Data is the blood of businesses today, offering valuable insights towards controlling processes and operations. You see, most people still use PCs for accessing centralized services such as DropBox, Gmail, and Office 365. Also, devices such as Amazon Echo and Apple TV get powered by cloud content and intelligence. Now, in 2021, the conversation has progressed towards yet another phenomenon, edge computing.
Edge computing is a distributed computing framework. It brings enterprise applications closer to the data sources. This proximity to data helps deliver benefits such as quicker insights, improved response times and faster bandwidth. In simple words, edge computing works around the geographic distribution of data. The computing happens at or near the source data.
Instead of transmitting raw data to a central data centre, edge computing processes the data to where it gets generated. For instance, sales data gets processed at a retail store and the production volume data at the factory floor. However, the central data centre now becomes a storage space for real-time business insights, equipment maintenance predictions or other actionable answers.
Edge computing is a strategy! Today, edge computing has varied applications, including telecommunications, transport, and utilities.
Example
Take, for instance, the gamut of connected vehicles. Buses and trains rely on computing power to track passenger flow and service delivery. Now, delivery drivers can find the fastest, efficient routes using the technology onboard. What this does is makes the services more timely and reliable.
The gamut benefits both users and enterprises. The former gets to enjoy greater convenience and speed. As for the latter, edge means low-latency and highly available applications with real-time monitoring. Another aspect is shorter loading times.
One might ponder about sensitive information and data as well. Well, edge computing also renders better control for confidential data. It does so by keeping all the computing power local. If you have ever wondered why companies enforce security practices or conform to regulatory policies, this is it.
Taking the higher stance
Edge computing helps considerably in conducting on-site big data analytics and aggregation. It places a lot of emphasis on data-sensitive intelligent applications. Tasks related to AI or ML, such as image recognition algorithms, run efficiently when close to the source.
Although it sounds easy, edge computing has its challenges. At the outset, an effective model should help in:
- Managing workloads across all clouds and on multiple devices
- Deploying applications to all edge locations in a reliable and seamless manner
- Maintaining flexibility towards evolving needs
- Operating securely and with confidence
According to Gartner, by 2025, about 75 per cent of enterprise-generated data gets created outside of data centres. The movement of voluminous data is strenuous on the global internet and is subject to congestion and disruption. What’s more, edge computing continues to evolve with new technologies and practices such as 5G and Wi-Fi 6. These will affect edge deployment in the coming years, enabling virtualization and automation capabilities.
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