NTT unveils what it calls the ‘first edge and private 5G’ service

“In fully digitized enterprises, data will be generated in all possible locations of the respective site,” said Leo Gergs, senior analyst at ABI Research. “Edge computing allows data to be processed much closer to their origin.” 

He added that by reducing the transmission of data between the place of origin and the place of processing, “edge computing drives down end-to-end latency, as any avoidable data transmit will be scrapped.”

Official edge-as-a-service

Capitalizing on this trend, NTT Ltd. today announced at VMware Explore its new edge-as-a-service (EaaS). It’s the first globally available, fully managed edge and private 5G offering, according to Shahid Ahmed, executive vice president for new ventures and innovation at NTT. 

The service is powered by VMware’s Edge Compute Stack and will enable enterprises to track, analyze and take action on data where it’s generated or collected. Concurrently, VMware is adopting NTT’s Private 5G technologies. The companies will jointly market the offering. 

“Enterprises have unique needs, especially in manufacturing, healthcare, retail and logistics around high availability and uptime,” said Ahmed. “They want to have control over the entire system; continue operating without being dependent on cloud connectivity.” 

Sanjay Uppal, senior vice president and general manager for VMware’s service provider and edge business unit, agreed: “Data gravity, meaning the place where the data resides most, requires capture and analysis of key data as close as possible to where it is created.”

Gaining an edge

According to IDC, worldwide enterprise and service provider spending on edge hardware, software and services will reach $176 billion this year, representing a 14.8% increase over 2021. That spend is anticipated to approach $274 billion by 2025, according to the firm. 

Dovetailing this, the spend for edge computing within private networks will be $5.8 billion by 2030, according to ABI Research. 

Similarly, an NTT-sponsored survey of 216 technology executives predicts that private 5G networks will become the standard across industries. The survey lists the following results: 

• Just over half of executives plan to implement a private 5G network within 6 to 24 months.
• The most anticipated outcome of implementing private 5G is improved data privacy and security.
• A key barrier to adopting edge/5G is integration with legacy systems and infrastructure. 

Gergs pointed out that, while the combination of edge computing and 5G is nothing new, the pace of innovation and new product announcements has accelerated noticeably just this year. Hyperscalers are entering the stage and increasing their traction in the private networks’ domain — which is “traditionally a telco play,” said Gergs. 

All three major hyperscalers have offerings in place to capture edge compute data payloads and attract them to hyperscaler infrastructure, he pointed out. This includes AWS’ Private 5g; Google Cloud’s extensive partnerships with Betacom, Boingo and Kajeet; and Microsoft’s Azure Platform and acquisitions of Metaswitch and Affirmed networks.

Edge computing and 5G: A complementary pairing

Gergs called the combination of 5G and edge computing a “true win-win situation, as both trends will be an important enabler for each other.”

On the one hand, private 5G is “an important driver” for edge computing, as it allows offloading processing of cellular network data in different locations of a cellular network (that is, away from the core network), he said. Therefore, “enterprises will be looking at edge computing to distribute processing payloads evenly across their private network,” said Gergs.

On the other hand, edge computing is “an important building block and catalyst” for private 5G from both technology and commercial standpoints, he said. Edge computing will make any private network more efficient because it drives down end-to-end latency. Furthermore, by distributing payloads, it avoids overloading the core network with processing tasks, therefore “ensuring that the network remains functional even with the vastly increasing amount of data on enterprise sites,” said Gergs.

In addition, edge computing will considerably drive down total cost of ownership (TCO) for private networks, as it allows the utilization of some already existing public network resources for enterprise deployments, he said. 

Unlocking data

Clearly, across the board, there is a greater need for distributed compute processing power and data storage with “near-instantaneous” response times, said Ahmed. 

Connected devices generate significant amounts of data, thus creating a major challenge to extract, aggregate and leverage actionable information in a scalable way, he said. Also, the adoption of cloud and cloud services has created a hybrid model where enterprises simply can’t move the entire suite of applications and services into the cloud to take advantage of new kinds of low-latency, high-bandwidth connectivity. 

There is substantial data generated in these environments at the edge that enterprises want to process in real-time, locally, while avoiding high costs of backhaul connectivity into the cloud processing, said Ahmed. At the same time, there is a need to keep data localized for security and GDPR requirements.

NTT’s EaaS allows “better data control, immediately actionable insights, and a reduction in disruptions and costs,” said Ahmed. Other benefits include acceleration of business process automation, near-zero latency for applications at the network edge, more secure environments and global coverage. 

Combined edge and private 5G capabilities can predict, for example, equipment-servicing needs or potential outages, he said. 

Uppal also pointed out that the combined capability allows enterprises to utilize the newest radio access networking capabilities running on commodity hardware. He predicted that, moving forward, most data will be created at the near and far edge. And, both these compute platforms require IT-like management and automation.

All told, 5G networks have numerous advantages, such as broader coverage in difficult locations for use cases like drones, autonomous vehicles, cameras and other sensors. “You also get lower latency, higher performance, and better management and security,” said Uppal.