Define And Tackle Your Edge Now
An ambulance speeds down the highway to take a critically ill patient to the hospital. Employees in a crowded retail store help shoppers find just the right gift. An airplane cruises at more than 800 km per hour and higher than 9000 meters in the sky. A factory produces equipment.
What do these scenarios have in common?
You may be thinking, “they have nothing in common.” However, these scenarios each represent an important place where valuable data is created and acted upon. This data harnessed the right way, can create immediate, essential value and positively impact not only business outcomes but critical health and safety outcomes, too. We call these places where data can be acted upon near the point of creation the “edge.”
What is the Edge?
The edge is everywhere and can be hard to define. From the examples cited above, your edge could be just down the hall from your data center or flying around the world on a jumbo jet. Most definitions of edge computing agree that it refers to moving computing power closer to data sources, although the specifics can vary widely. It has been touted as a means which also brings operations close to the end user, unlike cloud computing. One of the most commonly cited cases of using edge infrastructure includes cybersecurity systems to monitor the operational network locally as well as storing and processing operational data to bring it to the cloud. Effectively, edge computing is about customer experience.
No matter what you call it or where you put it, the right approach to edge computing is specific to your industry and to your organization. When the right edge computing strategy is put in place, it can transform your business operations and outcomes.
Two years ago at a Press Conference held in Singapore, Schneider Electric said it was ready to pioneer the uptake of edge computing in Africa. It is during this period that its former Vice President, Secure Power Division Dave Johnson mentioned that African countries like Kenya needed not to feel to be left behind.
For example, healthcare organizations may wish to build remote clinics to serve customers in rural areas. Care homes have also been a great example of how edge computing can tackle both congestion and compliance problems. For instance, during the world outbreak of the Coronavirus disease, Kenya took the initiative of having patients who were asymptomatic and had mild symptoms undergo the care home procedure while recovering from the disease. Such a process usually requires the ability to process data close to the source to provide clinicians with near real-time patient information while also complying with healthcare guidelines.
Edge computing for healthcare could include analytics systems capable of processing data from patient monitoring systems or solutions that consolidate, and transfer insights used for population health tracking.
These solutions deployed at remote locations with limited IT staff need to be compact and simple to deploy and operate, with intrinsic security, advanced automation, and remote management capabilities. Without such support, the network’s edges may endure the IT equivalent of peripheral neuropathy. The biggest challenge here is the time scale.
Manufacturers can deploy sensors and video cameras to monitor the overall effectiveness of equipment on the factory floor and the quality of products coming off the assembly line. Edge computing takes the various sources of data and analyzes them to look at general trends. Data insights can be used to improve output quality and speed the system to make it as efficient as possible. A manufacturer could try to transport their data to a data center, but it would require massive amounts of time. With an edge strategy, the data is analyzed on the factory floor, providing the manufacturer with better data insights and accuracy so they can make faster decisions and improve efficiencies.
A retailer may aim to provide better shopping experiences by tracking how products are moved throughout a store to manage inventory and supply or help customers more quickly. With edge computing in a retail location, combined with AI, retailers can track what inventory is paid for or ensure employees are in the part of the store where they are needed most.
These edge scenarios are so different in design and outcome that lumping them under the common term “edge” seems like a misnomer. The IT infrastructure footprint, network, input sources, security, data storage, data protection, and architectural considerations all will be driven by several factors. These include the characteristics of the data that must be analyzed at the edge, how fast insights must be derived to align with the desired business outcome and what portion of that data or metadata will need to be sent back to a centralized environment.
How to Tackle Your Edge
The process of implementing and operating edge computing isn’t always straightforward either. Edge initiatives often have unclear objectives, involve new technologies, and uncover conflicting processes between IT and operational technology (OT).
Here are three tips to help you kick off your edge strategy:
- Design for business outcomes.
Successful edge projects begin with a foc