fewer than 10% of security professionals think their organization is secure enough for the rollout of 5G, according to a new report.

The AT&T Cybersecurity report indicates that only 9% of C-suite professionals and security practitioners surveyed worldwide felt their organization’s security posture was prepared for the rollout of 5G technologies. Plus, 12.5% of respondents have low confidence in their ability to adapt to 5G.

According to the report’s authors, “the fact that fewer than 10% of respondents feel their security posture is fully prepared today is an indicator that individuals are realizing the magnitude of change that will come with 5G and edge computing.”

When it comes to securing the cellular edge of 5G, 31% of respondents thought 5G is secure out of the box from the network provider without additional security required. Another 26% have no strategic plan to address 5G’s security.

This is in direct opposition to the 56% of respondents who understand that 5G will require a change to their security approach to accommodate network changes.

In addition, nearly half of the survey respondents believe 5G poses an elevated security threat, partly because there are more vectors through which adversaries can attack.

The report’s authors said these diametrically opposing beliefs sum up the conundrum facing enterprises as they transition enterprise network architecture, including security infrastructure, to incorporate 5G.

“Nearly half of the survey respondents think 5G requires no change to their security infrastructure, while the other half understands that this shift demands a rework of the security posture to keep the business protected,” the report said.

When it came to ranking the top three 5G use cases, data privacy (32.2%) came second after improvements to IoT infrastructure (35.9%).

The report’s authors said that while network operators have designed 5G with better encryption and network slicing capabilities, “5G requires a shared security responsibility, much like that in the public cloud. Every organization must keep that in mind.”

In a separate cyber security report by Netwrix, insider risks are now more common than external threat actors. With remote working now becoming the norm, four of the top six types of cyber security incidents they experienced were caused by internal users.

Among the incidents were: admin mistakes (27%), accidental improper sharing of data by employees (26%), misconfiguration of cloud services (16%) and data theft by employees (14%). Therefore, it is not surprising that 79% of CIOs worry that users are now more likely to ignore IT policies, thus posing a greater threat to security.

The survey of found that incidents related to inside actors were among the hardest for organizations to detect. For example, a significant portion of respondents needed weeks or months to detect data theft by employees (26%), improper employee data sharing (18%) and admin mistakes (12%).

“In this age of remote work, the insider threat can’t go unaddressed. We cannot emphasize enough the importance of paying attention to how employees handle sensitive data and follow security policies. Now is the time to revisit the founding principles of security — including tracking user activity, automating change and configuration auditing, and enabling alerts on harmful actions — to ensure that insider misbehavior is detected and addressed in a timely manner,” said Ilia Sotnikov, VP of Product Management at Netwrix.

Red Hat has unveiled new edge capabilities for Red Hat Enterprise Linux. The firm has also expanded the number of supported environments for Red Hat OpenShift, including leading public clouds and multiple datacenter architectures, like IBM Z and Power Systems.

At this year’s KubeCon + CloudNativeCon, Red Hat launched several edge-focused updates to Red Hat Enterprise Linux, including the rapid creation of operating system images for the edge through the Image Builder capability.

The firm said this would enable IT organizations to create purpose-built images optimized for architectural challenges inherent to edge computing but customized for the needs of a given deployment.

Red Hat also unveiled remote device update mirroring to stage and apply updates at the next device reboot or power cycle, helping limit downtime and manual intervention from IT response teams.

The edge update sports over-the-air updates that transfer less data while still pushing necessary code. Red Hat aims this update at sites with limited or intermittent connectivity.

Another feature announced is Intelligent rollback built on OSTree capabilities, enabling users to provide workload-specific health checks to detect conflicts or code issues. When it detects a problem, it automatically reverts the image to the last good update to prevent unnecessary downtime at the edge.

Red Hat also announced updates to Red Hat OpenShift 4.6 intended to help enterprises accelerate cloud-native application development. The latest update to OpenShift Serverless with Red Hat OpenShift Serverless 1.11 brings full support for Knative eventing, enabling containerized applications to consume only the resources they need at a given time, which prevents over- or under-consumption.

There is also a Red Hat build of Quarkus, a Kubernetes-native Java stack fully supported by Red Hat. With a single Red Hat OpenShift subscription, customers now have full access to Quarkus, enabling developers to repurpose mission-critical Java applications on Kubernetes, backed by Red Hat’s enterprise support.

Red Hat OpenShift 4.6 now includes new edge computing features with remote worker nodes, extending processing power to space-constrained environments. This enables IT organizations to scale remotely while maintaining centralized operations and management.

OpenShift 4.6 will also extend capabilities for public-sector Kubernetes deployments, including availability on AWS GovCloud and Azure Government Cloud, extended OpenSCAP support and more.

Further extending OpenShift’s reach into the public cloud domain is Azure Red Hat OpenShift, a jointly-managed, engineered and supported offering on Microsoft Azure backed by Microsoft and Red Hat’s expertise. A similar service is expected to launch on AWS with joint management and support from Red Hat and Amazon.

By 2025 analyst firm Gartner predicts that three quarters of enterprise-generated data will be created and processed at the edge – meaning outside of a traditional data centre or cloud and closer to end users.

The Linux Foundation defines edge computing as the delivery of computing capabilities to the logical extremes of a network in order to improve the performance, security, operating cost and reliability of applications and services. “By shortening the distance between devices and the cloud resources that serve them, edge computing mitigates the latency and bandwidth constraints of today’s internet, ushering in new classes of applications,” the foundation explains in its Open Glossary of Edge Computing.

Edge computing has been on a large hype cycle for several years now and many consider it “the Wild West”. This is because there’s a high volume of chaotic activity in this area, resulting in duplicated efforts, as technologists all vie to find the best solutions.

“It’s early doors,” says Brian Partridge, research director at 451 Research. “Vendors and service providers are throwing stuff at the wall to see what sticks. Enterprises are experimenting, investors are making large bets. In short, the market is thrashing, crowded and there’s a lot of confusion.”

A synergy between cloud native and the edge

Edge computing opens up many possibilities for organisations looking to scale their infrastructure and support more latency-sensitive applications. As cloud native infrastructures were created to improve flexibility, scalability and reliability, many developers are looking to replicate these benefits close to the data’s source, at the edge.

“Cloud native can help organisations fully leverage edge computing by providing the same operational consistency at the edge as it does in the cloud,” notes Priyanka Sharma, general manager of the Cloud Native Computing Foundation (CNCF).

“It offers high levels of interoperability and compatibility through the use of open standards and serves as a launchpad for innovation based on the flexible nature of its container orchestration engine. It also enables remote devops teams to work faster and more efficiently,” she points out.

Benefits of using cloud native at the edge

Benefits of using cloud native at the edge include the ability to complete faster rollbacks. Therefore, edge deployments that break or have bugs can be rapidly returned to a working state, says William Fellows, co-founder and research director of 451 Research.

“We’re also seeing more granular, layered container support whereby updates are portioned into smaller chunks or targeted at limited environments and thus don’t require an entire container image update. Cloud native microservices provide an immensely flexible way of developing and delivering fine-grain service and control,” he adds.

There are also financial benefits to taking the cloud native path. The reduction in bandwidth and streamlined data that cloud native provides can reduce costs, making it an incredibly efficient tool for businesses.

“It can also allow consumption-based pricing approach to edge computing without a large upfront CapEx spend,” notes Andrew Buss, IDC research director for European enterprise infrastructure.

However, it wouldn’t be the “Wild West” out there right now if cloud native was the perfect solution. There are still several challenges still to work on, including security concerns.

“Containers are very appealing due to them being lightweight but they’re actually very bad at ‘containing’,” points out Ildikó Vancsa, ecosystem technical lead at the Open Infrastructure Foundation (formerly the OpenStack Foundation).

“This means they don’t provide the same level of isolation as virtual machines, which can lead to every container running on the same kernel being compromised. That’s unacceptable from a security perspective. We should see this as a challenge that we still need to work on, not a downside to applying cloud native principles to edge computing,” she explains.

There’s also the complexity of dealing with highly modular systems, so for those interested in moving towards cloud native edge computing, you need to prepare by investing the time and resources necessary to effectively implement it.

What should businesses be thinking about when embarking on cloud native edge computing?

Cloud native edge solutions are still relatively rare; IDC’s European Enterprise Infrastructure and Multicloud survey from May 2020 showed that the biggest edge investments are still on-premise.

“However, we expect this to shift in the coming years as cloud native edge solutions become more widely available and mature and we have more use cases that take advantage of cloud as part of their design,” says Gabriele Roberti, Research Manager for IDC's European Vertical Markets, Customer Insights and Analysis team, and Lead for IDC's European Edge Computing Launchpad.

For those businesses eager to take the leap, Partridge recommends starting with the application vision, requirements and expected outcomes. After targeting edge use cases that can support a desired business objective – such as lowering operations costs – you can then turn your attention to the system required.

Laura Foster, programme manager for tech and innovation at techUK, reiterates that it’s important to build a use case that works for your business needs.

“There’s an exciting ecosystem of service providers, innovators and collaboration networks that can help build the right path for you, but the journey towards cloud native edge computing also needs to go hand in hand with cultural change,” she points out.

“Emerging technologies, including edge computing, will pioneer innovation, but only if businesses push for change. Retraining and reskilling workforces is a fundamental part of an innovation journey and can often be the key to getting it right,” she concludes.

EDJX, a pioneering edge computing platform, has partnered with Cyxtera, a global leader in data center colocation and interconnection services, to be available through the Cyxtera Marketplace network fabric in three initial markets, Santa Clara, Californiam Dallas, Texas and Weehawken, NJ. The initial facilities will be operational by December 2020.

EDJX is building the world’s largest edge cloud in terms of total edge locations. The partnership with Cyxtera provides carrier-neutral facilities EDJX will use as metropolitan area hubs to address compute bottlenecks.

Legacy serverless and content delivery network (CDN) solutions require compute in a few points of presence, which limits the ability to speed up code and data for Internet of Thing (IoT) apps. EDJX enables the compute to be distributed to many points of presence without the same capital investment.

"Launching the world's first distributed serverless CDN platform at the edge through this partnership with a leading global data center provider means that we're able to provide customers with a solution that rivals any similar solution in the market," said John Cowan, CEO, EDJX.

EDJX’s new EdjBlock solution, ITRenew and Virtual Power Systems (VPS) will feature in the rollout across Cyxtera’s data centers. EdjBlock is a pre-integrated edge computing infrastructure that supports rapid deployment and monetization of distributed CDN and edge computing services.

The platform will feature flexible, cost-effective, rack-scale compute and storage solutions for efficient scaling and greater sustainability, as well as software-defined power control to optimize uptime and efficiency.

"Cyxtera is focused on delivering the diversity of innovative infrastructure solutions that meet the demands of today's enterprise customers," said Holland Barry, senior vice president and field CTO, Cyxtera.

"We see tremendous potential in rolling out a truly global edge computing platform in our data centers in partnership with EDJX. We believe this partnership will enable customers that require infrastructure closer to end users to deliver the kind of efficiency that can make a meaningful difference in their business performance."

EDJX will work on building out the edge sustainably. Developers will have access to a cheaper, faster service to build, launch and accelerate IoT apps.

The first 100 qualified developers can sign up for one year of free service to the public limited beta of EDJX’s CDN, DNS, Serverless, and Serverless DB services. They will also learn first about new releases, product enhancements and future discounts.

As data generation inexorably moves out to the network edge, many businesses want to follow it with systems that can process data in situ instead of pushing it all the way back to the data centre or cloud. HPE has been in the edge computing game longer than most, having launched its EdgeLine series a few years ago - although some models are already a bit long in the tooth.

The EdgeLine EL8000 ups HPE’s game, delivering a high performance edge compute solution in a compact and rugged 5U half-width chassis. Naturally, 5G adoption is a key focus for HPE but it has many other target markets for the EL8000 including retail, manufacturing, transportation, defence and energy production.

Whereas the EL1000 and EL4000 systems employ HPE’s old Moonshot Xeon D and Xeon E3 server cartridges, the EL8000 gets a brand new purpose-built server blade. It supports up to four ProLiant e910 blades, making the EL8000 one of the first solutions to deliver Xeon Scalable computing to the network edge.

HPE EdgeLine EL8000 review: Chassis design

The EL8000 is designed for harsh environments – it’s shock and vibration resistant and rated for continuous operations in temperatures between 0 and 55 degrees C. The 5U chassis can be deployed as a standalone unit or rack-mounted, where you can place two alongside each other and even a third sideways on behind them.

The four upper 1U slots each accept an e910 blade and if you want more options, you can mix them with 2U versions which double the number of PCI-E slots. All system cooling is handled efficiently by an array of nine hot-plug cooling fan modules at the rear.

Two 1,500W hot-plug PSUs slot into the lower 1U space and alongside there’s room for up to two unmanaged 10GbE switch blades. Tucked up in the lower right-hand slot is HPE’s ECM (EdgeLine chassis manager) module which provides web browser access for managing the chassis, monitoring the blades and controlling power.

HPE offers a range of casing options for the EL8000; a 19in wall-mount enclosure allows two to be placed side by side, or you can go for a shipping container so the system can be delivered and operated without unpacking it. Our review unit was supplied in a battle-hardened aluminium wheeled case and it can be protected out in the field with a rugged, water-resistant version.

HPE EdgeLine EL8000 review: The e910 blade

The ProLiant e910 server blades pack a lot into their compact dimensions, with the single Xeon Scalable CPU socket located at the rear and flanked on each side by six DIMM slots. Further forward are two PCI-E expansion slots plus a dedicated slot in the middle for an optional mezzanine card.

The blades have an embedded Gigabit port which can be accessed from the ECM, as it uses its second Gigabit maintenance network port to aggregate all four connections. More importantly, they each have an Intel X722 quad 10GbE backplane connection where two can be routed through to the unmanaged network switch blades which terminate them on a 10GbE SFP+ port.

If you install the quad 10GbE mezzanine card, its QSFP+ port is presented at the front of the blade. This doesn’t go through the switch module though, so you’ll need to use HPE’s direct-attach breakout cables to split it into four external 10GbE ports.

The blades only support M.2 SATA or NVMe SSD storage, and have two on-board 2280 slots. This can be easily trebled with a riser adapter that fits over the top of the mezzanine card and supports longer 22110 M.2 cards.

The 2U server blades are essentially the same, with the main difference being that they have an extra 1U upper unit which provides four PCI-E slots. The chassis also supports a 2U storage bay providing 8 SFF hot-swap bays plus Smart Array controller. This is available as a factory order and can only be used with one 2U e910 server blade.

HPE EdgeLine EL8000 review: System management

The blades each have an embedded iLO5 management controller with all of them piped through the ECM’s network port. It presents a smart web console packed with information about server blade status and essential details on critical components.

We did come across one glitch though; we were unable to use HPE’s Intelligent Provisioning tool to deploy Windows Server 2019. This tool expects to see a Smart Array controller and with NVMe-only storage available on our blades, it refused to proceed, requiring us to manually deploy the OS from a mapped ISO file and apply all necessary drivers.

The chassis management web interface is very informative and opens with a dashboard view of blade health status and an active graphic of the chassis with all installed components. More information is available on the blade summary page and each entry provides a direct link to their iLO5 interface.

Clicking on a blade entry takes you to its personal power controls so you can gracefully bring the blade down, reset it or recycle power. Usefully, you can select a one-time boot option without visiting the iLO5 interface.

Strong platform security extends to silicon root of trust fingerprinting for the chassis and blades so you know their firmware hasn’t been compromised. The ECM supports SSH access and maintains audit logs, while the iLO5 chip allows administrators to use SSO to manage user access to all blade features and offers four encryption levels - including the highly secure FIPS and CNSA modes.

HPE EdgeLine EL8000 review: Verdict

The EdgeLine EL8000 shows HPE is getting very serious about edge computing. This 5U system delivers a smart modular design, allowing it to be customised to suit specific scenarios and the e910 blades are amongst the first to put Xeon Scalable CPUs close to the edge.

Network options are extensive and the e910 blade design and features allow you to create a high performance solution capable of running many enterprise apps. Its rugged design allows it to go places other servers daren’t venture, and HPE offers a wide range of portable, battle-ready transport cases for ‘deliver and deploy’ services.

HPE EdgeLine EL8000 specifications

At VMworld 2020, Lumen, a provider of fiber-based networking connectivity and managed solutions, and VMware announced an enhancement to their ongoing partnership that’ll help streamline and secure edge computing.

Amid the global COVID-19 pandemic, efficient and consistent edge computing has become more of a necessity, as teams are farther from their data centers than they’ve ever been. Lumen will help businesses of all sizes by using the VMware SD-WAN by VeloCloud solution and VMware SASE Platform to integrate VMware SD-WAN,

VMware Workspace ONE and VMware Carbon Black to deliver a “Work from Anywhere” solution on its global edge infrastructure.

The aim is to, of course, reduce latency and enhance the experience on the edge. According to Shaun Andrews, Lumen chief marketing officer: “We believe customers can benefit tremendously from the combination of Lumen’s edge compute, network and IT services and VMware’s software to bring technology solutions closer, within milliseconds, of the digital interaction.

On top this, Lumen will also develop edge computing services for enterprises to create new digital services using VMware Tanzu. This advancement will allow applications to run consistently from the data center through the could and to the edge via the Lumen network.

“The combined capabilities of Lumen and VMware will empower organizations to take on the next phase of digital business,” said Rajiv Ramaswami, chief operating officer, products and cloud services at VMware.

Ramaswami continued: “We are helping customers take advantage of holistic solutions that support the people, processes, apps, and data that power business.”

Modern businesses can live and die by their ability to quickly process data, which has made edge computing a popular method for cutting down time-to-value. In this Q&A session, Scale Computing CEO Jeff Ready and IT Pro reviews and community editor Adam Shepherd explain why edge compute and HCI aren't just for oil rigs and factories, and how businesses of all sizes can take advantage of the benefits.

Adam Shepherd

Reviews and Community Editor, IT Pro

As reviews and community editor, Adam is responsible for coordinating all of the hardware and software reviews across IT Pro, Cloud Pro and Channel Pro, from laptops and smartphones, all the way up to enterprise-grade data centre servers and network management software. He also runs the IT Pro Panel, a flagship initiative which sees CIOs and tech leaders from the likes of Dominos, Oxfam and GoCompare sharing their experience and insight with the IT Pro community.

Jeff Ready

CEO, Scale Computing

Jeff is the CEO and co-founder of Scale Computing. Prior to founding Scale Computing, Jeff was co-founder and CEO of Corvigo, a Linux-based anti-spam appliance, where he oversaw the company from startup through funding to acquisition. After the acquisition, Jeff served as VP of Marketing at Tumbleweed Communications. Prior to Corvigo, Jeff was co-founder, COO and VP of Marketing at Radiate. Jeff holds a degree in Computer Science from Rose-Hulman Institute of Technology.

Lenovo’s rapidly expanding ThinkSystem family is going in new directions, as signalled by the ThinkSystem SE350 with its sharp focus on edge computing. Targeting applications such as IoT, retail, surveillance, building control plus manufacturing and distribution environments, the SE350 is presented in an ultra-compact chassis that’s built to work in rugged environments.

The 1U high chassis measures a mere 21cm wide and 38cm deep, is shock and vibration resistant and can handle ambient temperatures up to 55 degrees C. Its modest dimensions mean you can rack it, stack it, wall mount it, hang it from the ceiling or squeeze it into tight spaces and if you want to show it off, Lenovo offers a range of bookshelf stand kits that can take up to three servers.

This compactness doesn’t come at the cost of features, either; the SE350 supports a Xeon D-2100 CPU with up to 16 cores, 256GB of Lenovo’s TruDDR4 memory and a maximum of two M.2 boot drives and eight M.2 SATA or NVMe data drives. Network choices are equally good as the SE350 is offered with a range of 10GbE modules plus wireless and LTE options and is even 5G-ready.

As the SE350 is likely to be deployed in the wild, Lenovo offers fast deployment services and has implemented some smart security measures. Along with M.2 SED (self-encrypting drive) support, the system incorporates an intrusion sensor plus a customisable motion detector and if either are triggered, you can set the server to go into lockdown mode.

Lenovo ThinkSystem SE350 Edge Server review: Design and features

The SE350 is solidly built and whipping the lid off reveals a very well-designed interior. The Xeon D-2100 CPU sits to the rear on the left, is covered with a large passive heatsink and flanked on each side by two DIMM slots. Base systems start with 8GB of TruDDR4 memory, which can be boosted to 128GB using RDIMMs or 256GB with LRDIMMs.

All cooling is managed by three cold-swap dual rotor fans behind the CPU socket which provide N+1 redundancy, so the server will continue to operate if one fails. Power is handled by chunky external power distribution modules (PDMs) and you can specify either one or two with the second providing redundancy.

In front of the CPU is a bracket for the slide-out system ID tab and snuggling up alongside is Lenovo’s optional dual 11ac WiFi and LTE module. The antennae are cabled through to screw mounts at the rear for external aerials, but you won’t be able to use these if the server is mounted in the 1U or 2U rack enclosures.

The server is available with a choice of three network modules which fit in a dedicated edge slot on the main board and present their ports across the front panel. Connection options abound - the modules offer a range of copper or fibre Gigabit and 10GbE ports, along with one or two Gigabit ports for connection to the server’s embedded XCC (xClarity Controller) remote management chip.

Lenovo ThinkSystem SE350 Edge Server review: Storage and expansion

The SE350 offers a surprisingly good range of storage choices, which start with a boot adapter mounted in a dedicated slot at the rear. You can choose the single M.2 SATA enablement kit or fit the mirroring version which has two M.2 slots.

Further forward, you have a slot for a horizontal riser cage with two models available. One has 4-bay M.2 data drive adapters on both wings while another has a standard 16X PCI-E slot on the right wing. This arrangement adds a lot of storage versatility as you could have a maximum of two boot storage devices and eight data drives. Even better, both wings can support SATA or NVMe SSDs, although you can’t mix them in the same adapter.

The PCI-E slot has other possible uses, and supports a range of standard Gigabit and 10GbE network adapter cards. The SE350 can also handle graphics intensive workloads - our system was supplied with an Nvidia Tesla T4 GPU card.

Lenovo ThinkSystem SE350 Edge Server review: Deployment and management

The SE350 sports the same XCC controller as all other ThinkSystem servers, which can be accessed at boot up where it presents a provisioning manager. It provides easy access for configuring the server, updating firmware and creating RAID arrays while its automated OS deployment tool helped us install Windows Server 2019 in under 30 minutes.

The XCC’s web console presents plenty of information about critical hardware components and puts hardware inventory and firmware upgrade tools at your fingertips. The Utilization page only provides data on voltages and fan speeds, and to get the graphs on CPU, memory, I/O and system usage, you’ll need to purchase an XCC feature on demand (FoD) license.

One smart feature is the Edge Networking page where you can apply topology presets to all the network ports. These allow you to define which ones are controlled by the OS, those set for cloud uplinks, edge downlinks or clusters and whether the WiFi adapter will function as an AP or a client.

The XCC console also allows you to enable tamper and motion detection. For the latter, you choose what orientation the server is in and when triggered, decide whether it should be powered down and if BMC access should be disabled.

Lenovo ThinkSystem SE350 Edge Server review: Verdict

The high-end system Lenovo supplied to us for review shows clearly what the SE350 can do but it will set you back around $11,600. For those with more modest demands, entry-level systems start at a more affordable $1,825 and sport a 4-core 2.2GHz Xeon D-2123IT CPU with 8GB of TruDDR4.

A competitor to the SE350 is HPE’s EdgeLine range, although some of these are over four years old and support equally elderly Moonshot (anyone remember that?) server cartridges. The SE350 is clearly a significantly more powerful and versatile alternative, making it a great choice for businesses that want to easily push processing out to the network edge right where the data is being generated.

Lenovo ThinkSystem SE350 Edge Server specifications (As reviewed)

A seismic shift is coming to how businesses use communications technologies. As the roll-out of 5G accelerates, the internet and the networks it supports will transform as centralised data moves to the edge of the network, creating flexible communications systems with low latency.

The burgeoning Internet of Things (IoT) space will also influence how data processing takes place on the edge of networks. Already, 'edge data centres' are being built, delivering efficient services to end-users who are distant from the centralised data centres. Data processing on the edge of networks will expand to support developing sectors such as autonomous vehicles, for example, that need low-latency communications to ensure they function safely.

Data networks in their current form are highly hierarchical. The expansion of 5G not only delivers new hardware infrastructure, but also a shift to large-scale network function virtualisation (NFV). This is coupled with software defined networks (SDN) that can be used with ‘network slicing’, enabling businesses to divide the 5G network in specialised channels for specific use cases.

Communications services industry body TM Forum explains: “Architecturally, the evolution to 5G may not be as dramatic as some of the other transformations, but when it comes to opportunity, 5G promises to be revolutionary if communications service providers, suppliers, application developers and enterprises can figure out how to co-create, manage and participate in digital ecosystems.”

Speaking to IT Pro, Martin Garner, chief operations officer at CCS Insight, says: “The key benefit of 5G is speed and latency. By doing the initial processing of a lot of the data at the edge, decision making can be done more quickly, and at a lower cost. For example, in a processing plant, there are huge benefits from automatically detecting anomalies in real-time."

He continues: “An additional benefit comes from the option to process relevant data locally and never allow it to leave the premises. This is true for many healthcare uses, where the information is extremely sensitive for personal reasons, and also for businesses that, for example, do not want to let commercially sensitive production data leave the factory. Some industrial sites even have an ‘air gap’, with no external data connection to the machinery, to ensure that local data stays local."

Edge networks will become the fundamental foundation onto which all intensive data processing services will be built.

Computing on the edge

While edge computing offers innumerable benefits, it needs a solid mobile communications infrastructure to support it.

“A fundamental goal of 5G is to enable virtual network slicing, as fully scalable, programmable and flexible networks are the future with 5G,” says Colin Bryce, Director of Mobile Network Engineering at CommScope.

“Dividing the infrastructure into independent virtual networks enables operators to create an independent standardised layer above the control plane, from which they can deliver proprietary value-added services. Network slicing will be especially important for 5G network success, as mobile network operators seek to find effective solutions to manage spectrum while reducing costs. Virtual networks will allow for tremendous network efficiencies and provide operators.”

In its 2017 “Introduction to Network Slicing”, the GSMA said that slicing could be determined by function or behaviour. For example, in automotive one slice could be dedicated to a high bandwidth connection for delivering infotainment, while another “ultra-reliable” slice would be used for assisted driving

John Vickery, principal technology partner at BT, who explains that the edge could also be closer to home.

“In an enterprise context where business customers have large quantities of data to process such as HD video, video analytics or machine vision, these requirements can be met by deploying an 'on-premise' edge capability at their business location,” he tells IT Pro.

“This allows them to benefit from reduced backhaul costs (since they won’t need to send all their data to the core) and they also get the added benefits of low latency, reliability and data sovereignty. So, any investment in a network edge capability will also need to be balanced against growth in demand for 'on-premises' edge.”

How businesses slice up the available 5G network to fuel their needs and how edge computing will factor into their infrastructures remains to be seen. What is clear for all enterprises is the edge offer massive potential to finally use data processing and communications to deliver world-class services.

New data ecosystems

While edge computing using 5G may be something of an emerging technology trend, there are already a number of practical applications and use cases to consider.

In a recent research paper, Julian Bright, senior analyst at Ovum, said: “The incentive for edge computing to be deployed in 5G networks appears to be growing, and it is becoming increasingly important to the 5G business case. The first commercial deployments appear likely to start in 2020 in markets such as South Korea and China with others following soon after. Above all, MEC [Multi-access edge computing] can become a reality, particularly as more commercial 5G deployments begin to appear, services start to bed in, and yet more use cases start to emerge.”

As the infrastructure begins to develop as 5G rolls out, all eyes will turn to the costs of deployment and ongoing development. It’s clear that there is a data and communications imperative no business can ignore.

In 2019, Barclays Bank conducted a study looking at the benefits and impacts 5G could have on businesses. It found that currently 59% of companies operate across disparate locations and need to communicate in real-time, 49% need to communicate with customers and fill customer orders online, 48% have to connect multiple machines together to run their business, and 43% say that customers expect it.

The report’s authors said that in light of these findings, “it’s obvious that 5G’s projected increase in speed and reliability will greatly benefit british firms. However, factor in the forecasts for future demand for mobile internet, particularly in the context of IoT and issues such as connecting multiple devices and customer expectations leap to the fore”.

This multi-channel approach is how 5G and edge computing services will be built. Once the new communications ecosystem begins to come into focus, more use cases will develop. It’s a heady time, as businesses can see the first signs of the shackles coming off their communications services. The edge could finally deliver the quantum leap in network design and management they have been waiting for.