Edge computing is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability.
The explosive growth and increasing computing power of IoT devices has resulted in unprecedented volumes of data. And data volumes continue to grow as 5G networks increase the number of connected mobile devices.
In the past, the promise of cloud and AI was to automate and speed up 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 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's created. Because data does not traverse over a network to a cloud or data center to be processed, latency is 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.
From connected vehicles to intelligent bots on the factory floor, the amount of data from devices being generated in our world is higher than ever before, yet most of this IoT data is not used at all. For example, a McKinsey & Company study found 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.1
Edge computing harnesses 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.
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Edge computing helps you unlock the potential of the vast untapped data that’s created by connected devices. You can 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 predefined 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
No matter which variety of edge computing interests you—cloud edge, IoT edge or mobile edge—be sure that you find a solution that can help 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 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.
CIOs in banking, mining, retail or just about any other industry are building strategies designed to personalize customer experiences, generate faster insights and actions and maintain continuous operations. This can be achieved by adopting a massively decentralized computing architecture, otherwise known as edge computing. However, within each industry are particular use cases that drive the need for edge IT.
Banks might need edge to analyze ATM video feeds in real-time in order to increase consumer safety. Mining companies can use their data to optimize their operations, improve worker safety, reduce energy consumption and increase productivity. Retailers can personalize the shopping experiences for their customers and rapidly communicate specialized offers. Companies that use kiosk services can automate the remote distribution and management of their kiosk-based applications, helping to ensure they continue to operate even when they aren’t connected or have poor network connectivity.
Manage and promote security cost-effectively across thousands of edge servers and hundreds of thousands of edge devices.
IBM Power® Systems and IBM Storage solutions put AI models to work at the edge. Unlock insights from live visual data generated at the edge.
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Autonomous management revolutionizes your approach to edge computing.
Edge computing offers a powerful strategy to help alleviate future network congestion driven by new technologies.
Healthcare startup Innocens BV identifies infants at risk of developing sepsis with predictive edge computing.
Footnotes
1"The Internet of Things: Mapping the Value Beyond the Hype" (link resides outside ibm.com), McKinsey Global Institute, McKinsey & Company, June 2015.