Verizon and Ericsson first in the world to introduce cloud-native technology in a live wireless core network environment

   Updated:2019-07-15    
HILLSBORO, ORIn a proof-of-concept trial in a live network environment, Verizon and Ericsson have introduced cloud native, container based technology on the core of Verizons active network. This trial, the first container- based wireless EPC (Evolved Pack
 
HILLSBORO, OR – In a proof-of-concept trial in a live network environment, Verizon and Ericsson have introduced cloud native, container based technology on the core of Verizon’s active network. This trial, the first container- based wireless EPC (Evolved Packet Core) technology deployment in a live network in the world, introduces a much more efficient way to deliver operational applications that run the network. It is a solution that will increase agility and enable deployment at scale for new services in 4G and 5G.
 
“The pace of technological advancement is rapid and is exponentially increasing. By evolving our core network past simply using virtualized machines and instead changing our underlying software architecture to run on cloud- native technology, we are able to achieve new levels of operational automation, flexibility and adaptability,” said Bill Stone, Vice President of Technology Development and Planning for Verizon.
 
That operational autonomy will be critical for the next generation of services being enabled by new network technologies. The advanced capabilities of 4G LTE and the high speed, increased bandwidth and low latency of 5G will help inspire development of a wide variety of new use cases that include everything from massive numbers of IoT devices that do very little networking, to smartphones with nearly infinite opportunities to use data, to more complex solutions such as AR/VR that will require massive computing capabilities on the edge of the network. Those solutions will each require different combinations of network capabilities. Cloud-native virtualization, in combination with built-in Artificial Intelligence and Machine Learning (AI-ML), will enable dynamic allocation of the appropriate resources and automated network configuration changes - including the ability to scale up or scale down network function capacity - to provide the right service levels and network resources needed for each use case. 

 
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