Welcome to the intelligent edge. Deloitte describes it as ‘the ability to pull upon the capabilities of Industry 4.0 technologies to act on the intelligence offered by data close to where it is captured’. It is the empowerment of the enterprise through efficiencies and valuable insights and the rich mysteries of analytics to translate data into insights and transformative business processes. Here, at the edge, the full scope of AI, connectivity, and compute merge to provide the organisation with the tools it needs to improve operations and drive the competitive advantage.
Forrester believes that the intelligent edge has come of age, moving from the realm of a science experiment to a solution capable of delivering real value. It is, according to the research firm, not so much a promising technology, but a toolkit that can be leveraged to transform cloud capability and enterprise innovation and that is able to fully realise the potential of the data generated by the Internet of Things, AI and 5G.
Gartner has estimated that around 75% of enterprise-generated data will be created and processed outside of the traditional centralised datacentre or cloud by 2025. This staggering figure highlights the importance of solutions that are capable of facilitating the movement of data and removing reliance on traditional points of data access. By removing the distances that data travels between point of origin and point of analysis can significantly reduce costs, improve latency and bandwidth, transform infrastructure costs, and support the move towards a more agile enterprise environment. This decentralised approach to digital business is far more suited to managing the volumes of data launched by IoT and devices into the cloud and datacentre.
Evolution of AI
The secure and immediate play of information across the business network has played no small role in driving interest in edge compute and has been further enhanced by the rapid evolution of AI. AI has become the great edge enabler, providing organisations with the tools needed to almost instantly turn the data into value and business relevance. As Forrester points out, AI at the edge will finally come of age, accelerating digital transformation and the development of intelligent edge applications.
Another of the key trends outlined by Forrester on the edge is the emergence of the datacentre marketplace as a hosting platform, thereby bringing compute even closer to the customer. This will be enabled by colocation providers, content delivery networks, and localised datacentre operators that can leverage local insights to deliver global value.
The speed and volume of data will only continue to increase exponentially, which makes it incredibly important for the organisation to minimise inefficiencies when moving the data from device to the cloud or to the datacentre. With the intelligent edge at the organisation’s disposal, it can do so much more with its data, catching it almost as it is created and improving speed to market, speed to value, and speed to productivity. As the edge and the technology that powers it come of age, it’s time to find the right hardware, connectivity, devices and technology to make sure that the enterprise is capable of fully realising the potential that sits on the edge of its compute.
Three Questions
It’s intelligence, Jim, but not as we know it
Brainstorm: Define the intelligent edge today – what is it, what does it mean and is it still interesting and important?
Hanno Brink, Synthesis machine learning engineer: The intelligent edge is really the marriage of two concepts. The first is edge computing, which simply refers to compute that happens right where the data is captured and often in a distributed manner. The second concept is machine learning, which is an increasingly well understood technology able to turn vast amounts of data into programs mimicking the insights and experience to produce seemingly intelligent behaviour.
Glenn Noome, director at Smart Integration: There has been a definite increase in edge solution investment. You only need to look at Tesla for an example of this, with its self-driving car autopilot neural networks. Covid has actually increased the investment and development into edge solutions.
Premie Naicker, CEO, FuseForward SA: Many organisations are finding it challenging to make meaningful use of all the data they are generating, and even those that have dedicated data teams are struggling to shift from a reactive to a predictive mindset. Companies are looking to the edge, and analytics in particular, to extend the life of assets and bring more predictability to their performance and health, which ultimately helps them plan and prioritise maintenance activities.
Tony Bartlett, director, datacentre compute, Dell Technologies South Africa: Although edge technology isn’t new, it’s the adoption thereof that has accelerated, along with the advent of the Fourth Industrial Revolution and the resultant convergence of technologies, accelerating our progress towards 5G speeds of connectivity as well as the emergence of hyper-connected intelligent devices.
Brainstorm: What role does IoT play in defining, shaping and driving the intelligent edge?
Leona Mentz, regional operations manager: Asia, Middle East, and Africa, BT: IoT is the foundation on which the intelligent edge is built. After all, capturing data as close to the source or point of creation as possible, means a company can start deriving intelligence from it by cutting out the middleman – in this case the cloud. When dealing with a massive amount of data, having the ability to analyse and filter the data before sending it can lead to huge savings in network and computing resources.
Hanno Brink, Synthesis machine learning engineer: IoT is really at the forefront of the intelligent edge innovation and this is an area where I believe the most value can be unlocked. This is also the area with the most significant challenges to overcome. The major challenges to the intelligent edge are bandwidth, latency, connectivity, cost and energy efficiency and any innovation that makes more efficient use of the available resources or alleviates some of the limitations could potentially open huge new areas of innovation.
Tony Bartlett, Dell: Devices such as phones, drones, automobiles, smart watches, utility grids and industrial sensors and machines are churning out large amounts of data, making it increasingly urgent for IT leaders to determine how and where this data will be processed. Accessing and analysing of distributed real-time data is becoming more important to businesses and is driving the need for different computing strategies and processing systems that complement larger datacentres located far away.
Brainstorm: Why should the business be paying attention to the edge?
Sven Blom, head of sales, Teraco: Demand for services requiring edge will increase. New technologies such as 5G, AI, VR and AR, as well as IoT will demand low-latency services, which will undoubtedly provide a stimulus for more edge infrastructure. Greater standardisation will unlock innovation for those clients seeking to harness the edge.
Leona Mentz, BT: The edge will transform the way companies deploy and consume datacentre resources.
Muggie van Staden, MD, Obsidian Systems: Edge computing is critical to creating new and improved ways of doing business, delivering data at speed, securely and with minimal downtime and increased levels of productivity.
Andreas Bartsch, head of service delivery, PBT Group: The intelligent edge brings with it a level of convergence not previously possible. Moving outside the context of IoT, this intelligence can help in the paradigm of data engineering, data analysis, and business intelligence – tying back into the concept of convergence. When the barriers of legacy, archaic ingestion patterns are removed and the use of technology and people at the place that the data resides to connect systems are maximised, then true business change occurs.
Shakeel Jhazbhay, GM: digital business solutions, Datacentrix: Edge devices make it possible to look at the manufacturing process from a holistic point of view, seeing where it is being affected, and where it can be streamlined and made more efficient. This, in turn, allows for faster, better decision-making.
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