In many situations, using cloud computing and edge computing at the same time can lead to the best overall result from a performance perspective.
Debates about the relationship between cloud computing and edge computing have a tendency to present cloud and edge as opposite types of architectures and to treat them as either a proposal or not.
This is not the best way to think about the cloud and the advantage. While there are key differences between cloud computing and edge computing, cloud and edge do not compete with each other as much as they complement each other.
Differences between cloud and edge
The differences between cloud computing and peripheral computing are greatly reduced where workloads are hosted.
In a conventional cloud, data and applications are hosted in large data centers located on a public cloud provider’s network.
In an edge architecture, workloads are housed in a location “closer” (from a network perspective) to end users than a traditional data center.
Multiple approaches to edge computing
Needless to say, the edge definition can be a bit messy because there are many possible ways to build an edge architecture. Sometimes a perimeter environment runs directly on end-user devices. In others, it looks more like a traditional data center populated by conventional servers, which are closer to end users than traditional cloud data centers.
Cloud computing tends to be simpler from an architectural perspective. While there are some variations in which cloud regions and clouds use equipment to host workloads, all public cloud environments rely on conventional data centers that are relatively far away (again, in terms of network) from end users.
Why cloud computing and edge come together
Although cloud computing and edge computing are fundamentally different types of architectures, “cloud vs. cloud. edge ”is not necessarily the best way to think about it.
In many cases, it makes sense to use the cloud and the edge at the same time. Data centers in the cloud can host workloads that do not require minimal latency and high reliability of those hosted on the edge, while the Edge infrastructure manages those that do.
By pairing cloud and edge, organizations can take advantage of the scalability and ease of deployment of cloud environments, while achieving high-performance goals that cloud data centers may not always be able to support due to latency issues. net.
That doesn’t mean you always have to use cloud and edge at the same time. It is completely possible to host applications or data in the cloud without having to run a perimeter environment. It is also possible, although less common, to use Edge without using a public cloud.
Conclusion: Overload performance in the cloud and on the edge
But overall, using cloud computing and edge computing at the same time can lead to the best overall result from a performance perspective. The only downside is that it can be more difficult to manage a cloud environment and an edge environment at the same time, although platforms like Kubernetes simplify this by facilitating the deployment of applications in both environments from a central management plan. .