Edge computing with distributed cloud
With an increasing interest in new use cases such as smart manufacturing, augmented reality and a multitude of IoT applications, there is a need for an infrastructure with edge computing and distributed cloud capabilities.
Edge computing and distributed cloud
Edge computing provides compute and storage resources with adequate connectivity (networking) close to the devices generating traffic. The benefit is the ability to provide new services with high requirements on e.g. latency or on local break-out possibilities to save bandwidth in the network – data should not have to travel far in the network to reach the server. Regulatory compliance and network scalability are also important edge computing drivers.
Many use-cases for IoT and 5G span the device, access-, distributed-, national- and global sites. For example, an augmented reality solution comprises a client on a device, a component supporting video processing, a CDN/caching function at a distributed site and a backend at a national- or global site. This requires a solution that can handle any workload, anywhere in the network, with end to end orchestration. Distributed cloud is doing this - managing different types of sites where the location of the edge depends on the use case.
Edge computing orchestration and intelligent placement of workloads
Distributed cloud goes along with automated deployment of applications at just the right location in the network to optimize resource efficiency and user experience. For that reason, orchestration is a key capability providing end to end management of networking, cloud infrastructure and workload placement.
The dynamic orchestration simplifies the complexity of the network enabling intelligent placement of workloads to everyone. The intelligent placement is policy driven and based on criteria such as latency, geolocation, and throughput.
Going forward, finding the optimal placement in the network will typically be enhanced by using artificial intelligence and machine learning.