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3 tips for developing an edge computing strategy (Reality Check)

Businesses have benefitted over the last few years from a wide variety of options for IT infrastructure, but edge computing has arrived and is redefining the way we approach today’s data center. Edge computing refers to compute, networking and storage capabilities that take place outside of the typical centralized data center, bringing IT infrastructure closer to where data is being created and used.

Although the terminology is relatively new, the concept has been around for a long time — an example being remote offices and branch offices (ROBO). These organizations require computing to take place in multiple locations, away from the main site. Other use cases include vehicles such as ships, planes and trains, large retailers with multiple locations, manufacturing facilities and medical institutions. Organizations such as these have long needed to manage and access data at multiple sites as it is essential to their day-to-day operation.

While more buzz is building around edge computing, it is important to have a strategy and plan in place to utilize the technology to the fullest. Below are a few guidelines of things to keep in mind as organizations build an edge computing strategy:

Take advantage of the rise of artificial intelligence and the Internet of Things  

 Edge computing is becoming more prevalent, and the rise in AI and IoT is bringing this to the forefront of business agendas. As these applications grow, there is an increasing need for quick and instant access to data. This is where edge computing comes into effect. Sending and retrieving data to and from the cloud brings with it a time delay and there continue to be concerns over connectivity. By analyzing data at the edge of the network, organizations can deliver real-time performance these applications need.

We are on the cusp of the possibilities this emerging technology can bring, and as our journey moves forward, the need for edge computing will become even more pronounced. Bringing data to the edge of the network will allow for real-time analysis with no latency. Many modern applications rely on data to operate and make informed decisions, and bringing that data closer will enable technology to advance. Edge computing will fundamentally allow these applications and IoT devices to respond, calculate and make informed decisions quicker, and smarter.

Although edge computing can vary from a few remote locations to thousands spread across a vast distance, many sites will share the same requirements. Paramount to this is performance and network connectivity since remote sites will likely not have the same levels of network connectivity as the main office/data center. And the more widespread the remote sites are, the higher the likelihood that connectivity issues will arise. It will be important to take advantage of AI and IoT to utilize edge computing to the fullest.

Don’t be overly dependent on the cloud

 For these requirements, local, on-premises computing resources can provide more fine-tuned and reliable performance. Although cloud computing enables organizations to operate remotely and provides scalability and elasticity, it is not without its drawbacks, such as internet connectivity and latency. If these sites are dependent on cloud computing to operate, then network outages or cloud outages will occasionally cause costly operational interruptions.

Some edge computing use cases have very specific performance requirements that are not always compatible with the capabilities provided by the cloud. For example, as we head toward smart cities and self-operating devices/gadgets, it’s imperative that operations are not hindered by lack of internet connection or cloud outages. Likewise, applications that rely on real-time data won’t be supported by a cloud model. However, IoT and AI are not the only technologies driving edge computing infrastructure. The same applies for many of today’s remote and branch offices, such as retail shops or manufacturing facilities. Many of these organizations rely on continuous connectivity to maintain business operations.

 Incorporate micro data centers into planning

 An edge computing strategy may well include some cloud computing capabilities, but it will most certainly include on-premises compute resources like micro-data centers. This is essentially on-premises technology scaled down to suit specific business models. The growth in edge computing is driving this demand because micro data centers eliminate the challenges around latency, connectivity and cloud outages, reliably processing data at the edge of the network.

 Edge computing is an IT infrastructure component that is getting a lot more attention as IT continues to grow and encompass every area of business and operation. With IoT on the rise, edge computing will grow, but organizations need to adopt a strategy that will also meet their remote site needs. Although not every environment is the same, these are common requirements and being able to deliver on remote IT infrastructure demands, while bringing data closer and to the edge of the network, will help organizations on their journey toward business success.

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