Edge Computing vs. Cloud Computing Explained
Edge computing and cloud computing are two opposite approaches within the same computing continuum.
Cloud computing processes all your data in a fully managed, centralized server. Whereas edge computing processes local data in the closest available decentralized server.
Comparing edge computing vs. cloud computing will help you adopt the best approach for each use case.
The Cloud Offers Scalable, On-demand Computing Resources
Cloud providers aggregate computing resources, package them into scalable modular units, and deliver them via the internet to paying users. These on-demand computing resources, such as processing power, memory, and storage, allow you to quickly deploy your applications without any infrastructure management.
As a result, increasingly more businesses are beginning to adopt cloud computing infrastructure. In a recent Harvard Business Review report, The State of Cloud-Driven Transformation, 81% of respondents say that the "cloud is very or extremely important to their organization's future strategy and growth."
Benefits of Cloud Computing
No infrastructure management: IT teams that adopt cloud infrastructure don't need to install or configure new, on-premise servers as the scale of their data operations grows. Because cloud providers offer a service-fee-based model, users avoid expensive, upfront capital investments.
Scalable, pay-per-usage pricing: The flexible, usage-based pricing of cloud computing makes it the most scalable solution. Because users only pay for the resources they use, over- or under-provisioning resources is no longer a problem.
Accessibility and availability: Any user with an internet connection and valid login credentials can access resources from a cloud computing platform. Cloud computing also automatically backs up multiple copies of all your data and stores them across multiple locations. Thus, reducing chances of data downtime or loss.
Limitations of Cloud Computing
Internet connectivity: Since all cloud computing services are delivered online, you can't access the cloud platform or its resources without an internet connection.
Security threats: In general, most cloud providers offer enhanced security. But you're susceptible to bad actors using brute force methods and man-in-the-middle attacks to gain unlawful access.
Vendor lock-in: When you build your application with a particular cloud provider, you risk facing difficulty while migrating your entire application to another platform later on.
Edge Computing Offers Low-latency Times and Better Security
Unlike cloud computing, edge computing relies on the server nearest the data source to process much of the data locally. As a result, you significantly reduce the time and distance required to transfer data between edge devices and the edge server. So, edge computing offers better performance for time-sensitive, mission-critical applications.
In fact, NASA is adopting edge computing to make decisions locally on intelligent edge servers to minimize data transfer delays in space exploration. For instance, it takes over 11 minutes for a radio signal from Mars to reach a data center on Earth because it has to travel 140 million miles. But in the event of a fuel shortage or system failure, a space mission can't afford such time delays.
To reduce time delays in analyzing new infromation, NASA is installing small edge devices on spacecrafts and satellites. These devices ingest data of terrain images, gas collections and core samples. The edge devices also run light-weight machine learning (ML) models that provide instant decisions, in space, without sending any data back to Earth.
Edge computing is also used in time-sensitive applications such as banking, autonomous vehicles, manufacturing, retail, and healthcare. For example, businesses are already using a chat provider with edge infrastructure to reduce in-app chat latency rates by up to five times.
IDC predicts a double-digit growth rate of investments in edge computing and has identified over 150 edge computing applications.
Benefits of Edge Computing
Low-latency rates: Edge servers that process data are located near edge devices that generate data. This eliminates the need to transfer data across long distances. And as a result, edge computing has far lower latency rates when compared to cloud computing infrastructure.
Real-time data analysis: Edge computing infrastructure uses a number of small microprocessors to process and analyze data within the edge of the network. When combined with lower latency rates, this leads to better network response times and enables real-time analysis of data.
Data security and privacy compliance: Because data is stored and processed locally within an edge perimeter, you don't need to send sensitive data to the cloud. This reduces the chances of cyberattacks and data breaches. A smaller footprint of sensitive data also makes compliance with privacy laws easier.
Limitations of Edge Computing
Higher infrastructure costs: Edge computing often needs more advanced infrastructure with more storage, memory, and processing capacity. Thus, increasing your overall infrastructure costs.
Potential data loss: Accidents and unforeseen events can destroy locally stored data. It is difficult to recover lost data because, unlike cloud computing, edge infrastructure isn't built to store multiple records of the same data records.
Over-reliance on people: Decentralized infrastructure requires more maintenance and manual interventions when compared to a fully managed, centralized cloud service. It can also be hard to implement edge computing in remote locations that face power cuts and have poor network infrastructure.
8 Key Differences Between Edge Computing vs. Cloud Computing
Let's compare the key differences between cloud computing and edge computing approaches:
- Data Processing: Edge computing uses decentralized local servers, cloud computing uses centralized cloud servers.
- Data Transfers: Edge computing aims for the least possible distance between server and origin, cloud computing focuses on maximum distance across server and origin.
- Network Latency: Edge computing's is 100 to 200 milliseconds, cloud computing's is 500 to 1000 milliseconds (4-5x higher).
- Storage: Edge computing stores data on edge devices with no data replication, cloud computing replicates data on it's cloud platform for storage.
- Computing Power: Edge computing is low capacity with limited local resources, cloud computing's is high capacity with nearly unlimited resources.
- Internet Connectivity: Neither computing method can work without an Internet connection.
- Costs: More edge computing devices means higher cost, cloud computing is a pay-per-use server cost model.
- Bandwidth: Edge computing is lower usage with less data to transmit, cloud computing is high usage with more data to transmit.
Edge Computing and Cloud Computing Will Co-exist Together
Edge computing and cloud computing may lie on opposite ends of the computing continuum, but both have important applications. So, it's important to choose the right approach based on your business needs.
For example, edge computing may work better for time-sensitive applications that involve many networked IoT devices, whereas cloud computing may be a cost-effective choice for fast-growing web applications.
In some scenarios, you may also use both approaches together. For instance, you can use edge computing to process data across many decentralized locations and use a centralized cloud platform to aggregate and analyze incoming data from your entire edge infrastructure.
The applications of edge computing are many. For more information, visit our Guide on Edge Computing.