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Top 3 Predictions for Telecom in 2022

Telecom industry faces new challenges in the post-pandemic era

2022 will be a transition year for the telecom industry

After emerging from the COVID-19 pandemic relatively unscathed, the telecom industry is entering a new phase and faces a new set of challenges. These challenges include navigating a supply chain left in shambles due to the impact of the pandemic and, representing a separate concern, the inexorable rise and encroachment of hyperscalers in the telecom domain, which threatens to completely disrupt the status quo in the industry.​

Incumbent communication service providers (CSPs) and their vendors are navigating these issues, but there is an increased urgency to digitally transform and align with structural changes occurring in the industry, such as the pressure to work with hyperscalers on network transformation and business model co-creation in the cloud.​

2022 is poised to be a unique transition year for the telecom industry. While unprecedented government stimulus that originated in the wake of the COVID-19 outbreak continues to be pumped into the global economy, lifting all players in some way across the market landscape, CSPs and their vendors must transition to the fundamentally new network architecture, which is software-based, fully virtualized and cloud-centric. CSPs must also determine where they will play in the new value chains that are being created in the digital economy, most notably in hyperscalers’ marketplaces, and in conjunction with new players that are entering the scene in domains such as private networks and satellites.​

Meanwhile, supply chain challenges are expected to persist through 2022, with continuing semiconductor and component shortages as well as ongoing skilled labor deficiencies and shipping delays, all of which threaten to delay market development and hinder vendors’ ability to recognize revenue and pursue new growth opportunities. Inflation (potentially stagflation) and rising interest rates also pose risks, portending margin pressure and debt refinancing challenges.​

Taken together, these circumstances indicate 2022 will be an unusual year for the telecom industry. While government-induced stimulus will provide various benefits to players across the industry, giving off a sense that the industry is functioning normally and is healthy, an acceleration in competitive and technological changes poses a risk to the long-term performance of incumbents. Amid the uncertainty 2022 will bring, one thing is certain: Major changes are coming to the telecom industry in the post-pandemic world, and fast.

2022 telecom predictions

  • Supply-demand imbalance delays pace of 5G market development
  • Hyperscalers scale out edge cloud
  • Government becomes leader in 5G spend among nontelecom verticals

Send me a free copy of TBR’s Top 3 Predictions for Telecom in 2022

Telecom Business Research’s 2022 Predictions is a special series examining market trends and business changes in key markets. Covered segments include cloud, telecom, devices, data center, and services & digital.

Scope of Red Hat OpenShift expands, bringing hybrid cloud to new environments and open-source projects

TBR perspective

Based on a foundation in Linux, which enables containerized applications to move across physical and virtual environments, Red Hat maintains a unique market presence with its neutral PaaS solution, Red Hat OpenShift. Red Hat’s vision to extend the applicability of Red Hat OpenShift, which is leveraged by 90% of Fortune 500 companies, to new use cases, consumption models and environments was one of the key takeaways from Red Hat Summit 2021.

As discussed by Paul Cormier, one of the main benefits of an open hybrid cloud approach, which is based on open code, processes and cultures, is the flexibility to run applications across environments with consistency. This approach positions Red Hat and its customers to evolve alongside emerging market trends such as AI, 5G and even quantum computing. As seen in Red Hat’s expanding top line, the company has been successful leading with an architectural approach under core brands such as Red Hat Enterprise Linux (RHEL), OpenShift and Ansible. TBR believes Red Hat will be well positioned to expand its portfolio to new markets and customers and push its open-source expertise beyond the bounds of cloud computing due to continued support from IBM (NYSE: IBM) and an expanding ecosystem of systems integrators (SIs) and ISVs.

Red Hat expands Red Hat OpenShift usage with new managed cloud services

While Red Hat has offered Red Hat OpenShift as a managed service for some time, scaling up managed support is becoming a key initiative for the company, especially as more customers pursue managed offerings to offload operational tasks at both the applications and infrastructure layers. To broaden the applicability of Red Hat OpenShift, at the event, the company unveiled three new cloud managed services supporting customers’ need to build, deploy and integrate modern applications within their existing Red Hat OpenShift environment, either in the cloud or on premises.

At the Red Hat Summit 2021 conference, Red Hat continued to convey to a group of customers, partners and industry analysts the message of open hybrid cloud the company has been leading with for over a decade. Over the course of the three-day event, executives including Red Hat CEO Paul Cormier and Products and Technologies EVP Matt Hicks outlined Red Hat’s evolution from an operating system company to one offering a full suite of self-service software and services for hybrid cloud.

mimik pioneers a unique hybrid edge cloud solution that empowers the localized autonomy of devices

The journey to capitalize on the edge is rooted in deep telco experience, coupled with a passion for breaking boundaries

A brief history lesson is important to understand how mimik came to be. It was during her tenure as CEO of Vodafone xone that mimik CEO and founder Fay Arjomandi realized the growing importance of decentralizing data analytics and processing to the edge. Through the testing of capacity improvement and utilization of network traffic, Arjomandi noted the inherent delay that occurs when traffic hits a data center, causing extensive issues such as bottlenecks as data struggles to reach the back end of the application. This was all occurring in the context of the rapid evolution of devices themselves, increasing not only in sheer volume but also in sophistication.

Arjomandi came to the realization that the existing architecture of the time was not equipped to support the ongoing shift to a hyperconnected digital world where almost every object can be smart. The future is not about vertically integrated devices that communicate in a linear fashion to the cloud or on-premises data center environments, but rather will be rooted in horizontal platforms where data can be processed and exchanged across diverse networks, platforms and systems. Created in the context of IoT but viewed with new eyes as the Internet of Systems versus “things,” mimik pioneered a new architecture in the form of a hybrid cloud edge solution that enables any computing device to act as a cloud server with the ability to communicate autonomously and locally and to make decisions across and within networks. 

Empowering local systems to make autonomous decisions is mimik’s core value 

By virtue of placing enterprise applications closer to where data is created and where insights are actionable, edge devices have always maintained some degree of autonomy. That said, there has also been an underlying perception that the cloud has an umbilical-cord-like function in that it ultimately serves as the main governing force and point at which most of the data is processed, analyzed and housed. mimik has cut the cord, recognizing that as IT becomes increasingly decentralized, localized servers and sensors are evolving beyond mere endpoints and becoming part of powerful systems that can function independently of the cloud. mimik’s Hybrid edgeCloud application development platform was born out of the realization that applications can interact locally with the power to function as clusters of communities that communicate, inform and analyze data at the source.

The edge has traditionally been viewed as a localized extension of the cloud, providing a 1+1=3 opportunity to capitalize on the inherent benefits of the cloud with localized data processing and reduced latency. In the context of an increasingly hyperconnected world, the devices and sensors that interact at the edge are taking a central role, driving more and more use cases, rather than acting just as add-ons to amplify the value of the cloud. By focusing on what devices can accomplish as part of interconnected systems at the edge, mimik, a Canada-based technology firm, has emerged with an advanced out-of-the-box solution, Hybrid edgeCloud, which enables any computing device to act as a cloud server. The multiple positive implications include lowered latency, reduced constraints on network bandwidth, heightened security and decreased cost of cloud hosting — all due to the reduction of traffic traveling to and from the cloud and the enhanced connectivity within and between systems of devices.

COVID-19 necessitates data center investments, becoming a catalyst for digital transformation

Like the rest of the world, IT decision makers have been moving into a highly reactive and tactical mode in 2020 to mitigate COVID-19’s impact on the businesses they underpin. TBR believes the ripple effect of these decisions will continue through 2021. The COVID-19 pandemic has accelerated macro trends toward cloud technologies that leverage automation to reduce person-to-person contact in economic commerce. AI and machine learning will pull infrastructure along and similarly push the infrastructure deployments further to the edge, while reinforcing the need for investment in emerging technologies to solve pain points that existing technologies cannot address.​

Join Stephanie Long and Geoff Woollacott as they dive into the impacts of COVID-19 on the data center market thus far and how they predict the impacts will evolve during 2021.

Don’t miss:

  • How 1H20 investments in modernizing the data center to meet COVID-19 mandates will reduce data center hardware spend in 2021
  • COVID-19 increases the need for edge deployments
  • Quantum computing advancements persist, leading to an increase in M&A activity to consolidate capabilities

Mark your calendars for Wednesday, Feb. 3, 2021, at 1 p.m. EST,
and REGISTER to reserve your space.

TBR webinars are held typically on Wednesdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. Previous webinars can be viewed anytime on TBR’s Webinar Portal.

For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

NVIDIA acquires ARM: Creating a next-generation AI platform

NVIDIA announced Sept. 14 an agreement to acquire ARM holdings from SoftBank for $40 billion, subject to regulatory approval in the U.S., the U.K., the European Union and China. The acquisition has been rumored for several weeks, but the announcement generated negative comments from ARM customers. The two companies’ IP portfolios complement each other, especially in the context of rapidly growing AI workloads. TBR believes the combined company can successfully create new integrated AI hardware platforms, while growing profitable in each former company’s primary business, graphics processors for NVIDIA and mobile CPUs for ARM.

Complementary IP and different business models

ARM is in the CPU business. NVIDIA is in the graphics processing unit (GPU) business, and NVIDIA GPUs are increasingly used in non-graphics AI processing applications. Both companies rely on microprocessor design to deliver value and grow their businesses, but the way each company monetizes its IP is very different. NVIDIA is a traditional product-based business; it makes processors and boards that it sells to equipment manufacturers and to cloud service providers. ARM follows a licensing model; it sells the rights to use its designs and instruction sets to equipment manufacturers that often modify the ARM designs to meet their needs.

One concern of current ARM customers is that NVIDIA will eventually move ARM to a product model; only NVIDIA will make hardware that incorporates ARM designs, shutting off customers’ ability to customize ARM-based chips. This would be a disaster for the major mobile OEMS, including industry behemoths Apple and Samsung. ARM chips power virtually all smartphones and tablets, and mobile vendors rely on derivative ARM designs for differentiated products. Apple makes its own modifications and recently announced that its PCs will be migrated from Intel to ARM processors, allowing the company to have a uniform hardware platform for all its major products. Samsung designs its own ARM processors but relies on third-party ARM designer Qualcomm for many of its products. To make matters more confusing, Samsung manufactures both Qualcomm and Apple processors.

NVIDIA announced that it would continue the current ARM licensing business model and, in fact, would license some of its GPU IP in the same manner. Nevertheless, ARM customers are concerned because strategically vital licensed IP would now be owned by a hardware vendor. TBR believes the ARM licensing model will continue for ARM designs and the same model will greatly benefit NVIDIA’s GPU business as well.

NVIDIA is transitioning from graphics to AI

NVIDIA is the dominant vendor in GPUs, and for that reason, if its processors were used only for graphics, its growth would be limited to the growth of graphics applications. GPUs, however, are also well-suited for AI deep learning applications because both graphics and deep learning rely on massively parallel processing.

2Q20 is a crossover quarter. For the first time, NVIDIA data center revenue, which is almost all AI, was greater than revenue from graphics applications in PCs. NVIDIA data center revenue grew 167% year-to-year; NVIDIA will soon be dominated by AI applications in data centers. There is competition in AI processors from Google’s tensor processing unit (TPU) and from field-programmable gate arrays (FPGAs), as well as several new AI processing entrants, including two from Intel. Nevertheless, NVIDIA enjoys an enormous lead in a very rapidly growing business.

GPUs and CPUs working together

GPUs and CPUs coexist. Every device that uses GPUs for AI needs CPUs for all the other required processing. In data centers, the CPU is now almost always an Intel product. While ARM designs are increasingly powerful, as illustrated by Apple’s decision to use them for PCs, they are not yet used widely for data center devices. Where the GPU is doing most of the work, however, ARM-NVIDIA designs could be quite viable. ARM-NVIDIA designs would also work well in edge devices. This synergy positions NVIDIA well in a world where deep learning is becoming increasingly important.

Applications for deep learning are becoming more diverse, creating a variety of settings and requirements for CPU-GPU platforms. This proliferation of design requirements is a challenge for a product-based company like NVIDIA. The ARM licensing business model fits this diversifying market very well. TBR believes NVIDIA will first experiment with the licensing of older GPU designs, but then move rapidly to licensing GPU IP for all AI applications, greatly accelerating adoption of NVIDIA designs for AI and inhibiting growth of competing AI chip designs.

The ARM acquisition will accelerate AI

While NVIDIA and ARM are not competitors, therefore reducing anti-trust concerns, many parties have expressed concerns about this acquisition. Both companies are very important, with NVIDIA dominating AI processors and ARM monopolizing mobile CPUs. There are also concerns about a U.S. company controlling these two critical components. In the U.K., there is concern about the loss of jobs. TBR, however, believes this union will prove beneficial, certainly to the combined company, but also to other companies basing their business on the growth of AI.

Technology Business Research, Inc. announces 2Q20 webinar schedule

Technology Business Research, Inc. (TBR) announces the schedule for its 2Q20 webinar series.

May 6           IoT use case stories: How use cases drive IoT

May 20        The digital transformation ecosystem demands cooperative partnerships

June 10        The CSP ecosystem is gearing up for a major edge build-out; the U.S. and China will lead the world

June 17        Cloud is becoming higher touch

June 24        Advisory-led discussions help quantum computing emerge in customers’ transformation-centric conversations

TBR webinars are held typically each Wednesday at 1 p.m. EDT and include a 15-minute Q&A following the main presentation. Previous webinars can be viewed anytime on TBR’s Webinar Portal.

For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

The CSP ecosystem is gearing up for a major edge build-out; the U.S. and China will lead the world

Communication service provider (CSP) spend on edge compute infrastructure is poised to ramp up over the next few years as telcos and cablecos virtualize and cloudify their networks and as webscales pursue their digital lifestyle-related initiatives and stimulate growth of their cloud businesses. The U.S. and China will lead the world in edge compute development.

TBR’s Telecom Edge Compute Market Forecast, which is global in scope, details edge compute spending trends among CSPs, including telecom operators, cable operators and webscales. This research includes current-year market sizing and a five-year forecast by multiple edge compute market segments and geographies, with the most recent publication covering 2019 to 2024.

Join Principal Analyst Chris Antlitz on June 10 for an in-depth and exclusive review of TBR’s most recent Telecom Edge Compute Market Forecast.

Don’t miss:

  • Why webscale companies such as Amazon and Microsoft are building out the edge
  • Which countries will deploy the most edge sites by 2025 and why
  • How COVID-19 could impact demand for edge computing

Arriving at the edge of cloud computing

The cloud reimagined by edge computing and influenced by IoT

Cloud computing can be best described as a centralized data center remotely running thousands of physical servers. All devices that need to access this data or use applications associated with it first must connect to the cloud. Since everything is centralized, the cloud is generally easy to secure and control while still allowing for reliable remote access.

As IoT devices become more common and require more processing power, an increasing amount of data is being generated on what is referred to as the edge of distributed computing networks. By sending only the most important and least time-sensitive information to the cloud, as opposed to raw streams of it, edge computing eases the burden on the cloud and reduces costs. Put simply, edge computing delivers the decentralized complement to today’s core centralized and hyperscale cloud and legacy data centers.

The edge and the cloud do not compete with one another, and emphasizing edge or cloud computing is not an “either/or” choice, but rather, the adoption model can be viewed as a “1+1=3” opportunity. The relatively distributed nature of cloud and access to scalable compute resources is augmented by the real-time data gathering potential of the edge, reducing efficiency and latency concerns. These latency requirements vary by device and are highly situational depending on the need for real-time analytics and response versus transactional or business intelligence analytics.

More than a decade after the initial transition to the cloud forever expanded the limitations of physical and on-premises storage and compute options, we’ve reached quite literally, the edge of a new era of cloud. Organizations in industries such as telco and manufacturing, among others, will increasingly rely on edge computing to provide a suitable infrastructure and to complement the ongoing adoption of related technologies such as machine intelligence and IoT. The edge should not be viewed as a threat to cloud computing, but rather as the next phase in the evolution, driving increased adoption of the cloud into the next decade.

Maturing offerings, vendors and customers prompt long-term IoT vendor growth

The continued interweaving of the technology component market with Internet of Things (IoT) techniques delivers a well-defined path to long-term sustained growth for many IT and operational technology (OT) vendors, especially those vendors that are best able to differentiate their portfolio and position themselves as critical partners for a wide set of IoT solutions.

The hype surrounding IoT has only served to confuse and overwhelm customers and vendors, but efforts by both parties to cut through the hype is driving the growth of installed IoT solutions. As the hype fades, vendors are better able to rationalize their go-to-market strategies and messaging, particularly around how to assemble IoT solutions, leading customers to better understand how to apply IoT.

However, while it is becoming easier to assemble an IoT solution, it is still challenging to design and implement the IoT technique. We don’t expect a huge explosion of revenue; IoT itself isn’t a “killer app,” but it will enable moderate and slowly accelerating revenue growth for the various components involved in an IoT solution.

In our 3Q18 reports and thought leadership, TBR will focus on three topics that we believe are currently the most impactful on the wider IoT ecosystem: the increasing maturity of the IoT technique, the growing consolidation of generic platforms, and how increasing commoditization around IoT is working in favor of economies of scale and enabling the growth of installed solutions.

IoT is growing up: Increased ecosystem maturity will lead to increased customer adoption

TBR, through discussions with vendors and customers as well as our use case databasing, is noticing growth in installed IoT solutions, whether from net-new deployments or expansions of existing IoT deployments, signaling improved maturity. IoT maturation is not so much about the components of IoT as it is about businesses developing their ability to leverage technologies and techniques that are increasingly applicable to a growing number of business problems.

A major driver of this maturity is greater clarity around IoT techniques, led largely by go-to-market realignment and improved messaging by vendors, organization around IoT by customers, shifts from competition to coopetition by vendors, and general improvements in the construction of the technology that facilitate advanced usage of the IoT technique.