Schneider Electric, the trailblazer in energy management and automation, is teaming up with NVIDIA to redefine the landscape of data centre infrastructure. Their mission? To supercharge the capabilities of edge artificial intelligence (AI) and digital twin technologies, paving the way for a future powered by unparalleled innovation.
Picture this: cutting-edge data centre reference designs, meticulously crafted to harness the full potential of NVIDIA’s accelerated computing clusters. With a laser focus on high-power distribution, liquid-cooling systems, and controls engineered for reliability, they’re setting new benchmarks for performance, scalability, and sustainability.
Natalya Makarochkina, Senior Vice President of Secure Power International at Schneider Electric, is exhilarated about the possibilities: “Our collaboration with NVIDIA isn’t just about breaking barriers; it’s about unlocking the boundless potential of AI. Together, we’re dismantling the constraints of traditional data centre infrastructure, propelling us towards a future that’s efficient, sustainable, and transformative.”
But that’s only the beginning. These reference designs aren’t static blueprints; they’re dynamic frameworks designed to evolve alongside the ever-changing landscape of AI. Ian Buck, Vice President of Hyperscale and HPC at NVIDIA, shares the excitement: “With Schneider Electric, we’re not just building data centres; we’re building gateways to innovation. These designs empower organizations to harness the full power of AI, driving unprecedented levels of innovation across industries.”
Looking ahead, Schneider Electric and NVIDIA are on a relentless quest to explore new frontiers in AI-driven technology. And they’re not alone in this journey. AVEVA, Schneider Electric’s visionary subsidiary, is poised to revolutionize virtual simulation and collaboration with its integration of NVIDIA Omniverse. Together, they’re creating a digital playground where imagination knows no bounds.
Caspar Herzberg, CEO of AVEVA, envisions a future where digital intelligence and real-world outcomes converge: “This partnership isn’t just about simulation; it’s about transformation. By merging digital intelligence with real-world applications, we’re redefining the possibilities of industry, empowering organizations to operate safer, smarter, and more sustainably than ever before.”
In a world propelled by innovation, Schneider Electric and NVIDIA are at the forefront of change. Together, they’re not just building data centres; they’re building bridges to the future. And with every breakthrough, they’re inspiring a new generation of pioneers to dream bigger, aim higher, and push the boundaries of what’s possible.
This article is contributed by Francis Chow, Vice President and General Manager, In-Vehicle Operating System and Edge, Red Hat
Organizations across the globe are deploying new services, generating massive amounts of data at the edge. With this explosion of data, companies are looking for ways to make real-time decisions where this data is being generated – this is where edge computing comes in. Whether it be massive amounts of data, clusters and nodes or disconnected and connected applications in hard-to-reach locations (or all of the above), edge computing can help companies create more intelligent devices, providing innovative ways to stand out in competitive and quickly evolving marketplaces.
Scalability, low latency, more bandwidth, enhanced security, standardization and reusability – these are benefits every organization wants in their infrastructure. But how can they get there? How do they use the IT and OT human and physical resources they currently have to make this happen? Companies are partnering with software companies like Red Hat to provide the infrastructure, support, services and solutions from the far edge to the cloud and back. Red Hat believes in open source solutions at the edge. Adopting open source technologies at the edge helps minimize vendor lock-in, facilitating standards-based integration and means anyone can inspect, modify or enhance, unlike proprietary software that is limited to specific users. From device endpoints to gateways to edge servers to on-premise data centres to the cloud, open source solutions can help drive collaboration and standardization across industries so that everyone can benefit from better products and faster innovation.
In the early stages of edge computing, Red Hat worked with service providers like Verizon to successfully use open source solutions at the edge to transform networks. Verizon built its 5G core network on a modern cloud platform because Red Hat has the capabilities for critical infrastructure with extremely high availability, security and performance requirements within our open source technologies. Red Hat then helped Verizon roll out this same platform to the edge to host 5G RAN base stations at the edge, achieving a homogeneous platform with a leg up in operational efficiency. Verizon is driving 5G into its network to offer its intelligent Edge Network (iEN) and Network as a Service (NaaS) strategy aiming to make its network the most intelligent, adaptive and service-aware network available.
Another example is automotive and software-defined vehicles. With software-defined vehicles, computing at the edge is critical as most of the computing workload is in the vehicle itself. We’re working with key players in the automotive industry to help them embrace new and innovative solutions that can keep up with the pace of change and overcome limitations that have created barriers to adopting new technologies, despite their efforts in standardization and reusability.
Two years ago, we announced that we were investing in the automotive market to build a functional-safety certified Linux operating system. Since then, we’ve started working with companies like Luxoft, Qualcomm Technologies, Inc. and General Motors to help advance software-defined vehicles at the edge. Red Hat and GM are continuing to work together to develop next-generation platforms for GM’s software-defined vehicles, while also creating a methodology to build high-quality and functionally safe platforms and applications. The goal of this collaboration is to establish best practices that promote the adoption of new technologies and ensure interoperability across different vehicles and systems, making the automotive community more accessible for all, including developers. Today, Red Hat announced the next step in this important work with a collaboration with ETAS, a subsidiary of Bosch, to provide a more scalable platform to help accelerate software-defined vehicle transformation. As a result of this collaboration, automakers can benefit from a tightly integrated, reliable and scalable platform for developing, testing and deploying advanced driver assistance systems and automated driving applications on software-defined vehicles.
As our ecosystem work shows, Red Hat is committed to helping our customers with their biggest challenges and it’s clear to see that open source is the new normal at the edge, whatever the use case. Whether it be concerns about security at the edge, flexibility at scale, management, integration and complexity, Red Hat can provide the best open source infrastructure software as they move to the edge.
Put simply, edge computing is computing that takes place at or near the physical location of either the user or the source of the data being processed, such as a device or sensor.
By placing computing services closer to these locations, users benefit from faster, more reliable services and organizations benefit from the flexibility and agility of the open hybrid cloud.
Challenges in Edge Computing
With the proliferation of devices and services at edge sites, however, there is an increasing amount to manage outside the sphere of traditional operations. Platforms are being extended well beyond the data- centre, devices are multiplying and spreading across vast areas, and on-demand applications and services are running in significantly different and distant locations.
This evolving IT landscape is posing new challenges for organizations, including:
Ensuring they have the skills to address evolving edge infrastructure requirements.
Building capabilities that can react with minimal human interaction in a more secure and trusted way.
Effectively scaling at the edge with an ever-increasing number of devices and endpoints to consider.
Of course, while there are difficult challenges to overcome, many of them can be mitigated with edge automation.
Benefits of Edge Automation
Automating operations at the edge can reduce much of the complexity that comes from extending hybrid cloud infrastructure so you are better able to take advantage of the benefits edge computing provides.
Edge automation can help your organization:
Increase scalability by applying configurations more consistently across your infrastructure and managing edge devices more efficiently.
Boost agility by adapting to changing customer demands and using edge resources only as needed.
Focus on remote operational security and safety by running updates, patches and required maintenance automatically without sending a technician to the site.
Reduce downtime by simplifying network management and reducing the chance of human error.
Improve efficiency by increasing performance with automated analysis, monitoring and alerting.
7 Examples of Edge Automation
Here are some industry-specific use cases and examples demonstrating edge automation’s value.
1. Transportation industry
By automating complex manual device configuration processes, transportation companies can efficiently deploy software and application updates to trains, aeroplanes and other moving vehicles with significantly less human intervention. This can save time and help eliminate manual configuration errors, freeing teams to work on more strategic, innovative and valuable projects.
Compared to a manual approach, automating device installation and management is generally safer and more reliable.
2. Retail
Establishing a new retail store and getting its digital services online can be complex, involving configuration management of networked devices, configuration auditing and setting up computing resources across the retail facility. And once a store is set up and open to the public, the IT focus shifts from speed and scale to consistency and reliability.
Edge automation gives retail stores the ability to stand up and maintain new devices more quickly and consistently while reducing manual configuration and update errors.
3. Industry 4.0
From oil and gas refineries to smart factories to supply chains, Industry 4.0 is seeing the integration of technologies such as the internet of things (IoT), cloud computing, analytics and artificial intelligence/machine learning (AI/ML) into industrial production facilities and across operations.
One example of the value of edge automation in Industry 4.0 can be found on the manufacturing floor. There, supported by visualization algorithms, edge automation can help detect defects in manufactured components on the assembly line. It can also help improve the safety of factory operations by identifying and alerting hazardous conditions or unpermitted actions.
4. Telecommunications, media and entertainment
The advantages edge automation can provide to service providers are numerous and include clear improvements to customer experience.
For example, edge automation can turn the data edge devices produce into valuable insights that can be used to improve customer experience, such as automatically resolving connectivity issues.
The delivery of new services can also be streamlined with edge automation. Service providers can send a device to a customer’s home or office that they can simply plug in and run, without the need for a technician on site. Automating service delivery not only improves the customer experience, it creates a more efficient network maintenance process, with the potential of reducing costs.
5. Financial services and insurance
Customers are demanding more personalized financial services and tools that can be accessed from virtually anywhere, including from customers’ mobile devices.
For example, if a bank launches a self-service tool to help their customers find the right offering — such as a new insurance package, a mortgage, or a credit card — edge automation can help that bank scale the new service while also automatically meeting strict industry security standards without impacting the customer experience.
Edge automation can help provide the speed and access that customers want, with the reliability and scalability that financial service providers need.
6. Smart cities
To improve services while increasing efficiency, many municipalities are incorporating edge technologies such as IoT and AI/ML to monitor and respond to issues affecting public safety, citizen satisfaction and environmental sustainability.
Early smart city projects were constrained by the technology of the time, but the rollout of 5G networks (and new communications technologies still to come) not only increase data speeds but also makes it possible to connect more devices. To scale capabilities more effectively, smart cities need to automate edge operations, including data collection, processing, monitoring and alerting.
7. Healthcare
Healthcare has long since started to move away from hospitals toward remote care treatment options such as outpatient centres, clinics and freestanding emergency rooms, and technologies have evolved and proliferated to support these new environments. Clinical decision-making can also be improved and personalized based on patient data generated from wearables and a variety of other medical devices.
Using automation, edge computing and analytics, clinicians can efficiently convert this flood of new data into valuable insights to help improve patient outcomes while delivering both financial and operational value.
Red Hat Edge
Modern compute platforms powered by Red Hat Edge can help organizations extend their open hybrid cloud to the edge. Red Hat Edge represents Red Hat’s collective drive to integrate edge computing across the open hybrid cloud. Red Hat’s large and growing ecosystem of partners and open methodologies give organizations the flexibility they need to build platforms that can respond to rapidly changing market conditions and create differentiated offerings.
As the amount of connected “things” — vehicles, devices, equipment, sensors — proliferate, organisations continue to look for ways to securely harness the data those things generate. An entire ecosystem dedicated to collecting and analysing that data has erupted, and it’s taking data infrastructures to the edge of their capabilities.
Edge computing represents a vast opportunity for IT organisations if implemented well. Unfortunately, the data centre infrastructure required to host edge computing implementations is a patchwork affair. Today, organisations must leverage centralised data warehouses, regional edge data centres and local edge micro data centres.
Tech Research Asia (TRA) revealed in 2020 that organisations in Malaysia who has deployed edge computing were able to lower their costs in IT and operations, resulting in an overall improvement in employee experiences. However, most local organisations still find edge computing a fairly new concept. How can local organisations effectively tap into the full potential of Edge computing?
With so many geographically dispersed locations without on-site IT staff and often limited in-house resources, many organisations are turning to managed services providers to help deploy, monitor, and maintain their edge data centres. Still others, such as existing managed service providers and IT solutions providers, are expanding their services portfolio to help clients with the edge. This represents a vast opportunity for IT solution providers.
Managed services providers enable end-users to focus on core competencies
Edge locations need the same resilience, security, and fault tolerance as centralised locations, especially as they support more and more mission-critical applications. Managed service providers with the right capabilities offer peace of mind and operational efficiencies for edge deployments.
Ensuring the necessary resilience and availability at the edge is not a simple matter. It requires having at least two major capabilities in place:
Remote monitoring and management of UPS and physical infrastructure
Data collection and analytics from monitoring equipment. This data improves the reliability and cost-effectiveness of assets at the edge.
These highly specific capabilities are not the core competencies of most companies. They don’t even cover all the expertise and manpower necessary to maintain support infrastructure. Turning to a managed services provider places the responsibility for infrastructure uptime into the hands of experts so end users can focus on the core of their business.
Managed services boost revenues for existing providers
An increased need for managed services also represents an opportunity for existing providers. For example, power protection at the edge is not something many end-users consider. But an unmanned edge computing deployment without power is just another cost centre. For existing services providers, adding power monitoring and protection to their portfolio of offerings invites additional recurring revenue streams.
The story is the same for monitoring and dispatch services. When physical infrastructure in remote locations goes down, those sites need immediate attention. Most organisations don’t have a full-time response staff for such incidents, opening the door to managed services providers. Solutions and services providers can earn additional business by offering remote monitoring or dispatch services.
Managed services keep the edge ecosystem running smoothly
Edge computing has come a long way despite still having challenges to overcome. There are still operational issues to be considered in order for organisations to effectively ensure edge of network availability during this proliferation. The global health crisis too played a role in the impact of data centre downtime, making the availability of data centres, at the core and at the edge, a key concern for organisations.
Maintaining availability is challenging, given edge data centres experience more frequent total facility outages than their centralised counterparts. The primary methods companies leverage to improve edge availability — investing in improved equipment and redundant equipment — are not cost-effective ways of ensuring uptime.
It’s clear that the growing edge ecosystem represents a two-pronged opportunity for managed services. End users can turn to managed services providers for cost-effective uptime of their edge deployments, and existing providers can work with partners to add new services to their portfolios.
Regardless of where companies fall in the spectrum of offered services, the first step is to cultivate true partnerships. A typical service provider contract lasts three years. Customers must feel at ease knowing that the contract brings them the latest offerings, keeps equipment in optimal condition, and prepares them for uncertainties and surprises.
The edge is the present and future of infrastructure investments. Appropriate managed services can keep the ecosystem running smoothly for all parties involved.
From telecommunications networks to the manufacturing floor, through financial services to autonomous vehicles and beyond, computers are everywhere these days, generating a growing tsunami of data that needs to be captured, stored, processed and analyzed.
At Red Hat, we see edge computing as an opportunity to extend the open hybrid cloud all the way to data sources and end-users. Where data has traditionally lived in the data centre or cloud, there are benefits and innovations that can be realized by processing the data these devices generate closer to where it is produced.
This is where edge computing comes in.
4 benefits of edge computing
As the number of computing devices has grown, our networks simply haven’t kept pace with the demand, causing applications to be slower and/or more expensive to host centrally.
Pushing computing out to the edge helps reduce many of the issues and costs related to network latency and bandwidth, while also enabling new types of applications that were previously impractical or impossible.
1. Improve performance
When applications and data are hosted on centralized data centres and accessed via the internet, speed and performance can suffer from slow network connections. By moving things out to the edge, network-related performance and availability issues are reduced, although not entirely eliminated.
2. Place applications where they make the most sense
By processing data closer to where it’s generated, insights can be gained more quickly and response times reduced drastically. This is particularly true for locations that may have intermittent connectivity, including geographically remote offices and on vehicles such as ships, trains and aeroplanes.
Source: Pixabay
3. Simplify meeting regulatory and compliance requirements
Different situations and locations often have different privacy, data residency, and localization requirements, which can be extremely complicated to manage through centralized data processing and storage, such as in data centres or the cloud.
With edge computing, however, data can be collected, stored, processed, managed and even scrubbed in place, making it much easier to meet different locales’ regulatory and compliance requirements. For example, edge computing can be used to strip personally identifiable information (PII) or faces from a video before being sent back to the data centre.
4. Enable AI/ML applications
Artificial intelligence and machine learning (AI/ML) are growing in importance and popularity since computers are often able to respond to rapidly changing situations much more quickly and accurately than humans.
But AI/ML applications often require processing, analyzing and responding to enormous quantities of data which can’t reasonably be achieved with centralized processing due to network latency and bandwidth issues. Edge computing allows AI/ML applications to be deployed close to where data is collected so analytical results can be obtained in near real-time.
3 Edge Computing Scenarios
Red Hat focuses on three general edge computing scenarios, although these often overlap in each unique edge implementation.
1. Enterprise edge
Enterprise edge scenarios feature an enterprise data store at the core, in a data centre or as a cloud service. The enterprise edge allows organizations to extend their application services to remote locations.
Chain retailers are increasingly using an enterprise edge strategy to offer new services, improve in-store experiences and keep operations running smoothly. Individual stores aren’t equipped with large amounts of computing power, so it makes sense to centralize data storage while extending a uniform app environment out to each store.
2. Operations edge
Operations edge scenarios concern industrial edge devices, with significant involvement from operational technology (OT) teams. The operations edge is a place to gather, process and act on data on-site.
Operations edge computing is helping some manufacturers harness artificial intelligence and machine learning (AI/ML) to solve operational and business efficiency issues through real-time analysis of data provided by Industrial Internet of Things (IIoT) sensors on the factory floor.
3. Provider edge
Provider edge scenarios involve both building out networks and offering services delivered with them, as in the case of a telecommunications company. The service provider edge supports reliability, low latency and high performance with computing environments close to customers and devices.
Service providers such as Verizon are updating their networks to be more efficient and reduce latency as 5G networks spread around the world. Many of these changes are invisible to mobile users, but allow providers to add more capacity quickly while reducing costs.
3 edge computing examples
Red Hat has worked with a number of organizations to develop edge computing solutions across a variety of industries, including healthcare, space and city management.
1. Healthcare
Clinical decision-making is being transformed through intelligent healthcare analytics enabled by edge computing. By processing real-time data from medical sensors and wearable devices, AI/ML systems are aiding in the early detection of a variety of conditions, such as sepsis and skin cancers.
NASA has begun adopting edge computing to process data close to where it’s generated in space rather than sending it back to Earth, which can take minutes to days to arrive.
As an example, mission specialists on the International Space Station (ISS) are studying microbial DNA. Transmitting that data to Earth for analysis would take weeks, so they’re experimenting with doing those analyses onboard the ISS, speeding “time to insight” from months to minutes.
3. Smart cities
City governments are beginning to experiment with edge computing as well, incorporating emerging technologies such as the Internet of Things (IoT) along with AI/ML to quickly identify and remediate problems impacting public safety, citizen satisfaction and environmental sustainability.
Red Hat’s approach to edge computing
Of course, the many benefits of edge computing come with some additional complexity in terms of scale, interoperability and manageability.
Edge deployments often extend to a large number of locations that have minimal (or no) IT staff, or that vary in physical and environmental conditions. Edge stacks also often mix and match a combination of hardware and software elements from different vendors, and highly distributed edge architectures can become difficult to manage as infrastructure scales out to hundreds or even thousands of locations. The Red Hat Edge portfolio addresses these challenges by helping organizations standardize on a modern hybrid cloud infrastructure, providing an interoperable, scalable and modern edge computing platform that combines the flexibility and extensibility of open source with the power of a rapidly growing partner ecosystem
We are living in a do-anything-from-anywhere economy enabled by an exponentially expanding data ecosystem. It’s estimated 65% of Global GDP will be digitalnext year (2022). This influx of data presents both opportunities and challenges. After all, success in our digital present and future relies on our ability to secure and maintain increasingly complex IT systems. Here I’ll examine both near-term and long-term predictions that address the way the IT industry will deliver the platforms and capabilities to harness this data to transform our experiences at work, home and in the classroom.
What to look for in 2022:
The Edge discussion will separate into two focus areas – edge platforms that provide a stable pool of secure capacity for the diverse edge ecosystems and software defined edge workloads/software stacks that extend application and data systems into real world environments. This approach to Edge, where we separate the edge platforms from the edge workloads, is critical since, if each edge workload creates its own dedicated platform, we will have proliferation of edge infrastructure and unmanageable infrastructure sprawl.
Imagine an edge environment where you deploy an edge platform that presents compute, storage, I/O and other foundational IT capacities in a stable, secure, and operationally simple way. As you extend various public and private cloud data and applications pipelines to the edge along with local IoT and data management edges, they can be delivered as software-defined packages leveraging that common edge platform of IT capacity. This means that your edge workloads can evolve and change at software speed because the underlying platform is a common pool of stable capacity.
We are already seeing this shift today. Dell Technologies currently offers edge platforms for all the major cloud stacks, using common hardware and delivery mechanisms. As we move into 2022, we expect these platforms to become more capable and pervasive. We are already seeing most edge workloads – and even most public cloud edge architectures – shift to software-defined architectures using containerisation and assuming standard availably of capacities such as Kubernetes as the dial tone. This combination of modern edge platforms and software-defined edge systems will become the dominant way to build and deploy edge systems in the multi-cloud world.
The opening of the private mobility ecosystem will accelerate with more cloud and IT industries involved on the path to 5G. Enterprise use of 5G is still early. In fact, today 5G is not significantly different or better than WiFi in most enterprise use cases. This will change in 2022 as more modern, capable versions of 5G become available to enterprises. We will see higher performance and more scalable 5G along with new 5G features such as Ultra Reliability Low Latency Communications (UR-LLC) and Massive Machine Type Communicators (mMTC), with dialogue becoming much more dominant than traditional telecoms (think: open-source ecosystem, infrastructure companies, non-traditional telecom).
More importantly we expect the ecosystem, delivering new and more capable private mobility, will expand to include IT providers such as Dell Technologies but also public cloud providers and even new Open-Source ecosystems focused on acceleration of the Open 5G ecosystem.
Edge will become the new battleground for data management as data management becomes a new class of workload. The data management ecosystem needs an edge. The modern data management industry began its journey on public clouds processing and analysing non-real-time centralised data. As the digital transformation of the world accelerates, it has become clear that most of the data in the world will be created and acted on outside of centralised data centers. We expect that the entire data management ecosystem will become very active in developing and utilising edge IT capacity as the ingress and egress of their data pipelines but will also utilise edges to remotely process and digest data.
As the data management ecosystem extends to the edge this will dramatically increase the number of edge workloads and overall edge demand. This correlates to our first prediction on edge platforms as we expect these data management edges to be modern software-defined offerings. Data management and the edge will increasingly converge and reinforce each other. IT infrastructure companies, like Dell Technologies, have the unique opportunity to provide the orchestration layer for edge and multi-cloud by delivering an edge data management strategy.
The security industry is now moving from discussion of emerging security concerns to a bias toward action. Enterprises and governments are facing threats of greater sophistication and impact on revenue and services. At the same time, the attack surface that hackers can exploit is growing based on the accelerated trend in remote work and digital transformation. As a result, the security industry is responding with greater automation and integration. The industry is also pivoting from automated detection to prevention and response with a focus on applying AI and machine learning to speed remediation. This is evidenced by industry initiatives like SOAR (Security Orchestration Automation & Response), CSPM (Cloud Security Posture Management) and XDR (Extended, Detection and Response). Most importantly we are seeing new efforts such as the Open Secure Software Foundation in the Linux Foundation ramp up the coordination and active involvement of the IT, telecom and semiconductor industries.
Across all four of these areas – edge, private mobility, data management and security – there is a clear need for a broad ecosystem where both public cloud and traditional infrastructure are integrated. We are now clearly in a multi-cloud, distributed world where the big challenges can no longer be solved by a single data center, cloud, system or technology.
What to look for beyond 2022:
Quantum Computing – Hybrid quantum/classical compute will take center stage providing greater access to quantum.In 2022 we expect two major industry consensuses to emerge. First, we expect the industry will see the inevitable topology of a quantum system will be a hybrid quantum computer where the quantum hardware or quantum processing units (QPU) are specialised compute systems that look like accelerators and focus on specific quantum focused mathematics and functions. The QPUs will be surrounded by conventional compute systems to pre-process the data, run the overall process and even interpret the output of the QPUs.
Early real-world quantum systems are all following this hybrid quantum model and we see a clear path where the collaboration of classical and quantum compute is inevitable. The second major consensus is that quantum simulation using conventional computing will be the most cost effective and accessible way to get quantum systems into the hands of our universities, data science teams and researchers. In fact, Dell and IBM already announced significant work in making quantum simulation available to the world.
Automotive – The automotive ecosystem will rapidly shift focus from a mechanical ecosystem to a data and compute industry.The automotive industry is transforming at several levels. We are seeing a shift from Internal Combustion Engines to Electrified Vehicles resulting in radical simplification of the physical supply chain. We are also seeing a significant expansion of software and compute content within our automobiles via ADAS and autonomous vehicle efforts. Finally, we are seeing the automotive industry becoming data driven industries for everything from entertainment, to safety to major disruptions such as Car-as-a-Service and automated delivery.
All of this says that the automotive and transportation industries are beginning a rapid transition to be driven by software, compute and data. We have seen this in other industries such as telecom and retail and in every case the result is increased consumption of IT technology. Dell is actively engaged with most of the world’s major automotive companies in their early efforts, and we expect 2022 to continue their evolution towards digital transformation and deep interaction with IT ecosystems.
Digital Twins – Digital Twins will become easier to create and consume as the technology is more clearly defined with dedicated tools. While gaining in awareness, digital twins is still a nascent technology with few real examples in production. Over the next several years, we’ll see digital twins become easier to create and consume as we define standardised frameworks, solutions and platforms. Making digital twin ideas more accessible will enable enterprises to provide enhanced analytics and predictive models to accelerate digital transformation efforts. Digital twin adoption will become more mainstream with accelerated standardisation and availability of solutions and framework, bringing deployment and investment costs down. Digital twins will be the core driver of Digital transformation 3.0 combining measured and modeled/simulated worlds for direct business value across industry verticals.
As a technology optimist, I increasingly see a world where humans and technology work together to deliver impactful outcomes at an unprecedented speed. These near-term and long-term perspectives are based on the strides we’re making today. If we see even incremental improvement, there is enormous opportunity to positively transform the way we work, live and learn and 2022 will be another year of accelerated technology innovation and adoption.
While many aspects of edge computing are not new, the overall picture continues to evolve quickly. For example, “edge computing” encompasses the distributed retail store branch systems that have been around for decades. The term has also swallowed all manner of local factory floor and telecommunications provider computing systems, albeit in a more connected and less proprietary fashion than was the historical norm.
However, even if we see echoes of older architectures in certain edge computing deployments, we also see developing edge trends that are genuinely new or at least quite different from what existed previously. These trends are helping IT and business leaders solve problems in industries ranging from telco to automotive, for example, as both sensor data and machine learning data proliferates.
Edge computing trends that should be on your radar
Here, edge experts explore six trends that IT and business leaders should focus on in 2022:
1. Edge workloads get fatter
One big change we are seeing is that there is more computing and more storage out on the edge. Decentralized systems have often existed more to reduce reliance on network links than to perform tasks that could not practically be done in a central location assuming reasonably reliable communications. But, that is changing.
IoT has always involved at least collecting data almost by definition. However, what could be a trickle has now turned into a flood as the data required for machine learning (ML) applications flows in from a multitude of sensors. But, even if training models are often developed in a centralized data centre, the ongoing application of those models is usually pushed out to the edge of the network. This limits network bandwidth requirements and allows for rapid local action, such as shutting down a machine in response to anomalous sensor readings. The goal is to deliver insights and take action at the moment they’re needed.
2. RISC-V gains ground
Of course, workloads that are both data- and compute-intensive need hardware on which to run. The specifics vary depending upon the application and the tradeoffs required between performance, power, cost, and so forth. Traditionally the choice has usually come down to either something custom, ARM, or x86. None are fully open, although ARM and x86 have developed a large ecosystem of supporting hardware and software over time, largely driven by the lead processor component designers.
But RISC-V is a new and intriguing open hardware-based instruction set architecture.
Why intriguing? Here’s how Red Hat Global Emerging Technology Evangelist Yan Fisher puts it: “The unique aspect of RISC-V is that its design process and the specification are truly open. The design reflects the community’s decisions based on collective experience and research.”
This open approach, and an active ecosystem to go along with it, is already helping to drive RISC-V design wins across a broad range of industries. Calista Redmond, CEO of RISC-V International, observes that: “With the shift to edge computing, we are seeing a massive investment in RISC-V across the ecosystem, from multinational companies like Alibaba, Andes Technology, and NXP to startups like SiFive, Esperanto Technologies, and GreenWaves Technologies designing innovative edge-AI RISC-V solutions.”
3. Virtual Radio Access Networks (vRAN) become an increasingly important edge use case
A radio access network is responsible for enabling and connecting devices such as smartphones or internet of things (IoT) devices to a mobile network. As part of 5G deployments, carriers are shifting to a more flexible vRAN approach whereby the high-level logical RAN components are disaggregated by decoupling hardware and software, as well as using cloud technology for automated deployment and scaling and workload placement.
Hanen Garcia, Red Hat Telco Solutions Manager, and Ishu Verma, Red Hat Emerging Technology Evangelist, note that “One study indicates deployment of virtual RAN (vRAN)/Open RAN (oRAN) solutions realize network TCO savings of up to 44% compared to traditional distributed/centralized RAN configurations.” They add that: “Through this modernization, communications service providers (CSPs) can simplify network operations and improve flexibility, availability, and efficiency—all while serving an increasing number of use cases. Cloud-native and container-based RAN solutions provide lower costs, improved ease of upgrades and modifications, ability to scale horizontally, and with less vendor lock-in than proprietary or VM-based solutions.”
4. Scale drives operational approaches
Many aspects of an edge-computing architecture can be different from one that’s implemented solely within the walls of a data centre. Devices and computers may have weak physical security and no IT staff on-site. Network connectivity may be unreliable. Good bandwidth and low latencies aren’t a given. But many of the most pressing challenges relate to scale; there may be thousands (or more) network endpoints.
Kris Murphy, Senior Principal Software Engineer at Red Hat, identifies four primary steps you must take in order to deal with scale: “Standardize ruthlessly, minimize operational ‘surface area,’ pull whenever possible over push, and automate the small things.”
For example, she recommends doing transactional, which is to say atomic, updates so that a system can’t end up only partially updated and therefore in an ill-defined state. When updating, she also argues that it’s a good practice for endpoints to pull updates because “egress connectivity is more likely available.” One should also take care to limit peak loads by not doing all updates at the same time.
5. Edge computing needs attestation
With resources at the edge tight, capabilities that require little to no local resources are the pragmatic options to consider. Furthermore, any approach needs to be highly scalable or otherwise, the uses and benefits become extremely limited. One option that stands out is the Keylime project. “Technologies like Keylime, which can verify that computing devices boot up and remain in a trusted state of operation at scale should be considered for broad deployment, especially for resource-constrained environments” as described by Ben Fischer, Red Hat Emerging Technology Evangelist.
Keylime provides remote boot and runtime attestation using Integrity Measurement Architecture (IMA) and leverages Trusted Platform Modules (TPMs) which are common to most laptop, desktop, and server motherboards. If no hardware TPM is available, a virtual, or vTPM, can be loaded to provide the requisite TPM functionality. Boot and runtime attestation is a means to verify that the edge device boots to a known trusted state and maintains that state while running. In other words, if something unexpected happens, such as a rogue process, the expected state would change, which would be reflected in the measurement and would take the edge device offline, because it entered an untrusted state. This device could be investigated and remediated and put back into service again in a trusted state.
6. Confidential Computing becomes more important at the edge
Security at the edge requires broad preparation. Availability of resources, such as network connectivity, electricity, staff, equipment, and functionality vary widely but are far less than what would be available in a data centre. These limited resources limit the capabilities for ensuring availability and security. Besides encrypting local storage and connections to more centralized systems, confidential computing offers the ability to encrypt data while it is in use by the edge computing device.
This protects both the data being processed and the software processing the data from being captured or manipulated. Fischer argues that “confidential computing on edge computing devices will become a foundational security technology for computing at the edge, due to the limited edge resources.”
According to the Confidential Computing Consortium’s (CCC) report by the Everest group, Confidential Computing – The Next Frontier in Data Security, “Confidential computing in a distributed edge network can also help realize new efficiencies without affecting data or IP privacy by building a secure foundation to scale analytics at the edge without compromising data security.” Additionally, confidential computing “ensures only authorized commands and code are executed by edge and IoT devices. Use of confidential computing at the IoT and edge devices and back end helps control critical infrastructure by preventing tampering with code of data being communicated across interfaces.“
Confidential computing applications at the edge range from autonomous vehicles to collecting sensitive information.
Diverse applications across industries
The diversity of these edge computing trends reflects both the diversity and scale of edge workloads. There are some common threads – multiple physical footprints, the use of cloud-native and container technologies, an increasing use of machine learning. However, telco applications often have little in common with industrial IoT use cases, which in turn differ from those in the automotive industry. But whatever industry you look at, you’ll find interesting things happening at the edge in 2022.
Edge computing is the ability to give life to the transformative use cases that businesses are dreaming up today and bring real-time decision making to last-mile locales. This can include a far-flung factory or train roaring down the tracks, someone’s connected home, or their car speeding down the highway or even in space. Who thought we’d be running Kubernetes in space?
This shows that edge computing can transform the way we live, and we are doing it right now.
Why Collaboration Is Critical
Edge technologies are blending the digital and physical worlds in a new way, and that combination is resonating at a human level. This human resonance might sound like an aspirational achievement, but it is already here. A great example is when we used AR/VR to improve safety on the factory floor.
Continued collaboration, however, is necessary to keep enabling breakthrough successes. Across industries and organizations, we are all highly dependent on one another. Thinking about the telecommunications and industrial sectors, in particular, there is a mutually supportive, symbiotic relationship between these industries—5G development cannot be successful without industrial use cases, which, in turn, are based on telco technologies.
However, numerous challenges remain: reducing network complexity, maintaining security, improving agility, and ensuring a vibrant ecosystem where the only way to address and solve those is by tapping into the collective wisdom of the community.
With open-source, we can unify and empower communities on a broad scale. The open-source ecosystem brings people together to focus on a common problem to solve with software. That shared purpose can turn isolated efforts into collective ones so that changes are industry-wide and reflect a wide range of needs and values.
The collaboration that open source makes possible continues to ignite tremendous change and alter our future in so many ways, making it the innovation engine for industries.
If we collaborate on 5G and edge in this manner, nascent technologies could become exciting common foundations in the same way that Linux and Kubernetes have because when we work together, the only limit to these possibilities is our imagination.
From Maps to Apps and Much More
Do you remember having to use a paper-based map to figure out driving directions? Flash forward to today: Look at the applications we take for granted on our phones or in our homes that allow us to change our driving route in real-time to avoid traffic, or to monitor and grant access to our front doors—to the point that these have shaped how we interact with our environments and each other. Yet not too long ago, many of these things were unimaginable. We barely had cloud technology, we were in the transition from 3G to 4G, and smartphones were new.
But there was important work being done by lots of people who were improving upon the core technologies. The convergence of three technology trends, as it turns out, unlocked a hugely disruptive opportunity: a cloud-native, mobile-device-enabled transportation service that picked you up wherever you were and took you wherever you wanted to go.
This opportunity was only possible because each trend built on the others to create a truly novel offering. Without one of these trends, the applications from the ride-sharing apps of the world would not have been the same or as disruptive. Imagine yourself scrambling to find a WiFi hotspot on the street corner, whipping out your laptop outside a restaurant while standing in the rain, or starting your business by first constructing a massive data centre. The convergence of smartphones, 4G networks, and cloud computing has enabled a new world.
Today we are creating the next set of technologies that will become the things so embedded in our lives and so indispensable to our daily habits that we will wonder how we ever got by without them. Are you ready to be wearing clothes with sensors in them that tell you how healthy you are?
The possibilities with edge technologies are equally as exciting. It starts with the marriage of the digital world with the physical world. Adding in pervasive connectivity—leveraging a common 5G and edge platform—we can transform how operational technologies interact with the physical world and that changes everything.
The Future Is Now
We are creating this new world that is hard to imagine, yet it is not so foreign because we have seen how this story has played out before. Expect these new technologies to have profound implications for humanity—in our daily lives, how we interact with one another, and the social fabric of our world.
We have only to look at how open source has empowered collaboration and how working together has helped people across organizations and industries build more robust, shared platforms more quickly and differentiate on top of them—with apps and capabilities built on the foundation of Kubernetes and Linux, for example.
From shifting to work from home policies to customers’ increasing demand for better services and experience, organizations are finding that they need to transform faster to address the impact of the COVID-19 pandemic. We expect technology trends to only continue to evolve as reliance on technology becomes more critical in our current social and economic landscape. To ride out the wave rather than sink in it, forward-thinking organizations in Asia-Pacific (APAC) should rethink their digital transformation strategies based on these trends we expect to see in the coming year.
5G, IoT, Edge computing: The trio for intelligent connectivity
APAC will continue progressing on its 5G journey. While commercial 5G services are already available in nine markets in the region — including South Korea, Japan, and China — another 12 have officially announced similar plans. The increased availability of 5G will help drive the adoption of Internet of Things (IoT) and edge computing to deliver ultra-low latency, high bandwidth network, and effectively support large-scale distribution of endpoints. For example, 5G, IoT and edge computing can be applied to smart fleet management, wherein edge devices can monitor critical vehicle systems and access the 5G network to send alerts, track the flow of goods, plan routes, and facilitate communications between a vehicle and any IoT-enabled entity that may affect or be affected by the vehicle.
We foresee more APAC organizations and cities adopting 5G, IoT, and edge computing in 2021 to become more connected and efficient. Emerging use cases for the three technologies include analyzing sensor data for predictive maintenance and quality control, augmented reality systems for remote operations, and personalized ‘connected experiences’ for customer and supplier engagement.
Security is a growing priority for hybrid cloud
Customers and employees alike now expect business applications and services to be highly available, on-demand and secure. To achieve that, we recommend organizations to embrace hybrid cloud in order to run workloads across any environment (i.e., on-premises, private or public cloud) more easily and quickly. Red Hat’s 2021 Global Tech Outlook found that 77% of APAC organizations surveyed plan to use more than one cloud platform — be it private and public clouds — in the next 12 months, up from 53% in 2020. According to the survey results, the top three reasons for organizations to run their applications across hybrid cloud include improving data security, gaining IT agility, and addressing data privacy concerns.
Security will remain a focus area as organizations progress in their hybrid cloud journey — nearly half of the organizations we surveyed globally cited cloud security as their top funding priority next year. The challenge when it comes to security is that it is made up of different elements such as endpoint, network and data security. One way of overcoming this is by adopting an open security automation framework that unifies the different security practices using a set of automated workflows. By doing so, organizations can gain greater visibility across the entire security function, enabling them to identify threats or remediate cyber attacks faster.
Cloud-native will drive container adoption
Cloud-native applications can respond quickly to change, adapting and evolving with new features and functionalities released incrementally more quickly, reliably and frequently with less risk. As more organizations adopt hybrid cloud to increase the scalability and availability of apps, those that also embrace cloud-native development are in a better position to build and run responsive, scalable, and fault-tolerant apps on any cloud.
Containers are a key technology for unlocking the benefits of cloud-native development. Containers enable applications to be packaged and isolated with their entire runtime environment, making it easier to move them between environments while retaining full functionality. With containers, developers can more easily release and update apps as a collection of loosely coupled services, like microservices, instead of having to wait for one large release. Recognizing that containers can help accelerate innovation, 45% of APAC respondents from the 2021 Global Tech Outlook expect more than half of their workloads to be containerized in the next 12 months.
Automation is on the rise
Customers are demanding more at a faster pace, while IT architectures are ever-changing and built on increasingly complicated technology stacks. Organizations also need to support a work-from-home productivity model during the COVID-19 pandemic. To address these requirements, APAC organizations are increasingly turning to automation to reduce complexity, improve productivity, and lower operating cost. However, they must have an enterprise-wide automation strategy instead of deploying automation in silos in order to fully benefit from the technology.
More organizations are increasingly using automation in conjunction with artificial intelligence and machine learning to create an additional layer of automated insight to optimize business processes. Some APAC banks are already using robotic process automation (RPA) to approve credit card applications, automate payments, and validate claims. Because RPA can augment and mimic human judgment and behavior to replicate rules-based human action, it reduces the time taken for those tasks.
Open culture needs to complement technology modernization
According to a November 2019 study sponsored by Red Hat, 80% of APAC business leaders surveyed rank cultural change and technology modernization of equal importance for digital transformation. Cultural characteristics key for transformation include adaptability, inclusivity, transparency, and collaboration – all of which are open source principles. Organizations that have supported their cultural change initiatives with efforts to modernize their infrastructure and application architecture have been able to quickly develop and deliver new applications, respond rapidly to customer demands, and control maintenance costs.
With APAC businesses recognizing that digital transformation is driven by a change in mindset, we foresee more organizations embracing open principles, processes, and culture next year. By doing so, organizations can nurture collaboration and empower employees to bring their best ideas and selves to work, which can help accelerate innovation and address changing customer and business requirements in an agile manner.
All in all, global events in 2020 have caused organizations to focus on near-term survival goals to support business continuity. As the business landscape continues to evolve, APAC organizations must prepare for the future by adopting flexible, agile and scalable technology solutions. Considering trends such as 5G and edge computing, hybrid cloud and automation can help organizations as they develop or update their digital transformation plans in 2021.
As Malaysia enters a fresh wave of movement restriction measures and lockdowns, local businesses have once again been cornered to adapt and find their footing with digital transformation initiatives.
Although the pandemic has accelerated the uptake of digital business technologies, many leaders are still unsure of how to approach their transformations given the current challenges. Global Data’s Market Opportunity Forecasts model reveals that many businesses in Malaysia will delay their long-term digital transformation initiatives until at least 2021 to mitigate the risk of financial instability in business operations.
While forecasts remain gloomy, there is a way forward. Gartner has identified that IT leaders can successfully navigate this uncertainty by achieving a TechQuilibrium – the balance point at which an enterprise has the right mix of traditional and digital capabilities and assets to power the business model needed to compete most effectively.
So, how can enterprises find their TechQuilibrium? By leveraging technology that can help them do more with less, starting with the cloud. The cloud has played a significant role in helping many businesses survive — and even thrive – as operations moved online and employees shifted to remote work during the health crisis.
Businesses are looking to eliminate complexities and streamline processes. They need to have the agility to react to market changes and take advantage of opportunities. They need to be able to move quickly, to adapt and make changes to stay relevant and minimize costs. The good news is that cloud technology can help in all these areas.
The complexity of the Hybrid Cloud
The cloud journey can isn’t always smooth sailing, especially when businesses choose to take a hybrid cloud approach – a mixed computing, storage and services environment made up of on-premises infrastructure, private cloud and third-party public cloud services.
Implemented well, hybrid environments offer the advantages of both private and public clouds and help to drive the best return on IT investments. Businesses have the capability to move workloads between private and public clouds as computing budgets and needs change.
However, things can get messy when the rubber meets the road — mainly because collapsing operational silos is often easier said than done.
According to Nutanix research, a majority of organizations in Asia Pacific and Japan (APJ) see hybrid cloud as the ideal cloud approach but an alarming 72% believe that their transformation is taking longer than expected.
So, what exactly is holding organisations back?
A great deal of it has to do with the complexity of synchronizing private and public cloud technologies. Amazon Web Services (AWS) and Microsoft Azure, for instance, each have their own expansive, high-powered toolbox for managing resources in public cloud servers. On the other hand, private, on-premises clouds often use different tools and interfaces.
Reconciling the differences between private and public clouds can get expensive and time-consuming, but a hybrid cloud environment can also be a marvel of power and flexibility — if IT teams have the tools to seamlessly coordinate their public and private clouds.
Reconciling the Conflicts
In a nutshell, private clouds are public cloud-like solutions built on conventional on-premises data centres with racks of computing, networking and storage gear. Public clouds, on the other hand, are giant server farms operated by Amazon, Google, Microsoft and other technology platform companies.
Private and public clouds have different use cases. The consensus is that private clouds work best for industries with sensitive data — such as the public sector and financial services — where tight security and abundant, concentrated computing power is critical. By contrast, public clouds are known to be ideal for rapid software development and services that must scale up or down quickly.
That said, in this rapidly evolving environment where flexibility is key, enterprises need to be able to move resources like applications, containers and virtual machines between public and private clouds.
This is where hybrid environments come into play. An encrypted highway of sorts, hybrid cloud allows businesses to meld on-premise, private and public cloud capabilities.
However, until now, it was nearly impossible to move applications across platforms without re-architecting them. One component of tackling this challenge is to implement a unified cloud platform to manage workloads in both environments. Still, to be truly hybrid, businesses need help getting their workloads to flow seamlessly between public and private clouds.
Getting Down to Bare-Metal Level
Over the past year, I have come to realise that enterprises often need much more control over their public cloud resources than we as an industry previously believed. Here’s where utilising public cloud “bare-metal” compute instances with dedicated servers are critical. Bare-metal instances can enable businesses to build their hybrid cloud environments with ease, which typically would have required substantial expertise to master.
Why is this important? The team that manages an on-prem infrastructure may not be the same one managing the cloud infrastructure. This can then result in unnecessary costs and time spent, because different people do essentially the same job on separate cloud architectures.
Instead, businesses should utilise a hybrid cloud platform that would allow on-prem and cloud services to work the same way in both on-prem and bare-metal public cloud instances, all while breaking down silos. IT teams can then be more comfortable to manage their environments, without worrying about unexpected costs or needing to custom-build existing applications. This has proven useful for organisations in sensitive industries such as finance, and even businesses who have to manage demand spikes during the year.
Bare-metal compute offers businesses the opportunity for complete portability and flexibility. It provides superior economics and help teams manage and administer their multiple cloud environments through one unified, seamless IT operating environment, while keeping costs down.
Supporting Future of Work
There are several use cases for businesses to invest in a unified hybrid cloud management tool, and we have seen these come to life this year especially.
A flexible hybrid cloud platform allows businesses to support a remote workforce while adding secure connections for employees working from home. While businesses are beginning to reopen their offices, remote work could be a potential fixture in the future workforce.
An analysis by Deloitte found that up to 4.1 million people in Malaysia – or 26 percent of the workforce – could shift to working remotely over a multi-year time horizon. A hybrid cloud platform can enable organisations to support this future.
External factors such as seasonality, like the upcoming holiday shopping season, may require some businesses to ramp up computing resources. 2020 is also known to be the year of disruption, increasing the impetus for businesses to strengthen disaster recovery and reduce downtime after a disaster. A unified hybrid cloud platform can enable businesses to spin up more capacity and shrink it when they need it, without having to reinvent these environments.
Ensuring Hybrid Success
There is a rule of thumb that Nutanix takes with software development. We focus on getting our product out in front of the customers, letting them try it out, gathering feedback, fixing bugs and iterating quickly to generate improvements. We also discuss directly with customers to identify their pain points and everyday challenges.
Business leaders should tap into this methodology to ensure that hybrid environments deliver the most value to the organisation’s users.
Hybrid clouds are more than an emerging trend. It is a new set of technologies and IT operating models that is reshaping how organisations across different industries will function now and in the future.
