How Cloud Computing and Edge Computing Fit Together
Published on : Tuesday 09-11-2021
Edge computing has a significant positive impact on an organisation’s operational responsiveness, but it is complementary to – rather than competing with – cloud, says Rob van den Dam.
The rising popularity of edge computing has all to do with its ability to analyse data at its source. This is important as the increasing number of connected devices and sensors, the growth in industrial automation, and the demand for immersive experiences will require more decision-making at the edge of networks. Gartner predicts that, by 2022, more than half of enterprise-generated data will be created and processed outside of a traditional centralised data centre or cloud. This will reach 75% by just 2025. Edge computing deployments will have to expand rapidly for this to occur.
Artificial Intelligence (AI) plays a central role in the success of edge computing. In fact, AI has become the key driver for the adoption of this technology. AI can process large amounts of data in short periods and provide the insights to drive quick, local, data-informed decision making. It allows businesses and systems to take actions based on the most current data at any point in time. Locating AI close to the edge is particularly crucial for applications where near-real-time feedback and optimisation are a priority for applications – such a machine control, equipment monitoring, and remote surgery.
Intelligent edges will lay the foundation for industry innovation at a whole new level. That’s why edge computing deployments is gradually expanding into enterprises. An example can be found in agriculture, where a number of sustainable companies are already equipping plants with IoT-enabled sensors and using edge computing to monitor the growth needs and ideal harvest time for individual plants.
Some other examples can be found in the area of AI-assisted driving. Automotive companies are essentially making cars into edge devices, equipping them with internal and external sensors and using faster AI-based edge-induced decision making to power actions in real time – from braking to steering and lane changes. In real-time multi-player gaming, where milliseconds can make the difference between winning and losing, edge computing is used to improve the user experience.
Edge computing vis-à-vis cloud models
Edge computing is the act of running workloads on the edge of the network or on edge devices – instead of within clouds. This has a significant positive impact on an organisation’s operational responsiveness to changing conditions, and on its ability to generate better user experiences.
Improving operational responsiveness is the key reason why organisations are increasingly counting on edge computing. They believe edge-induced responsiveness will lead to significant business benefits, including reduced operational costs, more automated workflows and increased productivity (Figure 1).
But it is not only about improving responsiveness. Edge computing will also ease the growing pressure on the core network. Instead of overwhelming the network with a flood of relatively insignificant raw data to centralised cloud resources, edge applications can analyse, filter, and compress data locally. This will also improve energy efficiency as more data is processed at the edge and less moves to and from the cloud, thus reducing power consumption.
Edge computing allows for offline reliability and continuous operations. Although the edge-based application may interact with a centralised cloud, edge computing doesn’t need continuous contact with one. It also supports improved security because sensitive data can be analysed at the edge and doesn’t need to be sent over the core network to a central cloud.
And last but not least, edge computing can power new edge-inspired business models. An increasing number of organisations are already planning investments to further support these data-driven business models, and changing their processes and workflows to accommodate intelligent machines and interconnected devices.
Edge computing is complementary to – rather than competing with – cloud computing (Figure 2). In this way, benefits can be leveraged from both local (on the network gateway, company premises, or edge devices) and cloud computing. Cloud computing is better used to process data that are not time-driven, while edge computing is favoured for time-sensitive data and/or where the volume of data collected is too much to send—unaltered—to a cloud. Edge computing is preferred over cloud computing in remote locations that require local storage and while operating specialised and intelligent devices.
The race to the cloud and the edge
No doubt, the giant tech companies have dominated the cloud space since the beginning. In Q1 2021, the top 5 providers – Amazon AWS, Microsoft, Google, Alibaba and IBM comprised 72% of the $129 billion market for infrastructure as a service (IaaS), platform as a service (PaaS), and hosted private cloud service, with Amazon taking nearly a third. Although the market for cloud infrastructure comprises more than just these 5 companies, these players stand alone as hyperscalers with the technology, resources, capital spending budget and customer momentum that make them unique.
Hyperscalers continue to benefit from the massive economies of scale they have built. And they realise that cloud is no longer about raw compute and storage infrastructure. They have become platforms with robust developer communities and partner ecosystems supporting the development of market-leading products that end-users grave.
And they are rapidly establishing themselves as cornerstone technologies for digital transformation and industrial IoT. They are extending their capabilities to the edge to access source data and fulfil their digital transformation proposition. Hyperscalers see edge computing as an extension of their cloud business that places computing closer to the point of consumption and enables new ground-breaking services.
But non-hyperscalers – such as telecom operators, network equipment providers and smaller cloud and edge solutions providers – will be relevant as well, with many seeing strategic value in taking the lead role in offering cloud-related services to enterprises. Enterprises will continue to demand a diverse vendor portfolio to avoid lock-in, address data security, and take advantage of non-hyperscaler’s unique strengths, such as easier consumption models, points-of-presence, strategic client relationships and deep industry knowledge, allowing them to cater well to specific enterprise demands.
Non-hyperscalers also have great position to serve small businesses, including SMEs and startups. Cloud computing might be interesting for these businesses – for instance, to offload the hassle and costs of IT-management – as long as they can live with the disadvantages, such as security issues related to having their business data “out” on the internet. Their approach might be to start cloud computing slowly by choosing one or two business applications to be replaced.
Ideally, hyperscalers and non-hyperscalers should collaborate in ecosystems to co-create services in support of vertical industries. Telecom operators, for instance, have clear strengths around connectivity and networking, while hyperscalers understand how to be agile, innovative and software driven. As an example, Verizon built its own platform and ecosystem that enables developers to deploy 5G applications, with flexibility to manage multiple hyperscale partners – including Amazon AWS and Microsoft Azure – for different needs.
5G changing the equation for cloud and edge computing
5G is the first generation of telecom service that will truly be deployed in the cloud. Traditionally, telecom applications were running on appliances or purpose-built hardware, but that will all be replaced by a cloud-native environment where applications will run in containers with a common resource orchestrator, such as Kubernetes.
With 5G, we stand on the brink of the third digitisation wave – the “network cloud”. Network cloud is following the two previous waves of digitisation – PCs and cloud computing. Network cloud will converge network and cloud functions, connectivity and computing, infusing data-driven intelligence and automated decision-making into applications, forming what we call “intelligent connectivity” spread throughout network tiers.
Despite all the dramatic growth we have seen from cloud computing, the gains from the third wave are likely to be orders of magnitudes larger. Virtually everything in the digital world will need to adapt to accommodate the complexity and size of it: strategies, technology architectures, enterprise systems, operating models, development models, the nature and scope of platform business models and partner ecosystems, cultures, and the base that unites it all – enterprise-wide intelligent connectivity.
5G is designed to support applications that depend on increased connection speeds, improved traffic capacity, very low latency, high reliability/security and support for high density of devices. But it is especially the blending of 5G, edge computing and AI that represents a unique foundation for enabling new ground-breaking use cases simply not possible today (Figure 3). Without AI-based edge computing, 5G applications and services will rely upon connecting through the core network to centralised cloud resources for storage and computing, losing much of the positive impact of the latency reduction enabled by 5G.
5G technology is poised to shift the dynamics in entire industries, with manufacturing expected to be the largest beneficiary. In fact, it will be the driver for Industry 4.0, powered by cloud and edge computing, AI, IoT, robotics, augmented reality, 3D-printing and more, all of which will use 5G technology to allow-machine-to-machine communication.
The experienced difficulties in demand and supply chains and in enterprise operations during Covid-19 have only heightened the importance of digital transformation, intelligent automation and resilient networks, and accelerated adoption of emerging technologies. Industries are starting to realise that the faster they move to such an environment, the more they see a transformative effect on their business.
Rob van den Dam is recognised as a thought leader, lateral thinker and a strategic visionary in the field of telecommunications. He is recently retired as the Global Industry Leader, Telecommunications, Media and Entertainment (TME) of IBM's Institute for Business Value (the business think tank of IBM). In this role, he was responsible for developing strategic TME Thought Leadership and Eminence. As such he contributed to IBM’s global TME strategy. He has over 30 years of experience in the industry. Rob is now owner of van den Dam Telecom Advisory, and counselling companies on part-time basis and active in advisory boards.
Rob is a recognised speaker/presenter – often being invited as keynote speaker – at almost all major industry conferences, such as TMForum, ITU, GSMA, IBC, CommunicAsia, Total Telecom, DigiWorld, Broadband World Forum, World Telecoms Council and the European Commission i2010 Industry roundtable. In the last 15 years, Rob has authored more than 100 reports, articles and blogs. Rob can be contacted at [email protected] and https://www.linkedin.com/in/robvandendam
