What is edge computing and why is everyone talking about this new approach to network architecture? As many companies become cloud native in their deployments, they also realize that the cloud does not have the real-time response that is necessary to support crucial workloads. High latency is also unavoidable with public cloud, which is where edge computing can step in to solve these problems.
What is edge computing? Everybody is talking about it as being the emerging computing paradigm that will change the information technology landscape as we know it and will witness unprecedented adoption in the next few years, according to this report by Gartner.
Edge computing is a distributed computing model in which data is processed and analyzed closer to the physical location where the actual data is obtained, instead of on the cloud or on centralized servers. The data is generated and simultaneously processed on devices and networks in close proximity to users. When you process data on the edge, you can process enormous amounts of it at greater speeds and you also tackle problems like high latency. Edge computing also helps you to extrapolate more powerful, action-backed insight, all in real time. The number of devices connected to the Internet and the amount of data traveling through networks are growing by the day, and traditional data center infrastructures cannot bear the load singlehandedly.
Gartner predicts that by 2025, 75% of data will be processed outside centralized data centers – in other words, on the edge.
Picture this – in a regular client-server computing setup, if you want to record and mine customer data, the data is produced in the customer’s mobile or computer, and then moved through the Internet to an enterprise data server. The data is then moved across a wide area network, either a LAN or the Internet, and then processed by an enterprise application, which then sends the results back to the client endpoint. With edge computing, you are moving away from data centers and virtualizing network services over WAN networks. Both data storage and processing are taken to the very point where data is being generated, thereby reducing response time and benefitting end users in the process. Edge computing spans everything from basic event filtering to more layered, complex data processing tasks.
Edge computing technology eases the pressure and the risk of transferring huge amounts of data. Data loads often congest wide area networks like the Internet, which are already strained. It is therefore risky to place so much data and so many computing resources in specific locations that are often hundreds, sometimes thousands of miles away from the customers’ locations. By distributing the load and shifting focus to the edge of the infrastructure, you can get real-time insight at the very different endpoints where data is being generated.
Edge computing and its many use cases
Here’s an example. The automotive industry is one of the biggest industries to benefit from the edge computing revolution. Autonomous vehicles produce more than 40 TB of data an hour and this is necessary for them to operate reliably. The potential for delays when sending such high volumes of data to the cloud is huge, and traditional, centralized systems do not come close to processing the sheer volume of data generated. From Advanced Driver Assist Systems to adaptive and preventive vehicle maintenance, the automotive industry is a top candidate for edge computing.
Another example is the Internet of Things. With IoT technology, data processing that takes place at or near the source of the actual data. This data processing happens through networks and data centers that are decentralized and are sourced using sensors and embedded devices.
Edge computing solutions come in big and small sizes. They can power smart cities but there are so many examples that you may already be using every day. A simple wearable that monitors your health is an example of edge computing in its most essential form because it records data like heart rate and processes this data, with no reason to connect to the cloud. Edge computing solutions extend to larger uses like manufacturing plants, hospitals, and oil rigs.
There are so many reasons why edge computing will grow at an exponential rate. Cloud computing offers enormous benefits but its solutions are not easily affordable. Edge computing solves cloud computing’s pressing problems and will enable organizations to save costs without compromising on adopting the best technologies available in the market.
The explosion of VR and 5G will only take edge computing further. Everything from smart cities and self-driving cars to AI and VR will need the fast processing and lightning speed response time that only edge computing solutions can provide. Another example is Italy’s first 5G based edge offerings, which is being developed by the Italian communication service provider (CSP) TIM and Noovle, in association with Google.
Edge computing is also used extensively in remotely monitoring assets in the oil and gas industry and for preventive maintenance. Oil rigs and gas plants are located in remote areas. This means that instead of relying on uncertain network coverage, data analytics is carried on in real-time and close to where the asset is located.
The power industry is also set to be disrupted by edge computing solutions. With increasing grid complexity, there is a need to generate and store energy in a better, more efficient, and distributed way. When you process the operational technology (OT) data generated from the assets located near the grids, there is less pressure on the network to support the huge amounts of OT data that has to be sent to data centers.
Why a decentralized approach is necessary
You must have heard of Web 3.0 and its huge impact on the future of businesses. The first version of the Internet was Web 1.0, with its static websites and siloed content with no scope for interaction. Around 2004, we found ourselves in Web 2.0 and its centralized Internet architecture, but with more interactivity. We could find ourselves in the Web 3.0 era in a matter of few years. Web 3.0 will have a decentralized architecture and diverse computing concepts that will simultaneously run on integrated stacks. Blockchain and edge computing are important technologies operating in Web 3.0.
To show you just how much edge computing can become as mainstream as cloud computing, Gartner’s report states that “around 10% of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2026, Gartner predicts this figure will reach 75%.”
There are many reasons why a different kind of decentralized approach is necessary. When data processing and storage takes place in centralized data centers, it is difficult to gather real-time insights and take localized actions on critical data. When you move data storage, computing and processing functions towards the data sources themselves and at the edge of the network, you reduce latency and you can also process huge amounts of data quickly, especially data that leverages new age technologies like AI, AR, and VR.
The data explosion prompted companies to migrate to the cloud and to multi cloud but we are moving towards a world where we are operating with limited infrastructure, huge amounts of data processing needs, and rising costs. To combat these problems, we need a modern, decentralized approach and architecture that can take on the data that is coming in and its speed. Added to this, data security and privacy issues can cause problems and potentially huge revenue losses.
Edge computing does have its own challenges. The cost of deploying edge computing environments can pile up but there are other possible solutions, including creating edge computing server clusters whenever you need more computing power locally. With edge computing in the IoT space, scalability can be a problem, even as new IoT sensors and devices generate too many endpoints to manage.
Having said that, decentralization is one of the few possible solutions to tackle the biggest network problem that we currently face – how do we move and process the huge amounts of data and how do we address the problem of response time.
Cloud computing has helped companies push the boundaries of technological achievements but there are a few drawbacks. High latency is unavoidable with public cloud. Cloud providers tackle the problem of rising costs by setting up data centers at half the investment in remote places that are usually far away from the customers’ locations. This poses a problem. When data is generated a great distance away from the data center and at multiple endpoints, it is enormously difficult for the public cloud to handle these workloads due to distance. Also, cloud computing involves resource sharing and this too slows down the speed of data transmission and processing. For performance-sensitive workloads, this can spell trouble.
How edge computing can solve the cloud’s problems
Edge computing is the next phase in the evolution of cloud computing. It offers developers and service providers the benefits of cloud computing capabilities but with something else – a more distributed network and a robust, consistent operating paradigm that operates across different infrastructures. No doubt, cloud computing is also about distributed computing, with the data storage resources and processing points being located away from the data source but there is a key difference between cloud and edge computing. Cloud computing can process data close to a data source but not at the network edge.
Companies also deploy edge computing solutions to save on costs, seeing as the high-bandwidth costs in cloud computing can add up significantly. Edge computing offers a cost-effective alternative. When companies need to work on tasks that require short response times, they opt for edge computing. Another huge benefit of edge computing is that it offers pre-emptive, real-time data insights, which can be used to solve issues even before they happen.
Speed and high response time are critical for most companies, especially ones that rely on data-backed decisions. High latency can be a huge problem with cloud computing and the edge computing architecture can avoid the latency caused when data is being transmitted from the device and across the network to the centralized data centers. With increased network performance and high-bandwidth, companies can double their pace and productivity.
When data processing is done on the peripheral devices, there is a lower risk of interruptions and breakdowns, especially in edge solutions that are deployed in remote areas where network coverage is limited.
Edge computing complements cloud computing and transforms it, taking it to the next level. There are a few edge devices that cannot analyze data and in such cases, analytic models and parameters are created on the cloud before they are sent to edge devices. This proves that while edge computing is but a natural evolution of cloud computing capabilities, and both are important and independent of each other.
Security is another area where edge computing scores over cloud computing. With edge computing, you can vet and pre-process sensitive data and confidential information right at the source instead of risk sending it to a central data center. Another advantage of edge computing and a decentralized approach is that because of a distributed computing paradigm, one security breach will not affect other devices and connected data centers.
With edge computing, there is greater network reliability because you process data locally. Even if there is a downtime, you can re-route the data from the IoT edge device and send it to your end-users.
How you can prepare your organization to handle edge computing in the future
If you want to prep your company for edge computing adoption, here’s where you can start.
Review your IT assets and get set for 5G: To prepare your network infrastructure for edge computing, build an infrastructure that can support different edge use cases. This infrastructure must complement your existing multi cloud applications. Start by shifting your IT infrastructure away from hardware-based networks and update your IT infrastructure and networks for 5G. Move to network function virtualization (NFV). This is when you replace your physical network with a virtualized network. Shift your IT infrastructure to software-defined networking (SDN) technologies to keep prep your networks for high data capacity and to make them more agile.
Prioritize security: One of the biggest challenges that your organization will face is to establish security in an edge deployment, the same security that you will enjoy in a large data center.To avoid the risk of a data breach, evaluate your security needs. Switch to a secure access service edge (SASE) solution, a cloud-based cybersecurity concept that Gartner states is a key edge technology to adopt in the coming years. SASE is delivered directly to edge devices and combines networking and security services.
Understand business needs before putting together your infrastructure: Edge computing has huge potential in different industries, with mobile devices and laptop being the top contenders. Evaluate your business needs before putting together your edge device infrastructure.
Run prototypes and look for the right service providers: You may also start to look for the right edge computing service provider. This is still a recent technology, which means that most existing providers have only been working on it for a few years. Run prototypes and make use of trial periods before you choose your vendor and take a cautious approach to selecting one. Another idea is to deploy only a portion of your computing to the edge. Also, adopt compliance strategies, as there are international compliance laws that you need to take into account before making the shift to edge computing.
Edge computing is touted as a technology game changer. Beyond its exciting new network architecture that will break down the barriers of traditional cloud-based networks, edge computing will help companies harness the power of data and transform their future.
