Stay Connected from Edge-to-Core-to-Cloud with NetApp HCI

For Christmas of 2018, my dad, whose technology proficiency can best be described as limited, gave me an Amazon Alexa for Christmas. And my world changed. What did I do before I had a smart home device? Alexa reminds me to take out the garbage on Sunday evenings, plays perfect party music, and has helped settle a few trivial sports arguments between me and my husband (no surprise, I lose most). Beyond answering questions like “Which NFL teams have never been to the Super Bowl?” (sorry, Detroit), Internet of Things (IoT) devices enrich the lives of consumers by making data readily accessible. Businesses also can capture significant value by adopting IoT, but that requires a fresh approach to data architecture. To process the amount of data being captured by IoT devices, computing power at the edge has become essential. NetApp HCI is now available in a 2 Node configuration, designed as a starting, scalable entry point for edge workloads.

Like the internet itself, the IoT contains a wide variety of edge devices with different configurations that use different communications protocols and have different physical interfaces. As the number of connected devices and sensors—and the resulting data volume—explode, the landscape is shifting from a centralized model of client to cloud to a distributed compute model and to the emergence of the intelligent edge within an edge-to-core-to-cloud architecture. Keeping track of all these devices, the data streams, and the applications that deal with them, can be an arduous task that falls mostly on the developer.

The time that it takes to record, transport, analyze, and respond to the data from edge devices causes a delay that affects the ability to respond quickly to business-critical information. If the data is piped and processed in the cloud, that window of time, which could have been used to take action, may have passed. By distributing the computing part of the problem to the edge with NetApp HCI, it’s possible to execute detection-decision-action logic with limited latency.

Even if a business is digitally mature at its corporate, primary, and IT data centers, often the same cannot be said of their remote plants, factories, and industrial sites. Only in the past 5+ years have the costs of sensors, communications, analytics, and IT infrastructure come down to a point where the benefits of deployment outweigh the costs. Industrial data centers encounter difficulties because they are often running on bare metal and have no backup or disaster recovery programs in place. This lack typically offers challenges with software upgrades. It can also be difficult to contend with multiple disparate systems, each running separate analytics from multiple vendors.

Rapidly Make Business Decisions with Compute at the Edge