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Edge Computing - A MUST HAVE for all Technology Strategies

Updated: Nov 28, 2022

Anthony Maiello, CEO, CTO July 28 2022

Most business leaders are concerned about keeping up with the overall management of their operations. CTOs and CIOs are therefore focused on efficiency and the response rate of their computing and this requires state-of-the-art data analysis capabilities that can be found with edge computing.

Edge computing is a top trend that all CTOs and CIOs need to be including in their technology strategies in 2022 and beyond. The early goal of edge computing was to reduce the bandwidth costs associated with moving raw data from where it was created to either an enterprise data center or the cloud. But more recently, edge computing has taken advantage of "real-time" technologies bringing data storage and computation closer to the business delivering differentiation experienced with major improvements in response times, costs, latency, and security, while also paving the way for AI/IoT evolution. The ongoing global deployment of the 5G wireless standard ties into edge computing because 5G enables faster processing for these cutting-edge, low-latency use cases and applications.

So, it's VNCTech Group's expert opinion, that CTOs and CIOs need to have some level of edge computing in their technology strategies across most industries if their leaders are concerned about overall management of their operations. This is no longer a "nice to have"; it's a "MUST HAVE" in all technology strategy planning.

Response Times / Latency

Increasingly, the biggest benefit of edge computing is the ability to process and store data faster, enabling more efficient real-time applications that are most critical to corporations. Speed gets massively enhanced with the help of edge computing as it reduces the amount of latency across most technologies and industries. Here are a couple of examples:

  1. Autonomous vehicles require faster processing of data since every millisecond while driving on the roads matter. By "intelligently" confining data analysis to the edge, the speed of processing (and storing) the data can be massively improved.

  2. Before edge computing, a smartphone scanning a person’s face for facial recognition would need to run the facial recognition algorithm through a cloud-based service, which would take a lot of time to process. With an edge computing model, the algorithm could run locally on an edge server or gateway, or even on the smartphone itself.

  3. Other applications such as virtual and augmented reality, smart cities and even building-automation systems require this level of fast processing and response hence take advantage of edge computing.

Cost Savings

For many companies, cost savings alone can be the single driver to deploy edge-computing. Retaining data without a purpose costs money and many companies often are not seeing the value. Edge computing reduces the cost of retaining data by categorizing data from a business and management perspective. As data can be retained in edge locations, it significantly reduces the bandwidth cost while eliminating redundant storage. Companies that initially embraced the cloud for many of their applications may have discovered that the costs in bandwidth were higher than expected, and are looking to find a less expensive alternative. Edge computing is the answer.


Edge computing enhances security to a new level by countering the issues of local compliance, privacy regulations, and data sovereignty. Although many "experts" believe that edge computing, in fact, expands the vulnerable surface for attacks, it should clearly nullify the impact of an organization if IT understands what to do as the number of IoT devices grows. It's imperative that IT understands the potential security issues and makes sure those systems can be secured. This includes encrypting data, employing access-control methods and possibly VPN tunneling - all should be part of the technology strategy.

AI and IoT

Edge computing is being accelerated by the rapid evolution of IoT starting to create an "AI based and smart architecture" over a set of distributed cloud services. For example, drones directly communicate with the enterprise IoT platform and conduct peer-to-peer exchanges. One of many examples is the latest package delivery drone by Amazon. While AI algorithms require large amounts of processing power that run on cloud-based services, the growth of AI chipsets that can do the work at the edge will see more systems created to handle those tasks.

CTOs and CIOs across all industries need to create and enable technology strategies aligned to business outcomes - short, medium and long term - and connect all the dots. In the major list of other technology trends and disruptions that all technology strategies should incorporate is, without a a doubt, some form of Edge Computing. This will ensure your company can deliver and differentiate well into the future.

How VNCTech Group Can Help

VNCTech Group is equipped with expertise and a proprietary VNCPropel Platform to assist you with all your technology strategy needs. Our experience spans 3 decades of helping companies and executives enable their technology strategies. Our VNC Propel platform is a data-driven technology providing an ecosystem of models, scenarios, experience and intelligent services that unleash full technology planning and delivery services.

We understand your existing technology, future technology trends and how it all relates to your business and industry - from edge computing to 5G and distributed clouds - we work with you to align your business needs to the right "actionable" technology enablers.

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