Edge computing deployments are well underway as companies seek to better process the wealth of data being generated, for example, by Internet of Things (IoT) devices.

So, what are the results? Plus, how can you ensure success with your own edge projects?

Measurements of success

The use cases for edge computing deployments vary widely, as do the business drivers and, ultimately, the benefits.

Whether they’re seeking improved network or application performance, real-time data analytics, a better customer experience, or other efficiencies, enterprises are accomplishing their goals. Based on two surveys — one by Automation World and another by Futurum Research — respondents have reported:

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The growth of edge computing is about to take a huge leap. Right now, companies are generating about 10% of their data outside a traditional data center or cloud. But within the next six years, that will increase to 75%, according to Gartner.

That’s largely down to the need to process data emanating from devices, such as Internet of Things (IoT) sensors. Early adopters include:

• Manufacturers: Devices and sensors seem endemic to this industry, so it’s no surprise to see the need to find faster processing methods for the data produced. A recent Automation World survey found that 43% of manufacturers have deployed edge projects. Most popular use cases have included production/manufacturing data analysis and equipment data analytics.
  
  
• Retailers: Like most industries deeply affected by the need to digitize operations, retailers are being forced to innovate their customer experiences. To that end, these organizations are “investing aggressively in compute power located closer to the buyer,” writes Dave Johnson, executive vice president of the IT division at Schneider Electric. He cites examples such as augmented-reality mirrors in fitting rooms that offer different clothing options without the consumer having to try on the items, and beacon-based heat maps that show in-store traffic.

• Healthcare organizations: As healthcare costs continue to escalate, this industry is ripe for innovation that improves productivity and cost efficiencies. Management consulting firm McKinsey & Co. has identified at least 11 healthcare use cases that benefit patients, the facility, or both. Two examples: tracking mobile medical devices for nursing efficiency as well as optimization of equipment, and wearable devices that track user exercise and offer wellness advice.

While these are strong use cases, as the edge computing market grows, so too will the number of industries adopting it.

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According to research firm MarketsandMarkets™, from 2017 through to 2022, edge computing will experience a Compound Annual Growth Rate (CAGR) of 35.4% (from $1.47 Billion US to $6.72 Billion US). Those in the business of distributing, configuring and selling IT solutions recognize that traditional IT offerings will need to be modified in order to accommodate these new edge computing environments.

A number of factors influence the adaptation of edge computing in what are primarily remote locations. These include fast delivery and ease of installation, operation and management of that hardware equipment such as server racks and software. These systems also need to perform in such a way as to address latency, bandwidth cost and data location issues.

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It’s becoming a cliché to say that data security is a top concern among executives and boards of directors. The problem is: the problem just won’t go away.

Hackers and attackers are ever finding new ways to exploit weaknesses. Just as companies start to use emerging technologies like artificial intelligence and machine learning to protect their organizations in an automated fashion, so too are bad actors using these tools to further their goals.

In a nutshell, security simply cannot be overlooked. And now, as companies increasingly adopt edge computing, there are new considerations to securing these environments.

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Organizations in virtually every vertical industry are undergoing a digital transformation in an attempt to take advantage of edge computing technology to make their businesses more efficient, innovative and profitable. In the process, they’re coming face to face with challenges ranging from time to market to reliability of IT infrastructure.

It’s a complex problem, especially when you consider the scope of what digital transformation entails. “Digital transformation is not simply a list of IT projects, it involves completely rethinking how an organization uses technology to pursue new revenue streams, products, services, and business models,” as the research firm IDC says.

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“The IT industry has done a good job of making robust data centers that are highly manageable, highly secure, with redundant systems,” says Kevin Brown, SVP Innovation and CTO for Schneider Electric’s Secure Power Division.

However, he continues, companies then connect these data centers to messy edge closets and server rooms, which over time have become “micro mission-critical data centers” in their own right — making system availability vital. If not designed and managed correctly, the situation can be disastrous if users cannot connect to business-critical applications.  

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I’ve seen plenty of articles touting the promise of edge computing technologies like AI and robotics in retail brick & mortar, but it wasn’t until this past weekend that I had my first encounter with an actual robot in a retail store. I was doing my usual weekly grocery shopping at my local Stop & Shop, and who comes strolling down the aisle, but…. Marty… the autonomous robot. He was friendly looking with his big googly eyes and was wearing a sign that explained he was there for safety, and that he was monitoring the aisles to report spills, debris, and other hazards to employees to improve my shopping experience. He caught the attention of most of the shoppers.

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Despite the increasing popularity and convenience of ecommerce, 92% of purchases continue to be made off-line, according to the U.S. Census. That’s putting enormous pressure on retailers to meet new consumer expectations around real-time access to merchandise and order information. In fact, 85.3% of shoppers expect retailers to provide associates with handheld or fixed devices to check inventory and price within a store, a nearly 51% increase over 2017, according to a survey from SOTI.

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The global edge computing market size is projected to reach $3.24 billion US by 2025 (according to a study conducted by Grand View Research, Inc.). While this research underscores the speed and volume at which edge computing installations are growing, it masks the idea that many organizations still consider themselves in the early adoption phases of this technology. Before companies plan the move to widespread rollouts, they are seeking answers to significant deployment questions.

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Industry trends such as the Internet of Things (IoT) and content distribution networks (CDNs) are driving the need for edge computing. That’s because these solutions often require low latency, high bandwidth, greater reliability, and strong security.

It’s a tall order meant for Micro Data Centers (MDCs) to fulfill. An MDC is a self-contained data center architecture that offers complete IT infrastructure within a stand-alone, secure enclosure.

MDCs offer a number of key advantages beyond today’s server rooms and traditional data centers. First, because they’re distributed closer to bandwidth-intensive content, MDCs can significantly reduce latency and lower costs. Secondly, it’s easy and cost-effective to add data center capacity to them anywhere and anytime it is needed – in both IT room and non-climate-controlled environments. And because MDC IT equipment is pre-installed before shipment in a self-contained and secure enclosure, it can provide physical security and protection of critical business applications.

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Recent breakthroughs in technology have expanded the possibilities for where data is gathered, processed, stored and analyzed. IT staffs and their business counterparts now have the flexibility of deciding whether their applications are more efficient residing in the cloud, within a traditional data center, or on the network edge. In fact, for the first time, the nature of the applications themselves is determining where they best should run. Over the last several months, micro data centers have emerged as a technology of choice for helping to manage the growing computing needs across edge environments.

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IT professionals have been honing their data center management expertise for decades. However, migrating these best practices to an edge computing environment can be challenging.

That’s because many workers located in edge environments, such as retail store clerks, lack the necessary data center expertise to ensure edge sites are properly maintained. Complicating matters is the fact that edge data centers can be expensive and complex to run.

Clearly, organizations need a new way forward. Fortunately, cloud-based platforms are designed for the edge, and can simplify remote monitoring and management. Here’s what every business should look for in a solution:

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There are plenty of reasons for organizations to embrace edge computing. By moving applications, data, and computing services to the edge of a network, as opposed to a large data center or cloud, organizations can lower operating costs, improve application performance, reduce network traffic, and achieve real-time data analytics.

As more organizations come to know the advantages of edge of network devices, many are eyeing deployments. In fact, according to the IDG 2018 State of the Network, 56% of networking professionals have plans for edge computing in their organizations.

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What do embedded sensors, ecommerce sites, social media platforms, and streaming services have in common? They all produce vast volumes of data, much of which travels across the internet. In fact, Cisco estimates global IP traffic will grow to 3.3 zettabytes annually by 2021 – up three times compared to internet traffic in 2017.

For many businesses, these data packets represent treasure troves of actionable information, from customers’ buying preferences to new market trends. But as the volume and velocity of data increases, so too does the inefficiency of transmitting all this information to a cloud or data center for processing.

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Spending on Internet of Things (IoT) will reach $1.3 trillion by 2020, and the processing of 43 percent of this data will be at the edge, according to IDC projections. The number of “connected things” will reach 30 billion in 2020 and jump to 80 billion in the following 25 years, the research firm predicts. This market demand is driving the need for new solutions like edge computing.

Pendulum Swings

Historically, the primary point of IT has swung between the focus on a centralized model and a decentralized one. It started with centralized mainframe computing, then moved to decentralized client-server networks, and then back again to a centralized model in the cloud. Now, the time for the pendulum to swing back to a decentralized model has come in the form of ‘local edge computing.’

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Gartner defines edge computing as “solutions that facilitate data processing at or near the source of data generation,” a nice, succinct explanation of this booming technology. If you don’t need it already, you most likely will soon as it’s a key enabler of cloud-based applications, including Internet of Things (IoT) applications and others supporting the digital transformation of business.

“Organizations that have embarked on a digital business journey have realized that a more decentralized approach is required to address digital business infrastructure requirements,” says Santhosh Rao, principal research analyst at Gartner. “As the volume and velocity of data increases, so too does the inefficiency of streaming all this information to a cloud or data center for processing.”

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