Similarly, traditional communications service provider (CSP) networks have edges. Because these edges are critical to CSPs’ ability to deploy services with solid customer experiences, there’s an Open Networking Foundation project called CORD, for Central Office Re-architected as a Datacenter, using virtualization and cloud-native technologies to help the CSP edge similarly deliver high-performing end-user experiences.
Reducing latency and boosting performance may be increasingly important in IoT applications. The speed with which IoT applications can affect a person’s health, safety or decision-making parallels what we accomplished with CDNs and what CSPs are now trying to do with their own networks.
Between IoT Apps and Processors
Real-time IoT applications are cropping up in planes, under the ocean, in autonomous vehicles, in smart utility meters, smart buildings, in Web-connected surveillance cameras on light poles…the list goes on.
Edge computing combines with analytics, artificial intelligence (AI) and automation directly in these devices – or in some cases, in mini-datacenters very nearby – to make data actionable almost instantly. Consider, for example, that financial trading systems, augmented and virtual reality, surveillance cameras, healthcare monitors and industrial robots generate vast amounts of data that are the most valuable at the moment they’re created. Edge computing attempts to make it available right at that moment.
Transporting data over large distances for processing, either to a traditional datacenter or a public cloud, incurs delay that real-time applications can’t tolerate. The analytics and AI can be bundled into the local processing so that the data becomes actionable almost in parallel with it being processed.
There are other, secondary benefits to edge computing in the IoT world. Perhaps most important, local processing filters data, reducing the volumes sent to the cloud or datacenter over a network, helping to ease network bandwidth requirements and cost. It also reduces processing resource requirements and costs in the cloud or datacenter.
That might seem like a minor consideration, if your enterprise is piloting small IoT rollouts. But with a possible 75 billion devices connected to the IoT by 2025, according to Statista. Using public cloud resources for storage and aggregate analyses, the volume and cost will add up fast.
How Enterprises Are Coping
How are IT teams embracing edge computing, from a management and security standpoint? With pockets of processing everywhere and billions of IoT endpoints opening up portals into organizations' networks and IT infrastructure, this could become a thorny task.
In some cases, such as in factory environments, the IIoT devices that need managing and securing may already be local. So they can be controlled by local systems and personnel according to existing policy and procedures.
Beyond that, enterprises will be choosing between traditional data center providers, new entrants and if CORD is successful, new locations that are within telecom companies.
Containers – From a management perspective, smart enterprises are managing the edge around containers. The approach is parallel to what happened when workflows became mobile and there were no longer definable network perimeters. Containers take virtual machines (VMs), which free application software and operating systems from hardware, a step further. They give code just the minimum it needs to run, helping keep ports and libraries you don’t need from being exploited. Many options exist and can be architected along with VMs or Hyperconverged Infrastructure.
Orchestration and integration – In addition, the industry is working to make on-premises, edge, and public cloud environments operate similarly enough that managing the distributed environment looks like a simple extension of your datacenter. Part of these efforts involves developing cloud-native tools that empower companies to build and run highly scalable applications in any cloud or edge environment. Eventually, it should be possible to create centralized policies in a standard way across private clouds, public clouds and edge locations, so that every time a new device is introduced, it doesn’t need to be secured separately, which can introduce the potential for error.
While all this integration work is not yet complete, significant progress is expected this year. With some hard work and a bit of luck, this orchestration will be available by the time large-scale IoT and edge computing implementations are ready in most enterprises.
This article from Steve Ginsberg, a CIO Technology Analyst at GigaOM, first appeared in Next Magazine, Issue 6.
Ken Kaplan is Editor in Chief for The Forecast by Nutanix. Find him on Twitter @kenekaplan.
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