Cloud Computing Taken to “The Edge”

The introduction of the cloud was a revolution in computing. By allowing enterprises to store data easily, securely, and more inexpensively, it changed the game for small businesses, particularly those seeking to operate in industries where data storage is highly regulated. While the cloud is a great place for centralized computing, not every computing task needs to run on a centralized system.

For this reason, computing is continuing to evolve as data projections and analytic demands continue to increase, particularly with the rise of the internet of things (IoT). We’ve gotten so used to “the cloud” that this new trend might sound counterintuitive. But edge computing stands to shake up how we think about the cloud, and how it will be used in the months and years to come.

What is edge computing?

The broad term, “edge computing” originated nearly 20 years ago when the term “edge servers” arose to refer to servers in content-delivery networks (CDN’s). It has more recently been used for processing, analyzing and applying knowledge from data produced by sources at the edge of the network—such as IoT devices and mobile devices—versus transmitting that data to a “core” processing unit.

Edge computing allows data produced by devices to be processed closer to where it is created instead of sending it across long routes to data centers or the cloud. By avoiding these centralized systems and operating closer to “the edge” of the network, organizations can analyze data in almost real-time, which is becoming increasingly necessary in industries such as manufacturing, health care, telecommunications, and finance.

Why go to the edge?

The three main drivers pushing organizations towards edge networks are:

    • Growing consumer and business data usage;
    • Emerging technologies—particularly in networking, processing, software—areas that make edge computing possible;
    • Demand for greater efficiency in processing and transmission across the network, lower latency, and the delivery of a better customer experience and data security.

There is explosive growth in IoT projected in the coming years. There have been a number of estimates of the growth in devices, and while they all vary, they are all in the billions of devices.

Processing data at the edge of the network, right where it is taken in, will reduce the burden on both the data center and the network, thus also reducing latency and make these connected applications and devices more responsive and robust.

Source: Network World

Should small businesses consider either?

Enterprises in several industries are particularly well poised to benefit from edge computing:

    Smart cities. As the number of sensors and sources grow (via citizens, traffic systems, health-care systems, utilities and security programs), storing and analyzing data in a central location will become more cumbersome. Edge computing will reduce latency delays in community services where action must be quick, such as in medical emergencies, law enforcement, traffic patterns and public transportation. It also allows for geographic precision, so information relevant to a particular street, block or suburb can be shared instantaneously with users in that area.
    Automated vehicles, drones and remotely operated machinery. Perhaps the most familiar example of edge technology—a self-driving car—is practically a data center on wheels. Self-driving cars can process live video and stream photos to make immediate decisions based on data input. They highlight the need to share collaborative information through a smart transportation network. This concept can extend to drones for agriculture, mining, oil and gas, and other industries that have to react in real time to the data they collect.
    Media and content. CDNs are already bringing content closer to the user, and edge computing is a logical next step to deliver additional applications to customers, such as interactive services.
    Manufacturing and Industry. Industrial organizations large and small have been adopting robotics, artificial intelligence and machine learning, all of which are optimal uses for edge computing. Manufacturing are constantly seeking to streamline production into a standard process from demand to production, delivery and consumption. This effort requires the exact type of real-time collaboration between data sources across a range of locations that edge computing provides.

Despite the increasing momentum and variety of applications of this trend, the jury is still out regarding precisely how and when edge computing will be fully deployed. With this in mind, the technology may not be for every business, at least for now. As with many innovations in the IT-sphere, adoption of edge computing and applications will ultimately be determined by how well these technologies mesh with individual business goals and will depend on whether an organization has the resources—either internally or via partnership with an MSP—to effectively implement and manage them.