The ‘Next Big Thing’ in the
Cloud/Edge Debate

The ‘Next Big Thing’ in the Cloud/Edge Debate

November 2020:

The ‘Next Big Thing’ in the Cloud/Edge Debate

The IoT needs both cloud and edge to reach its potential.

At the beginning of this year, the 2020 State of the Edge report referred to edge computing and its profound potential effect on the internet as the “Third Act of the Internet.” Now, on the verge of 2021, the edge computing market, still considered to be in its nascent stages, is being hailed as a sort of “gold rush” opportunity for new and existing ecosystem players.

The battle cry from companies like Amazon, AT&T, Microsoft, Verizon, and others is that cloud and edge go hand-in-hand, but will more organizations shift resources away from cloud to focus on edge in 2021? Most likely. And yet, many other organizations are continuing to plot a course based on a “cloud-first” strategy. What’s driving these decisions and, as a result, the cloud and edge markets? What’s most important for the IoT (Internet of Things)?

Cloud Trends

By 2021, Cisco predicts 94% of workloads and compute instances will be processed by cloud data centers. Cisco also says thanks to surging cloud applications, data center traffic will reach 19.5 ZB (zettabytes) per year by 2021. By 2022, Gartner’s prediction is that worldwide public cloud service revenues will reach more than $330 billion. And by 2023, IDC suggests public cloud spending will approach $500 billion—that’s double what it was in 2019 ($229 billion).

Richard Beeson, CTO of OSIsoft, says cloud grew out of a need to scale compute, storage, and network for consumer applications and services. “The demands of (the) consumer world taught the software industry a whole lot about agility and scalability and reliability and responsiveness,” Beeson says. “The cloud grew out of the need to solve problems like worldwide search, selling all the books of the world, building the biggest yard sale ever, and sharing every conceivable cat antic. It also taught the world that physical things can be made more valuable through ‘software definition’, such as software-defined networks, software-defined storage, and software upgrades of cars. The ability to abstract the management, features, and functions from the physical layer yields agility to an otherwise physically defined world.”

Jay Owen, senior vice president and NAM Secure Power Business Leader at Schneider Electric, says businesses realize the benefits of cloud computing and its role in helping improve service speeds and reduce latency. “While many businesses may have initially been skeptical about its ability to keep data secure, the cloud has now established itself as an essential part of any IT strategy,” Owen says. “In fact, organizations are beginning to adopt ‘cloud-first’ strategies by partnering with service providers that can help them build and manage their data centers.”

Today’s data center industry is experiencing a rapid transformation from enterprises that build and manage their own data center facilities to hyperscale models. “As the need for data centers and cloud resources continues to skyrocket, so too will the hyperscale market,” Owen adds.

Source: 2020 State of the Edge

“In fact, Cisco estimated that by next year alone, hyperscale data centers will represent 53% of all installed data center servers.”

Hyperscale cloud providers like AWS, Microsoft Azure, and Google Cloud are playing and will continue to play a key role in meeting the growing demand for cloud services. “As businesses across the globe place more effort on digitization efforts and expand their use of technology, these cloud providers will have an essential role in reducing the complexity that comes with managing the environments needed to support today’s digital business,” Owen explains. “The ability for these providers to handle the dramatic increase in data and traffic, plus their ability to scale quickly and integrate with other platforms is what differentiates them from other providers and ultimately gives them a competitive advantage.”

Large-scale cloud infrastructure providers are continuously improving tools and services to make compute, storage, and data processing services a commodity. Other key cloud trends, according to Sastry Malladi, CTO of FogHorn, include serverless computing and multi-cloud strategies. “There are significant and rapid technological advancements happening in the cloud IaaS (infrastructure-as-a-service) and PaaS (platform-as-a-service) layers leveraging hyper-converged infrastructure, serverless computing, and Kubernetes-based resource cluster management,” Malladi says.

“However, the most important trend is the adoption of multi-cloud strategies by almost every major enterprise, including abstraction layers to eliminate vendor lock-in.”

However, not all computational needs can be addressed via cloud. Malladi points out there are connectivity, bandwidth, latency, and security concerns, and this is exactly where edge computing comes in.

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Edge Trends

Predictions in the edge computing market suggest growth is in the forecast for the next several years. MarketsandMarkets expects the edge computing space to reach $9 billion by 2024, up from 2.8 billion in 2019. BCC Research aims a little higher, suggesting the global market for edge computing will hit $21 billion by 2023. And in one study, Edge Internet Economy: The Multi-Trillion Dollar Ecosystem Opportunity from consulting firm Chetan Sharma Consulting, the edge internet economy is forecast to reach more than $4 trillion by 2030.

FogHorn’s Malladi points to a couple of exciting trends in edge computing right now. “Using the power of AI (artificial intelligence) at the edge, machine-learning capabilities are moving beyond traditional analytics,” he says. “These new implementations, called Edge AI, allow machine-learning models to be continuously updated and automatically trained with new, meaningful data.”

Source: 2020 State of the Edge

Consider the following scenario. When organizations build machine-learning models, an assumption is made that the model will be accurate as long as the data patterns the model has been trained on remains true. If new data patterns emerge, or if the model has not been trained on all possible data sets or workflows, the model might be biased and provide inaccurate results. “A solution to this problem is to apply closed-loop machine-learning updates (meaning Edge AI) by detecting accuracy-level degradations and triggering automatic retraining,” explains Malladi. “Live data is then pushed back to a retraining module for model updates and subsequently, a new model is pushed back down to the edge to bring accuracy levels back to the original state. In summary, Edge AI helps organizations analyze live data streams and deliver intelligence at or near the source, leading to increased overall productivity, efficiency, and cost savings.”

Chetan Sharma, CEO of Chetan Sharma Consulting, says the edge market is just getting started, but it has been accelerating throughout 2020. “It is like the new gold rush, where everyone wants to own a piece of the business,” Sharma says. “There are many more participants in the value chain than just the cloud players, so the ecosystem will be more interesting and diverse.”

Sharma says edge access will become hugely important for latency-sensitive IoT services. The market, he adds, is being driven by industries like industrial and entertainment. Video analytics and AR (augmented reality) are other key drivers. The ability to push processing to the edge, rather than shipping all the data to the cloud for analytics offers huge bandwidth savings. To the list of market drivers, Malladi adds industries like green tech, automotive, and smart buildings. In green tech, efforts to take environmental responsibility and minimize carbon footprints are driving edge-computing implementations. “For example, fleet transportation organizations are beginning to deploy edge-based sustainability efforts to detect abnormal regen and idling events in realtime—ultimately reducing billions of pounds of CO2 emissions per year,” Malladi says.


Source: 2020 State of the Edge

In automotive, edge technology is helping players process the significant amounts of data today’s connected cars generate. “As the future of transportation with autonomous and connected vehicles depends on the creation of the required intelligence and processing capabilities to build and operate sophisticated, autonomous systems, edge computing has become a great avenue to gather, merge, process, and deploy sensor data more effectively,” he adds.

Modern smart buildings are also using edge computing to lower energy consumption, improve predictive maintenance, better security, increase occupant comfort and safety, and allow for better utilization of building assets and services. Rather than sending massive amounts of building data to the cloud for analysis, smart buildings can use edge capabilities for more responsive automation while reducing bandwidth costs and latency.

Finally, in light of the COVID-19 pandemic that dominated the scene in 2020, Malladi says many commercial and industrial organizations are reconsidering operational processes to ensure employee and customer safety and adhere to new regulations, including increasing the use of PPE (personal protective equipment), ongoing social-distancing requirements, and daily temperature screenings. “To date, monitoring has not been available or is conducted manually by supervisors or staff observing adherence to practices and through posted reminders,” he explains. “Leveraging realtime streaming video analytics and artificial intelligence enabled by edge-processing capabilities for video, audio, and thermal cameras, organizations are automating health and safety auditing and generating alerts when unsafe conditions are detected.”

Source: MarketsandMarkets

The Next Big Thing

In an email to Microsoft employees back in 2018, Satya Nadella, the company’s CEO, made it clear that intelligent cloud and intelligent edge are complementary parts of Microsoft’s strategy going forward. Mahadev Satyanarayanan, known as “Satya”, a professor of computer science at CMU (Carnegie Mellon University), says, in fact, the convergence of cloud computing and edge computing is nothing short of “the next big thing.”

“By ‘convergence’, I don’t mean that differences will disappear. Not at all,” Satya says. “Each will retain its distinct attributes and strengths. Rather, by ‘convergence’, I mean that edge-native applications will be created that leverage both edge computing and cloud computing for different facets of their execution.”

There is no substitute for the cloud for some applications. For a use case that has no critical timing constraints or bandwidth scalability issues, the cloud offers the lowest cost per unit of compute. “The ability to operationalize these costs is another big win,” Satya adds. “In terms of long-term archival storage of valuable data, there is no place safer than the cloud—possibly private cloud for very sensitive data, but the cloud nonetheless.”

However, Satya contends that the IoT will never reach its full potential without edge computing. Pushing compute close to IoT devices and storing IoT data at the edge are both important for reasons of bandwidth scalability and data privacy. And this is especially true as denser deployments of IoT devices emerge in 2021 and beyond.

“Edge computing is no longer a fringe idea that is waiting to become mainstream,” Satya says. “The recent announcement of Wavelength by Amazon and Verizon is clear evidence that even the largest and most successful cloud provider sees the opportunity in edge computing.  Microsoft has also embraced both cloud and edge computing in a big way. Actual deployments of edge computing will take some time, but now (it) is only a question of ‘when’, not ‘if’.”

  • 6 Quick Stats for Cloud and Edge

    1. MarketsandMarkets: Edge computing will reach $9 billion by 2024.
    2. BCC Research: The global market for edge computing will hit $21 billion by 2023.
    3. Chetan Sharma Consulting: The edge internet economy will reach more than $4 trillion by 2030.
    4. Cisco: 94% of workloads and compute instances will be processed by cloud data centers by 2021.
    5. Gartner: Public cloud service revenues will reach more than $330 billion by 2022.
    6. IDC: Public cloud spending will approach $500 billion by 2023.

Andre Fuetsch, CTO of network services at AT&T, says he also views cloud and edge as complementary. “Each plays a role in a business’s networking strategy,” Fuetsch explains. “For the super low-latency applications, bringing the processing power to the edge is probably the way to go, but less time-sensitive applications that might require a little more ‘oomph’ in computing could benefit from sticking with cloud computing. But as these technologies continue to evolve, it will be interesting to see how businesses innovate with them. The future of the cloud and edge computing is being built right now, and it’s an area of focus with us and our customers.”

AT&T’s vice president of enterprise mobility, Robert Boyanovsky, says due to extenuating circumstances in 2020, everybody is thinking about how cloud and edge compute fit into their business models. “A consistent trend question we’re getting from our customers is ‘How do I become more mobile?’” Boyanovsky says. “Work has to happen from nearly anywhere now. Because they can reduce the load on hardware and servers at a specific business location, edge and cloud computing could enable us to deliver capabilities that can be deployed on mobile devices on a new scale.

Combining that with the rise of 5G, and the nationwide 5G we expect to have this summer, we’re seeing new possibilities with our customers for mobile services we could only dream about five years ago.”

In fact, AT&T says 5G and edge computing go hand-in-hand, and the company is working with cloud companies to deliver on the promise of 5G with edge computing while also working with customers and the developer community to solve real business problems. Boyanovsky says looking to the future, he sees edge computing bringing a “sea change” in how businesses can use cellular data to massively improve their operations. “(Edge computing) allows businesses to route application-specific traffic to where they need it and where it’s most effective—whether that’s in the cloud, the edge of our network, or on their premises,” he concludes.

In 2021, the trend to watch in cloud and edge is not only how they will continue to interplay with each other but also how 5G changes the entire landscape—from factory floors to stadiums, hospitals, retail stores, and university campuses. “5G is enabling mass connectivity—with the potential to connect roughly a million ‘things’ per radio head,” Boyanovsky says. “What cloud and edge computing can do for all of these new connected devices is give them the capabilities to run new services that rely on low latency.”

Cloud and edge computing work best together to deliver maximum results. In many ways, edge computing is in the spotlight right now, and, yes, many companies are investing in the edge. But, at the end of the day, edge is supplementing cloud computing, not replacing it, and both are critical to helping the IoT reach its potential.


Peggy and Daniel Ernst, distinguished technologist, high-performance computing & AI, Hewlett Packard Enterprise, talk about the future of computing—exascale. He says one of the core pieces of exascale is the rate at which we can do calculations.

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