How close to the edge is your business model?

Many industry sources are now advocating that edge computing is increasingly an important topic being discussed in the boardroom. Leading analysts such as Gartner are reporting that the interest and demand for the capability to deliver edge cloud computing is growing exponentially. By 2022, 50% of enterprise-generated data will be created and processed by edge computing infrastructure. Furthermore, Gartner also reports that by 2025, the integration of a business’s IT infrastructure, in terms of delivery of content, will have increased fourfold compared to today where only 20% of infrastructure strategies integrate on-premises, colocation, cloud and edge. 

What is edge computing and why should you be interested?

This blog will explain what is edge computing and how it compares with cloud computing in its traditional format. Plus, the reasons you should be interested in Edge Computing. For those not using or unaccustomed to the technology here is my view of edge computing simplified.

So, what is Edge computing? It is a relatively new term but the challenges it is attempting to solve have been around for a very long time. The catalyst that is fuelling this quest is two-fold and is deeply rooted in our insatiable appetite for data on-demand and instant connectivity. The IoT (Internet Of Things) threw a massive rock in the traditional computing pond to which the ripples are now hitting the shoreline by accelerating the deployment of services that has been termed “the fourth industrial revolution.” This revolution is where data is the commodity, not the development of machines and the physical manufacture of materials as seen in previous industrial revolutions. The other catalyst is our adoption of autonomous and self-learning machines including AI (Artificial Intelligence) which is placing additional computational demands on traditional IT models as vast amounts of raw and unclassified data stream into systems that must collate, assess, and repurpose this information.

The next increment in our experience is the connection of these disparate and largely unconnected silos of data (i.e specific management systems, such as building, plant or safety systems, smart cities, smart ecosystems etc) enabling segments of useful data to be accessed either in the background or as real time interactions. The provision of this more holistic picture of datasets that when combined gives richer information to the user has required a rethink in where the computation takes place and will continue to be at the forefront of service providers as the integration and commercial adoption of the metaverse takes shape.

As the hyper connected world continues to develop, the two limiting forces at work here are still very down to earth problems and planted firmly in the domain of large cloud data centre providers and network companies around the world. These two forces are network latency (speed that data can be transmitted between two points) and volumes of data stored and processed (how to sift the useful information from the noise).

One definition of edge computing that Wikipedia lists is “any type of computer program that delivers low latency nearer to the requests.” It also notes “The origins of edge computing lie in content delivery networks that were created in the late 1990s to serve web and video content from edge servers that were deployed close to users”, confirming my earlier point that this is not new news.

Today, the infrastructure, networking and software are at the centre of this revolution, with Colocation of critical infrastructure being deployed across the world to act as aggregators, gateways and repeaters for service providers delivered using SD-WAN technology. This is software developed to enable virtual network topologies on which to route and operate edge computing services.

With super accessible, super configurable networks comes the need for super security, which is why edge computing is closely linked to the relatively new term of SASE (Secure Access Service Edge). Security Access Service Edge is predicated on a Zero Trust access model for corporate data. SASE addresses the significant shift in digital service adoption by consumers and corporates alike, enhanced by the Covid pandemic which saw the pivoting of many businesses to a digitally engaged strategy.

To read more about SASE and Zero Trust, read Vissensa’s 10 steps to Zero Trust Guide which can be found by clicking here.

Why all the fuss now?

One theory is that the global install base for IoT will exceed 75.4 billion devices by 2025 and as these sensors and autonomous devices expand, the technical challenges of getting all the data back to a central point, sifting it out to find the nuggets of useful information, processing it into data that is worth something and then transmitting it back or onward becomes impossible.

Edge Computing addresses this fundamental issue of volume and in turn, s creating new commercial opportunities by enabling a new set of partnerships to be developed that are intended to make the use of IoT based devices a frictionless and ubiquitous operation for the user Take embedded devices that can talk to the Internet, (i.e lights, mechanical sensors etc) these devices are already conforming to a standard so that a user can plug and play without having to understand how they connect. The manufacturers of these devices only have to collaborate on the connect method or protocol and a vast set of potential users can be unlocked. The technology is a “push” technology in that the device can be sent instructions and can be interrogated for settings and measurements but is unlikely to transmit information interactively back to base.

Ahead of these devices are the semi-autonomous devices, those that can transmit and receive a limited instruction set and can act on these instructions with predefined operations, (i.e plant or building monitoring (BMS), security or even home heating systems, home entertainment hubs and devices). These usually require a persistent network connection to operate but can maintain a setting or service independent of the network if it is temporarily unavailable. They will transmit and receive data if the network is available and change their settings based on a predefined set of criteria.

Then comes the smart devices that are expecting high payloads of information to be transmitted and received in which to either inform the user or make decisions themselves. This ranges from gaming and AI type activities, to self-learning technology, UAVs (Unattended Autonomous Vehicles)) which adapt their operation based on real-time data it is receiving while transmitting operational data back to a hub where the combined collection of many data points or sources can identify trends that can then be used to modify the behaviour of a fleet of machines, which could save time, materials or improve safety or throughput. In these cases, the interaction with the device or user is high and the demand on infrastructure requires a dispersed edge model.

In these situations, the world’s network topology just will not be able to keep up with all this data transfer and just like your internet at home goes slow when your family are logged on. The speed at which data from these remote devices will slow down and, in the worst case, take too long to transmit or be transmitted too late and become irrelevant or worthless in this real-time world.

The solution is to move the computation (sifting, processing, and classifying data) closer to the user or customer using services deployed locally and at the edge of the central computing function (called gamelets and cloudlets) before sending data back to a traditional core datacentre.

To understand better what AI and self-learning technologies can be applied to look at the following YouTube video from Microsoft which introduces project Bonsai and its business application.

How does edge computing help?

Firstly, edge computing network architecture removes the need to transmit large volumes of data between different points. Moving services to the edge enables the operations that are critical to the user (speed, relevance, usability, and security) to be processed close to the consumer.

Operations such as persistent tasks and storage, service management and security, content delivery and local caching can use edge computing network architecture to offload to edge based physical devices located either in physical data centres or on-premise computing facilities or localised public cloud networks.

This is one reason there is a global expansion of cloud services from big market players such as AWS, Google and Microsoft, who are building out hyperscale services in geographically important commercial centres around the world to be able to offer cloud-based edge services to their clients.

Spending these vast sums on capital building and equipping these data centres, it removes the problem of the reliance on a fast stable network to deliver consistent results aligned to a business’ vision. Laying more undersea cables and joining them together is far more expensive and technically challenging than building edge computing facilities on land. The importance of building out these services now will only grow when 5G devices exponentially increase the amounts of data being collected and classified. The near instant processing of data from connected devices and sensors will become an everyday activity.

As business agility by service providers is accelerated, geographically relevant processing of data becomes technically possible without the need to maintain persistent network links. The effect will be a cost reduction in the deployment of microsystems in specific geographic, regulatory, or political markets to support businesses moving into a new territory or new commercial lines.

An important footnote to the activities described above is security. The ability to deploy edge computing network architecture closer to the user negates the need to move private and personal data (including voice) across a network to process it, an important threat vector for cybercriminals, however, it places the network at the centre of all security based activities.

Edge Computing, SD-WAN technology and SASE processes are all moving at a great pace to keep up with the demands of computing networks at the edge, but the investment and broader understanding of the relevance of the security stance needed to protect corporate assets still lag behind where the cyber criminals are. Many companies are only now starting to adopt a Zero Trust network stance which is where SASE (Security Access Service Edge) is so relevant in a service based edge computing world.

Edge computing vs cloud computing and edge computing vision and challenges

“Cloud first” is a trendy term used everywhere an IT model is discussed. However, many companies are pausing their strategic IT planning and asking how edge computing compares with cloud computing as a deployment strategy? Reviewing this rush to cloud vendors, considering the emergence of edge computing, is starting to change the adopted technology engagement model. A more business relevant model might be “cloud first but not at any cost.”

The importance of understanding a workload continues to be a strong determining factor in where a service is deployed, and this is one of the biggest differentiators of how edge computing compares with cloud computing. The main driver of these discussions is the continued interest in the use of containers and kubernetes as the best way to enable easy workload and service flexibility. The costs and complexities of the delivery of edge computing, and its effects on the already sunk CAPEX infrastructure is driving more business to move to a hybrid, hyper converged IT model. This model engages specific cloud services which are combined with physical owned or rented infrastructure at the edge, operated by managed service providers like Vissensa in combination with a traditional data centre or on-premise infrastructure and intelligent software, particularly focused on the network component.

Successful CTOs are spending time focused on how their edge computing vision and challenges will dovetail into businesses applications, rather than scaling the physical infrastructure. For many businesses, this is a seismic move to aligning a service driven strategy in place of a traditional IT-architecture-driven strategy to provide the agility that successful businesses need in an ever-changing world.

Vissensa has a long history of being at the forefront of technical innovation and rode the wave of colocation, network connectivity, cloud and hybrid deployments. In a continued investment in technology that supports a wide range of market sectors across the world, Vissensa has continued to invest in datacentre capabilities. We can offer organisations a secure and resilient footprint across several geographically important locations offering edge computing on demand. Eliminating the need to purchase your own edge computing hardware and utilise best in class equipment from the top data centre providers. We can set this up quickly and at a fraction of the cost of building traditional hub and spoke services.


What are edge computing vision and challenges?

Successful CTO’s are spending time focused on how their edge computing vision and challenges will dovetail into businesses applications, rather than scaling the physical infrastructure. For many businesses this is a seismic move to aligning a service driven strategy in place of a traditional IT-architecture-driven strategy to provide agility that successful businesses need in an ever-changing world... read more

What is edge computing simplified ?

One definition of edge computing that Wikipedia lists is “any type of computer program that delivers low latency nearer to the requests”... read more

How edge computing compares with cloud computing?

The importance of understanding a workload continues to be a strong determining factor to where a service is deployed, and this is one of the biggest differentiators of how edge computing compares with cloud computingThe main driver of these discussions is the continued interest in the use of containers and kubernetes as the best way to enable easy workload and service flexibility... read more

What companies are using edge computing?

Let’s look at some of the highest-ranking applications that use edge computing: 

  • Pixel streaming (VR goggles or gaming)  
  • Trackers on cars and vans, and vehicle automation and safety systems 
  • Automated maintenance or warning systems on building plant and machinery 
  • All types of AI and Machine learning, medtech, fintech, pharmatech 
  • Voice & facial recognition and assistance 
  • 5G and wireless information 
  • Smart cities, smart homes, smart cars etc more