When one thinks about the modern cloud environment, the first thing that comes to mind is speed and reliability. With centralized data analysis, a faster bandwidth connection, access of data is faster. Speed and accuracy is the need of the hour and the collection of data from the organization's environment is continuous and centralized.
But, Is it necessary for the data from all physical devices to be centralized?
For instance, imagine numerous devices scattered around an organization's physical IT environment. They may be used to carry out a range of tasks such as identification, counting, measurements and so on. Many of these are IoT devices, which pile up data over time as they are used. While IoT devices are labelled to be 'data rich', most of the continuous stream of data need not travel to the centralized repository of the cloud.
What does this mean for cloud computing? Is there an optimal way of reducing the paths traversed by data building up over time? That is exactly what edge computing technology is used for, to collect, process and filter the data "in place" or near the network edge.
What is edge computing?
The cloud architecture is suited for the tasks of the modern IT workspace. However, given the abundance of physical devices used in the IT environment today, edge computing has emerged as a modern, and more feasible and important architecture. Rather than having all the data allocated at the cloud, edge computing helps deploy storage resources closer to the physical location of the device.
So, how is this helpful? Given the number of interactions we have with physical devices, this reduces the need for data to traverse all the way until the central repository. Edge computing puts compute and storage at the same point and the data source at the network edge. It helps deploy computing and storage resources at the location where data is produced.
How does edge computing work?
In simple terms, edge computing is all about having the data processing, right at the data source. Edge computing takes infrastructure into account, and focuses on data being near the infrastructure, rather than a central data hub. Given the current amount of data generation, the volume of data being produced may be too much for traditional data centers to accommodate over time.
Hence, with edge computing technology one can shift the focus to keeping the data where the resources are. The idea of edge computing is as similar as having hardware as a data collection platform, right beside the device. This is applicable in resources where it is more efficient to have the data collection right at the computing source rather than have it at a centralized location.