Edge Computing vs Cloud Computing: Differences and Use Cases

Written by Coursera Staff • Updated on

Compare, contrast, and identify real-world applications of edge and cloud computing.

[Featured Image] A person in a light blue button-down presents data to their coworkers using insights gleaned from edge computing technology.

In computing, the term edge refers to a range of devices and networks that are physically close to the user. In contrast, the cloud is an expansive, global network of remote servers. Each has different uses, features, and strengths.

Discover key concepts in cloud computing and edge computing, which can allow you to draw comparisons, identify major differences, and build a stronger understanding of each type of computing. 

Edge computing vs cloud computing

When comparing these two computing types, it's helpful to know that they are not interchangeable technologies. Their differences position them to be the best solution for specific requirements. In other words, it's unlikely that an organisation would switch from one type of computing to the other unless the type of data it's managing has changed. The next sections provide a brief overview of both types of environments. 

Key components of edge infrastructure

The primary goal of edge computing is to reduce the amount of resources the data management process requires by shifting storage and computing resources closer to the point where data is generated. Edge infrastructure typically involves the following:

  • Edge devices: An edge device can be any type of hardware that manages the boundary between two networks. You can think of them as gatekeepers that control the flow of data between service providers and users. WiFi routers are an example of an edge device. 

  • Edge data centres: Edge data centres are smaller data centres located near the edge of a network. They can deliver cloud computing resources to edge devices. 

Edge computing vs on-premise

In enterprise on-premise computing, data is produced at the client’s endpoint. An endpoint is any device that connects to a computer network and exchanges information, like a laptop. From this endpoint, data must move to a private data centre, such as a company’s local area network (LAN) via the internet. There, it’s stored and processed before being reflected back to the client’s endpoint. This process can be time and resource intensive, especially for organisations handling large amounts of data. 

Key components of cloud infrastructure

Cloud computing refers to the delivery of computational resources like data storage via the internet. Unlike edge and on-premise computing, cloud infrastructure is software-based and doesn’t rely on physical hardware. Explore this brief explanation of a few crucial aspects of cloud computing:

  • Cloud services: Cloud service providers offer businesses and individuals the tools and software they need to sustain a cloud system. Cloud computing services can include networks, cloud servers, and cloud platforms on which users can access and manage data. Cloud computing solutions are often categorised into the following categories: IaaS, PaaS, SaaS, and FaaS (or serverless). 

  • IT resources: IT resources and infrastructure are made up of a set of hardware, software, networks, and processes that are designed to support an organisation's technical needs. As IT infrastructure, cloud computing systems enable users to access computational resources via the internet through a process called virtualisation.

Edge deployment vs cloud deployment

In the context of computing, deployment refers to the installation or launch of a new system. Edge deployment includes edge device installation and edge network administration. Cloud deployment is the implementation of a cloud hosting model (such as SaaS). 

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Advantages of edge computing

When researching the benefits of edge computing, you're likely to encounter the term latency. With regard to edge computing, network latency refers to the amount of time it takes for a data packet to travel from one place to another. These insights make it easier to determine performance indicators like a website or application’s load time. Low latency is a significant benefit of edge computing. In situations where real-time data processing is crucial, edge computing can be the most suitable solution because it requires less processing time and resources for a more consistent overall user experience.

Use cases for edge computing

  • Self-driving cars: In order to operate autonomously, self-driving vehicles must be able to collect and process data in real-time. This data includes speed, traffic analytics, and location. Autonomous vehicles contain edge devices in the form of onboard sensors and cameras that can transmit data nearly instantaneously. 

  • Traffic management systems: Edge computing is often used to intelligently manage vehicle traffic. For example, edge devices in traffic signals can help adjust light timing to streamline the flow of traffic by collecting and processing data about congestion.

  • IoT devices: Internet of Things (IoT) devices can be many different types of smart devices, ranging from thermostats to heart monitors. In many cases, they rely on edge computing technology due to the sensitivity and urgency of the data they monitor. For example, home security systems may include edge devices in the form of motion detectors and cameras that initiate disaster recovery in real time by alerting homeowners and law enforcement. 

Advantages of cloud computing

Cloud computing is often the method of choice for enterprise-level businesses for a few reasons. First, cloud computing is cost-effective. You’ll find many types of cloud models that allow companies to customise their IT infrastructure. This customisability means companies can only pay for the services they need. Scalability is among the most notable benefits of cloud computing because it provides the option to expand to accommodate future requirements. Additionally, growing organisations with many members requiring access to IT resources can benefit from the collaborative nature of cloud technology. 

Use cases for cloud computing

  • Healthcare documentation: Cloud computing is used in the medical field to enable healthcare providers to access pertinent records like medical histories from anywhere. Since these records are stored and managed electronically, the time and resources it takes to share and process information is greatly reduced. 

  • Online education: Currently, many educational institutions offer online learning. In part, these services are made available through the use of public clouds and file-sharing solutions like Google Cloud and Dropbox.

  • Software development and testing: Cloud technology facilitates DevOps processes by increasing collaboration and visibility among team members. Cloud computing platforms also often include tools and services that enable developers to create testing, development, and production environments with ease. 

Keep learning about computing infrastructure with Coursera. 

Edge computing and cloud computing have different features and purposes, so you won’t use them interchangeably but rather choose one based on the type of data you use at your company. You’ll find that both have certain advantages. 

If you’re new to the field, consider an introductory, self-paced online course like Introduction to Cloud Computing by IBM. You’ll be introduced to leading cloud service providers and gain the fundamental knowledge necessary to understand cloud computing from a business perspective. For intermediate-level learners, consider challenging yourself with the University of Colorado’s Computer Communications Specialization, wherein you can learn to apply networking theory and design principles.

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