Government on the Edge: Part 1 – Developing an Edge-to-Cloud Model

Not so long ago, cloud computing changed the world as we knew it. It drove a rush to move workloads, applications and data into the cloud to take advantage of cost and management efficiencies. But a funny thing happened on the way to nirvana in the cloud, says Steve Orrin, federal chief technology officer at Intel: “A lot of organizations learned quickly that you don’t get anything for free.” It turns out, he says, “There’s a cost to doing things in the cloud, and if you don’t build cloud-native applications, you’re not really getting all the benefits you thought you’d get.”

This sentiment is especially true in the public sector, where “lift-and-shift” cloud efforts — a common strategy for moving workloads from one environment to another — helped migrate data and applications quickly and easily, but didn’t necessarily take into account the steps they had to take to prepare for successful cloud adoption.

Orrin, who has spent several years in his role at Intel, knows a thing or two about the tools needed to collect, aggregate, analyze and respond to data before it is transmitted to a cloud environment. With a host of offerings designed specifically for government agencies and contractors as they embark on their cloud migration journey, Intel’s edge-to-cloud offerings are designed to satisfy specific government requirements. As a result, technologists like Orrin have a front-row seat on the trends and demand signals shaping the future of public-sector cloud services.

These trends, Orrin explains, are moving in two directions: First, there is the general drive to converge data centers and build and deploy cloud-native applications; and second, is the emergence of the Internet of Things, with a proliferation of sensors and endpoints that generate massive data loads and demand instant local processing to make that data useful.

“That data is being generated at the edge by devices and sensors,” Orrin says. “There’s a massive expense of transferring all of that data into the cloud to do anything useful with it. What we are now seeing is the next logical extension: looking at mission applications, enterprise applications with the aim to drive intelligence and value to the end user in real time.”

To do that, agencies will need to ensure some processing occurs at the edge, he notes.

To derive the full value of artificial intelligence and machine learning, Orrin says intelligent edge computing is critical — especially where multitudes of data require advanced or accelerated processing capabilities. “If you want to do natural language processing for translation, or video or object recognition, you quickly see the need for doing something closer to the edge,” he explains.

An Edge-to-Cloud Model to Enhance the User Experience

Users don’t want to wait for data to travel halfway across the country or around the world and back. Nor is that always possible, especially in national security or other remote applications where network connectivity may be unreliable and where mission effectiveness cannot be dependent on connectivity. Such systems must be able to operate when networks are overwhelmed, degraded or disconnected.

But adding cloud-like processing at the edge does not mean abandoning the cloud itself.

“It means we have to do the right computing and the right processing at the right place,” Orrin says. “Video recognition and object recognition is a really good use case to understand why this is: If you’re driving in a Tesla, you want to be able to recognize that car at the corner right now, not when the network is ready to respond. You can’t wait for the cloud to communicate back and say, ‘Oh, yes, that’s a car, don’t turn.’”

At the same time, users depend on access to the cloud to do their jobs effectively. For instance, a Transportation Security Services agent, a reconnaissance drone in the sky or a soldier at an observation post in a combat zone all require access to locally processed data in real time as well as cloud-fed data from other sources to gain valuable insight and make informed decisions quickly and effectively.

“Also, you want to combine data from across multiple mobile platforms, doing both sensing and analysis, and then combine those to do things like predictive traffic patterns, to recognize inputs and use them to make better decisions,” Orrin adds. “That’s where the cloud is really powerful, being able to go across multiple sensors, and do the Big Data large-scale analytics. Now you can get insights you don’t need in real time, as well as the information you need immediately. That’s really the power of the edge and the cloud working together.”

Read Government on the Edge Part 2 to learn more about how IoT and cloud offer new opportunities for government innovation.

Mission Ready: Powering Innovation from Edge to Cloud
Intel’s new resource centerprovides resources to government decision-makers and helps the public sector make the most of modernization efforts. The resource center is your one-stop-shop for information on the remote workforce, securing the edge, data modernization and offering insights that help you achieve mission success.