Highlights
- Technological developments such as autonomous robots, self-driving cars, and automated retail experiences await breakthroughs in edge computing.
- Processing sensitive data at the edge improves reliability and safeguards privacy.
- Unique workloads and data characteristics are pushing processing to the edge, such as the small window of opportunity when decision-making is critical and latency should be minimized.
In this article
Reducing latency
Edge computing - the next frontier in digital transformation and innovation
Edge computing is the next frontier in digital transformation and innovation for organizations leveraging high-volume data faster in real-time. Find out where it’s headed and how verticals are embracing it.
The world is on the cusp of a paradigm shift. Technological developments such as autonomous robots, self-driving cars, and automated retail experiences await breakthroughs in edge computing, which are gradually getting there. The tremendous real-time data is about to be leveraged for cutting-edge innovation.
Gartner defines edge computing as “part of a distributed computing topology where information processing is close to the edge, where things and people produce or consume that information.”
Edge computing reduces latency and bandwidth use and minimizes processes in the cloud, moving them to a node, an edge server, or an Internet of Things (IoT) device.
Around 2025, organizations will accelerate digital transformation by building autonomous vehicles, using IoT devices in homes, offices, and cities, creating high-res content for 360-degree videos and leveraging augmented reality and 5G communications.
Sending data generated at such volume and speed to a centralized data center or cloud can lead to bandwidth, latency, and energy issues. The edge enables real-time processing and allows devices to make data-based decisions instantaneously, forming the bedrock of any innovation.
Edge computing, combined with technologies such as AI, can help find patterns in data, support ML and drive decision-making in real-time.
Why edge computing?
Optimal for data that is gigantic, noisy, and expensive to route
The core drawbacks of the cloud are low availability and long response times, which form the premise for edge computing. Edge computing shifts computing resources to the location of data creation, or the edge of the internet, to lead to real-time speeds, high availability, flexibility and resiliency, and improved data consistency.
Dave McCarthy, research vice-president for cloud and edge infrastructure services at IDC, points out the shift in mindset from “anything and everything should go to the cloud, to ‘Let’s use the cloud for what it’s good for, and use other things when they make more sense.’”
Gartner believes that the surge in edge computing and data management is driven by three distinct components: the end-user, the networking layer, and the computing place. The emerging edge and cloud infrastructure need a distributed network that optimizes latency and bandwidth consumption while staying reliable and secure.
Unique workload and data characteristics are pushing processing to the edge, such as the small window of opportunity when decision-making is critical and latency should be minimized, when the data is gigantic, noisy, and expensive to route, when interactions are confidential or regulated and when the processing must continue even if the connection is weak.
For instance, human-centered experiences will form the core of the retail industry. A hiccup-free store checkout could be one of the leading use cases of edge in retail. On-site cameras use AI to recognize inventory items, an edge network processes them, and customers can walk past a kiosk that charges their accounts and renders ‘waiting in line’ a thing of the past.
Edge computing alongside 5G technology will address bandwidth, security, and speed issues for networks with sudden traffic surges. The time is ripe for edge computing to realize commercially as organizations look at faster moving data and heightened infrastructure expectations to fulfill customer demands.
Enterprises must prioritize a distributed cloud-based solution as default and future-proof edge solutions by relying on partnerships and ecosystems over a single-vendor approach
Advantages
Data processing at velocity with cost savings and improved security
Here are the benefits of edge computing Gartner cites in the Planning Guide for Cloud and Edge Computing:
Cost savings - Edge data systems warrant lesser investment in hardware and maintenance and enable steady scaling to account for any growth in the demand cost-effectively. As it becomes increasingly costly to support legacy applications, making a case for traditional data centers will be harder.
Emerging technologies - Edge allows data processing at velocity, enabling sensors and robots to make hyper-quick decisions and supports the evolution of the IoT and newer application types, revolutionizing everything from autonomous vehicles to assembly-line quality checks.
Improved latency - In cases like self-driving cars and remote telesurgery, there is a little window for latency. Edge fulfills requirements for extremely rapid turnarounds in real-time.
Better security - Processing sensitive data at the edge improves reliability and safeguards privacy. In cases such as wearable health devices, regulated data can be processed locally, meaning securely.
The story in numbers
Applications
Edge computing will drive innovative solutions across industries
The low-latency and blazing speed available through 5G networks and real-time insights from edge computing will drive innovative solutions across industries:
Manufacturing - Industry 4.0 relies on intelligent automation to achieve the next levels of interconnection in plant floors and communication in ecosystems.
Supply chains - Suppliers get empowered to respond quickly to volatility in demand through real-time, insights-led, just-in-time supply chains.
Healthcare - Real-time processing and automated AI apps bridge the gap between care providers and remote patients in real-time.
Field workforce - Edge-enabled devices allow field workers to access secure corporate data even in disconnected locations.
Logistics - Edge-powered fleet management allows optimizing load, mode, and routes to balance workloads and manage last-mile logistics.
Autonomous vehicles - AI processing localizes quick data digestion and autonomous decision-making in automobiles, extending use cases to mining, oil and gas exploration, and other industrial product applications.
What's next
The impact of edge computing could be profound on innovation, productivity, and user experience.
The worldwide enterprise and service provider spending on edge software, hardware, and servers is expected to hit $176 billion in 2022, a 14.8% increase from 2021 and is anticipated to reach $274 billion by 2025.
Gartner predicts that 75% of enterprise-generated data will be created and processed outside the traditional settings of cloud or data centers by 2025. According to Santhosh Rao, senior research director at Gartner, “As the volume and velocity of data increases, so does the inefficiency of streaming all this information to a cloud or data center for processing.”
According to Market Research Future, the global edge computing market will reach $168.59 billion by 2030, growing at a CAGR of 24.51% between 2020 and 2030.
“Edge computing is broad enough to support many submarkets, but it will evolve from supporting thousands of custom patterns to merely dozens, with cloud providers taking an important role to the edge or complementing edge solutions. Enterprises must prioritize a distributed cloud-based solution as default and future-proof edge solutions by relying on partnerships and ecosystems over a single-vendor approach,” says John McArthur, senior director analyst at Gartner.
The impact of edge computing could be profound on innovation, productivity, and user experience.
