How Edge Servers Work

What is the purpose of an edge server? What makes it unique from standard servers? What are the benefits? In this article, we’ll address these and other questions.

When paired with hybrid computing, the edge server allows businesses to analyze data much closer to the customer – in the store, hospital, or connected vehicle. Edge servers do many of the same functions as traditional servers but from a different location.

Edge servers operate similarly to standard servers. Because they are located on the “periphery” of the network, their server requirements are typically varied.



The processing and other resources required to run apps are provided by the edge server. “Edge” simply means that it performs this function as close as feasible to the application and its data, as well as to the humans or machines who utilize such applications.

Edge servers are servers that are positioned outside of a traditional data center to handle compute, networking, storage, and security functions close to where users need them, such as in a hospital or manufacturing plant.

A centralized technique for delivering these resources makes sense for many enterprise applications and other use cases. This isn’t necessarily the most efficient approach in the increasingly dispersed consumption of technology, both in IT and in everyday life. In this situation, we’ll need to consider IoT, 5G, and AI.



Edge computing enhances IoT and mobile devices by bringing server resources as close to the almost infinite number of connected devices, applications, and data they generate as possible. Latency, cloud provider performance, and other issues are reduced with the edge approach.

For business, public, and individual consumers, this usually means improved service. More severe security measures are frequently used. Consumers will be concerned about security and privacy, therefore all of this will become more important as IoT data volumes from applications like smart cars and medical devices proliferate.



In its most basic form, an edge server is a server that sits between (and communicates with) two separate networks.

Consider the following interaction between a consumer (you) and a company (your bank): To check your latest transactions, simply go into your online banking account. For obvious reasons, a bank or other financial institution is unlikely to want to share their entire backend online to meet this common client desire. In this case, the edge server is used.

The bank exposes an edge server to the Internet in order to provide the website to the end-user. The same edge server pulls data from the core internal banking systems that do not have a direct internet connection. Edge servers allow a corporation to expose a much smaller percentage of its environment to outside networks, lowering the risk of security breaches.

Edge servers are sometimes built to fulfill more stringent requirements than traditional servers, especially when their primary goal is to better support extremely specific use cases like industrial sensors or networked surveillance cameras.

For use cases like telecom network activities that need services closer to customers, edge computing helps overcome fundamental challenges relating to bandwidth, latency, fault tolerance, and data sovereignty. In a hybrid computing model, centralized computing takes care of resource-intensive workloads, while edge computing takes care of jobs that require near-real-time processing.

Today, edge servers are meeting this vital requirement, and they will do so even better in the future.



While some may say that 5G networks are already available, we’ve only begun to scratch the surface of their potential impact and the important role of edge servers in 5G performance. Edge servers help carriers handle 5G traffic appropriately. They are situated near cell towers and handle streams of data from “smart” cars and cameras.

Artificial intelligence and machine learning are other growing drivers for edge computing. Because of the cloud’s massive computational capability, it’s becoming a popular choice for training AI/ML models that would otherwise overwhelm most companies’ on-premises systems. A cloud edge server can assist in the distribution of workloads between the cloud and on-premises resources.

A cloud edge server can be used to obtain previous insights or extract models for use in real-time on-premises data analytics. The AI/ML scenario is an incredible example of how edge servers can be used to centralize large computational workloads. A local edge server with a cloud-trained model allows a corporation to analyze local data in real-time without transferring vast amounts of data to the analysis location.



Edge and hybrid computing go hand in hand with AI applications and many other use cases, hence hybrid cloud architectures becoming more popular.

Edge has become one of the most important drivers of hybrid cloud because it is clearly a hybrid approach to computing.

The “suitable tool for the job” (or “proper workload for the right environment”) idea applies, much as it does with hybrid cloud. In hybrid cloud architecture, edge servers can improve performance and reliability by orders of magnitude. Edge computing has the ability to increase enterprise performance as a result.



In terms of reliability, moving server functionality closer to end-users (through edge servers) allows you to have additional points of presence (or actual server locations) nearby. Under the old paradigm, if the closest server breaks for any reason, the next point of presence could be rather far away (resulting in poor performance). With more edge servers in close proximity, even failures can be greatly reduced.

Edge computing can move application execution to the closest point of presence, reducing interruptions while maintaining high-speed performance. By locating application data as close to end-users as feasible, you can provide a faster experience with fewer loading screens. This is edge’s main advantage for users.

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Written by Helen Wilson

Helen Wilson is a professional content writer. Her main spheres of specialization are IT and Business. She also studies topics about psychology and health and provides a “pay to get an essay written” service for students.

June 8, 2022

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