If you are having trouble differentiating between cloud and edge computing, look no further. We have demarcated both and also talked about the possibilities of a merger!
We are all familiar with the buzz around edge and cloud computing. But how well do we know the two? Are we aware of what makes them different or even similar? We took the time to help you differentiate one from the other and pick your suitable option!
Edge computing and cloud infrastructure are far from each other and cannot work as replacements of each other. However, they can merge on specific fronts and be used together by customers like you!
Cloud vs Edge
A fundamental difference is the time-sensitivity to data processing. Edge computing comes handy when a real-time assessment is the need of the hour. Whereas, with cloud technology, you can be more laid back with how soon data should or needs to be processed. Cloud and Edge computing are very different technologies. The next point of difference would be connectivity. On the one hand, the edge perimeter easily covers remote locations. On the other, for central data storage, the cloud is a more reliable choice.
Using Both To Your Advantage
Which is more suitable, you say? It depends on your requirements. Questions will arise to pick the right tool for you. Whether your data is processed locally or you want to widen your reach to multiple sites across geographies? You need to be clear of your computing goals before picking the means to it.
Edge Computing By Itself
Edge computing can be used purely for computing and processing data on the devices at the perimeter itself. However, relying on edge computing only means you will have to keep adding local computing sources as the amount of data generated increases.
Merge Edge With The Cloud
Using edge computing as an extension of your cloud environment can open multiple possibilities for your business while reaping the advantages of both. In this case, edge acts as a peripheral system to pre-process data for the cloud. Edge analytics conducts real-time analysis on the data from edge devices while the data is stored centrally in the cloud.
Moreover, the cloud has access to advancements like artificial intelligence and its subsets, machine learning and deep learning. The models formulated by such technology can be passed on out to the edge devices. With your edge devices having access to possibilities like these, you can witness performance enhancement and improved user experience. This is because AI models are used to respond to interactions and data generated from the onsite devices.
