From Cloud to Edge
Automation is gradually displacing every possible manual task and the progress in the field of connected services have caused a massive storm of data.
But do we know where is this data processed and stored on a large scale?
There are massive storage and processing farms called Datacenter's which host, store and process massive bulk of data and software’s.
The Data centers which are located in a remote location and host software, storage and processing services are also termed as "Cloud" in modern day nomenclature.
It’s interesting to note the transformation of the Datacenter architecture based on industry trends.
Conventionally, all the Datacenters are present in a secured and remote location and all the connected services and cloud is hosted in these Datacenter’s. There are typical hub rooms or switches which will distribute the nodes from the Datacenter to the user end and all the IP (Internet Protocol) devices are connected via them.
But, this typical Data center architecture was sufficing the purpose of the conventional hosting and computing applications only until we started connecting more and more IOT (Internet of Things) enabled devices which requires nodal level computing.
The growth of more and more IOT devices gave birth to the term called “Industry 4.0”. During this era of Industry 4.0 the focus is on increasing IOT devices, Sensors and integrating it with more advances software’s having Artificial Intelligence and Machine Learning algorithms. The whole purpose is to automate every possible domestic and commercial business like smart homes, smart factories, and autonomous vehicles and make the data available at the tip of the finger.
This nodal level increase of computing requirement to reduce the latency has given birth to a new Datacenter architecture called “Edge Computing”.
Edge computing refers to data processing power at the edge of a network instead of holding that processing power in a cloud or a central Datacenter. Edge Computing is pushing the frontier of computing applications, data, and services away from centralized nodes to the logical extremes of a network. It enables analytics and knowledge generation to occur at the source of the data. This approach requires leveraging resources that may not be continuously connected to a network.
An edge device could also be an autonomous car, shop floor machinery , ATM (the bank wants to stop fraudulent financial transactions); a smartphone; a gateway device that collects data from other endpoints before sending it to the cloud,etc.
Edge computing does not replace cloud computing. However, in reality an analytic model or rules might be created in a cloud then pushed out to edge devices. Some edge devices may also be incapable of doing analysis and might depend on cloud. Edge computing is also closely related to "fog computing," which also entails data processing from the edge to the cloud.
It’s interesting to see in future where do we progress with data? We started from single computer level data computation, then moved to cloud and now its again nodal level computing. Will the future be a hybrid of cloud and Edge or only Edge is going to dominate the data world like primitive PC(personal computer) days.
