The Cloud Edge Computing Vendors are offering specialized gateways, firewalls, and other solutions to manage and process a large amount of data that is generated by edge devices. Data can be captured, processed, and analyzed in near real-time with edge computing. It can also filter out data that isn't needed, sending only important data to a data center.
Handling data processing at the edge improves the performance of applications like augmented reality (AR), virtual reality (VR), machine learning (ML), and artificial intelligence (AI). Data computing can also be used in remote locations which prevent data from leaving its source. Additionally, utilizing the local area network (LAN) for data processing and storage results in fewer data transfers to the cloud, lowering operational expenses. Even though it is thought that streaming data to the cloud or a data center is more efficient, keeping data at the edge still requires security.
To prevent theft or a cyberattack, data encryption policies must be in place for all data being streamed and stored. The viability of edge data processing is dependent on maintaining a robust edge security posture. Although cloud edge computing has great potential to boost processing capacity, it presents major management challenges for IT teams. IT teams must manage an increasing variety of enterprise cloud platforms, each with its own set of tools and processes, as cloud edge computing is added to public and private cloud resources. The end effect is a sort of managerial chaos that can only lead to more expenses, more complexity, and restrictions on innovation, agility, and speed.
Cloud Edge Computing Vendors' architecture keeps the responsibility for processing data within the edge devices rather than requiring edge devices to send raw data back to data centers for processing, building a vast network of processors that can match the power of very large data centers.
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