Edge Computing vs. Cloud Computing: Differences and Use Cases

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. The following article defines key concepts in cloud computing and edge computing. You can use it to draw comparisons, identify major differences, and build a stronger overall understanding of each type of computing.

Edge computing vs. cloud computing

When comparing cloud vs edge computing, it can be helpful to remember 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 organization 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.

Read more: What is Cloud Computing? 15 FAQ for Beginners

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 can be any hardware that manages the boundary between two networks. They can be considered gatekeepers controlling the data flow between service providers and users. WiFi routers are an example of an edge device.

• Edge data centers are smaller data centers located near a network's edge. 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 center, such as a company’s local area network (LAN), via the Internet. It’s stored and processed there before being reflected back to the client’s endpoint. This process can be time- and resource-intensive, especially in organizations that handle large amounts of data.

Key components of cloud infrastructure

Cloud computing refers to delivering 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 or centralized data centers. Here is a brief explanation of a few crucial aspects of cloud computing:

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

Read more: Intro to Cloud Computing: IaaS vs PaaS vs SaaS

• IT resources. IT resources and infrastructure comprise a set of hardware, software, networks, and processes designed to support an organization's technical needs. As IT infrastructure, cloud computing systems enable users to access computational resources from remote locations via the internet. This process is called virtualization.

Read more: What is ITIL? A Beginner’s Guide to the ITIL Process

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). 

Advantages of edge computing

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

Use cases for edge computing.

• Self-driving cars. 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 manage vehicle traffic intelligently. For example, edge devices in traffic signals can help adjust light timing to streamline traffic flow 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 such as motion detectors and cameras that initiate disaster recovery in real time by alerting homeowners and law enforcement.

Advantages of cloud computing

For several reasons, cloud computing is often the method of choice for enterprise-level businesses. First, it is cost-effective. Many types of cloud models allow companies to customize their IT infrastructure, meaning they can pay for only the services they need. Scalability is among the most notable benefits of cloud computing because it allows expanding to accommodate future requirements. Additionally, growing organizations with many members requiring access to IT resources can benefit from the collaborative nature of cloud technology.

Use cases for cloud computing.

• Health care documentation. In the medical field, cloud computing enables health care 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. Many educational institutions offer online learning today. 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 easily.

Keep learning about computing infrastructure with Coursera.

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 you need 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.