Edge Added to the Cloud

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Edge computing is growing in popularity due to its performance, security and cost benefits over traditional cloud architectures, but it's not always the best fit for distributed workloads.

Edge computing refers to architectures that process data at or near devices that generate and consume data, such as end-user PCs, mobile phones or IoT sensors. This differs from conventional cloud computing, which relies on central servers to receive data, process it and send it back to client devices. Edge computing can reduce network latency, lower the exposure of data to the network and, in some cases, reduces costs by offloading processing to end users' devices.

Due to its appealing advantages, cloud architects might want to push as many workloads as they can to the edge. But before they do, they should consider each application's structure, performance requirements and security considerations, among other factors.
The two types of edge computing architecture

When weighing whether an edge computing model is the right fit, the first question to ask is which type of architecture is available. 

There are two main types:

1. Device-edge computing, in which data is processed directly on client devices.
2. Cloud-edge computing, in which data is processed on edge hardware that is geographically closer to client devices than centralized cloud data centers.

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