Most companies store, manage, and analyze data on a centralized storage, typically in a public cloud or private cloud environment. However, traditional infrastructure and cloud computing
are no longer able to meet the requirements for many real life applications. For example, in the case of IoT
(Internet of Things) and IoE
(Internet of Everything), a highly available network
with minimal latency
is required to process large amounts of data in real time, which is not possible on a traditional IT infrastructure. In this case, the advantages of edge computing becomes more obvious.
In edge computing, data is processed close to the data collection source, so there is no longer the need to transfer data to the cloud or to an on-premises data center for processing and analysis. This approach will lessen the load on both network and servers.
Owing to its ability to process data in real time and its faster response time, edge computing is highly applicable in the field of IoT, particularly industrial IoT (IIoT). In addition to accelerating digital transformation
for industrial and manufacturing enterprises, edge computing technology allows for more innovations including artificial intelligence
and machine learning
The main difference between cloud computing and edge computing is where the data is being processed. In cloud computing, data is collected, processed, and analyzed at a centralized location. On the other hand, edge computing is based on a distributed computing environment, in which data is collected, processed, and analyzed locally. There is no need to choose between cloud computing and edge computing for cloud solution, they don't "compete" with each other, they just complement each other and work together to provide a better performance on applications.
Alibaba Cloud IoT platform
provides edge computing and other capacities to empower various IoT scenarios and industry developers. Click to learn more.