Edge computing acts on data at the source
Edge computing is a distributed computing framework that brings enterprise applications closer to data sources, such as Internet of Things (IoT) devices or local edge servers. This proximity to data at its source can deliver real business benefits: faster insights, improved response times and better bandwidth availability.
Gartner estimates that by 2025, 75 percent of data will be processed outside the traditional data center or cloud.¹
Why edge computing?
The explosive growth of internet of things (IoT) devices, and the increasing computing power of these devices, have resulted in unprecedented volumes of data. And data volumes will continue to grow as 5G networks increase the number of connected mobile devices.
In the past, the promise of cloud and artificial intelligence (AI) was to automate and speed innovation by driving actionable insight from data. But the unprecedented scale and complexity of data that’s created by connected devices has outpaced network and infrastructure capabilities.
Sending all that device-generated data to a centralized data center or to the cloud causes bandwidth and latency issues. Edge computing offers a more efficient alternative: data is processed and analyzed closer to the point where it is created. Because data does not traverse over a network to a cloud or data center in order to be processed, latency is significantly reduced. Edge computing — and mobile edge computing on 5G networks — enables faster and more comprehensive data analysis, creating the opportunity for deeper insights, faster response times and improved customer experiences.
Devices at the edge: Harnessing the potential
From connected vehicles to intelligent bots on the factory floor, the amount of data being generated in our world from devices is higher than ever before, yet most of this vast amount of IoT data is not exploited or used at all. For example, a McKinsey & Company study finds that an offshore oil rig generates data from 30,000 sensors — but less than one percent of that data is currently used to make decisions.²
Edge computing harnesses the growing in-device computing capability to provide deep insights and predictive analysis in near-real time. This increased analytics capability in edge devices can power innovation to improve quality and enhance value. It also raises important strategic questions: How do you manage the deployment of workloads that perform these types of actions in the presence of increased compute capacity? How can you use the embedded intelligence in devices to influence operational processes for your employees, your customers and your business more responsively? In order to extract the most value from all those devices, significant volumes of computation must move to the edge.
Your journey to edge computing: Things to consider
Edge computing helps you unlock the potential of the vast untapped data that’s created by connected devices. You can take action to uncover new business opportunities, increase operational efficiency and provide faster, more reliable and consistent experiences for your customers. The best edge computing models can help you accelerate performance by analyzing data locally. A well-considered approach to edge computing can keep workloads up-to-date according to pre-defined policies, can help maintain privacy and will adhere to data residency laws and regulations.
But this process is not without its challenges. An effective edge computing model should address network security risks, management complexities, and the limitations of latency and bandwidth. A viable model should help you:
- Manage your workloads across all clouds and on any number of devices.
- Deploy applications to all edge locations reliably and seamlessly.
- Maintain openness and flexibility to adopt to evolving needs.
- Operate more securely and with confidence.
Key capabilities for edge computing
No matter which variety of edge computing interests you — cloud edge, IoT edge or mobile edge computing — be sure that you find a solution that helps you accomplish the following goals:
Manage the distribution of software at massive scale
Reduce unnecessary administrators, save the associated costs, and deploy software where and when it’s needed.
Leverage open source technology
Leverage an edge computing solution that nurtures the ability to innovate and that can handle the diversity of equipment and devices in today’s marketplace.
Address security concerns
Know that the right workloads are on the right machine at the right time. Make sure there’s an easy way to govern and enforce the policies of your enterprise.
Engage a trusted partner with deep industry expertise
Find a vendor with a proven multicloud platform and a comprehensive portfolio of services designed to increase scalability, accelerate performance and strengthen security in your edge deployments. Ask your vendor about extended services that maximize intelligence and performance at the edge.
¹"What Edge Computing Means for Infrastructure and Operations Leaders," Rob van der Meulen, Gartner Research, October 2018 (link resides outside IBM)
²"The Internet of Things: Mapping the Value Beyond the Hype," McKinsey Global Institute, McKinsey & Company, June 2015 (link resides outside IBM)