One of the growing trends in technology is edge computing. Over the past few months, the buzz around edge computing has grown considerably due to its many applications and versatility. Some people have even suggested that edge computing could replace cloud computing models.
In reality, edge computing is a natural complement to cloud computing rather than a replacement. Cloud computing provides a fast and inexpensive storage solution; edge computing addresses limitations related to network latency. These technologies work synergistically to create reliable and efficient AI, machine learning, and data analysis capabilities.
What Is the Difference between Edge and Cloud Computing?
In the future, cloud and edge computing will likely combine, as each one helps to overcome the weakness of the other. To understand why, it is critical to know how each technology works.
With cloud computing, data is gathered and processed in a centralized location, usually a data center. Any device that needs to access this data must first connect to the cloud. Because everything remains centralized, the approach is generally quite secure and easy to control. Authorized users gain the ability to access the information and tools available on the cloud from anywhere and at any time. This sort of access is not possible with local networks.
While cloud computing is powerful, the technology struggles to process data collected at the edge of a network quickly and effectively. This information needs to be relayed back to the centralized data repository for processing before further instructions can be sent back to the edge. The large amount of travel involved can cause processing delays and jam the network with unnecessary volumes of data.
Edge computing relocates crucial data processing from the centralized repository to the edge of the network. With this technology, data is collected and processed in real time for an extremely fast response. Edge computing involves utilizing the processing power of edge data centers or devices themselves.
What Technologies Will Benefit from the Merger of Edge and Cloud?
The benefits of combining edge and cloud computing technologies may not be immediately evident. After all, the amount of time saved by moving computing capabilities to the edge is literally only milliseconds in most cases, but this small amount of time can make a major difference. The conversation now focuses on applications in the Internet of Things (IoT). For something like a self-driving car, milliseconds of processing time can make a major difference in responding to emergencies. Any sort of latency with a self-driving car could be disastrous. In many other cases, such as IoT devices or streaming media, latency is more of an inconvenience than a true safety issue, but one that can be addressed by combining edge and cloud computing.
Many industries are already playing with the combination of these technologies to create services that are more reliable and faster. In the medical field, for example, pharmaceutical companies are confronting the complexities of regulatory processes and inventory management through proximal systems that process information instantly. In the manufacturing industry, these two technologies are being combined to monitor changing process conditions and adjust on the fly to minimize downtime and improve overall safety.
For retailers, a combined edge and cloud system helps track sales and access information quickly to reduce lines and improve the overall customer experience. Edge computing may make solutions like autonomous checkouts an easily implemented strategy, as well. Combined cloud and edge computing will also play a role in supply chain reporting and management.
What Should the Technology Industry Expect Moving Forward?
Consumers’ expectations for technology are changing at the same rate as their data consumption. Scaling edge and cloud computing will become a major focus for a large number of companies moving forward. Some technology providers are already addressing the need for edge computing as part of their cloud solutions. For example, Microsoft offers Azure Stack Edge and AWS Snowball Edge. Both of these technologies use edge computing for rapid data transport to meet the growing demand for speed and reliability at various technology companies.
Implementing edge technology into cloud computing will likely be less complicated than it seems. After all, computing has long occurred at the edge of networks at branch offices and remote locations, which often hold data on small servers and networks.
Cloud systems provide a centralized system for reliability and agility, and in the past, implementing this solution often meant shifting data architecture completely. Recreating some edge processing power does not involve the same degree of architectural shift.
In some ways, combining edge and cloud strategies takes companies back to more localized data processing while maintaining the advantages of a large, centralized storage location.