Low-Latency Performance for Demanding Edge Workloads
Processing data at the network edge, close to its point of origin, enables low-latency apps and services while also reducing backhaul bandwidth costs. However, enterprise architects must meet the following challenges when designing edge computing solutions:
- Provide robust, scalable computing at remote locations, including demanding edge workloads such as artificial intelligence (AI)/deep learning and analytics.
- Protect the expanded attack surface created by distributed services and work-from-home scenarios that operate outside any network perimeter.
- Deliver a cloud-native implementation that supports transformation with ease of use and agility through cloudification of the edge.
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