This post was originally published on Network Computing
The adoption of a hybrid work environment has reverberated across the technology ecosystem. Employees expect fast, secure, and reliable access to corporate resources from any location, and the traditional walls of centralized security and applications have been dismantled as organizations look to support a geographically distributed workforce. This shift, combined with the growing amount of data generated by IoT devices, has given rise to edge computing as a game-changing technology for applications requiring real-time decision-making. Its distributed architecture provides the necessary compute, storage, and networking functions through edge clouds located closer to the resources they serve. Moreover, these resources are increasingly accessible through first-mile internet loops, providing rapid and dependable connectivity.
One of the most significant benefits of edge computing is reduced latency. Since data is processed closer to the source, the time it takes to transmit and process data is significantly reduced. This is especially important in use cases requiring real-time data processing, such as autonomous vehicles, healthcare monitoring, and industrial automation. Edge computing enables these applications to process data in near real-time, leading to faster decision-making and increased safety. It also improves data privacy and security by keeping data within a more localized network, making it harder for
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