TietoEVRY Scalable Edge Reference Platform
Last Updated: August 03, 2021
The solution provides a scalable, multi-workload Edge reference platform optimized for video analytics. Through the use of the Intel Smart Edge Open (previously known as OpenNESS), Kubernetes, and Intel technology optimizations, the platform can handle a coexistence of SmartCity, Telco, Automotive, and Enterprise workloads with reduced Time-To-Market for new services and Total Cost of Ownership. Running on standard off-the-shelf hardware (Advantech SKY-8101 5G Edge Server) removes vendor lock-in and makes the platform easily upgradeable and scalable. Based on the Cloud-native concept, it opens service providers with the possibility to deploy any new service in a matter of minutes instead of days. Integrated Smart City reference application is one example of the platform potential and its endless possibility of customization from hardware (and acceleration base) up to exact services and use cases to be run on. TietoEVRY works with its customers to define the targeted use cases, develop
- Scalable Edge Platform, video analytics optimized
White box platform-based standard off-the-shelf hardware and OpenNESS software enabled to run a variety of workloads, specifically tuned for Video Analytics applications. - Easy orchestration and cloud-native services deployment
OpenNESS based solution enables easy orchestration of edge services across diverse network platforms and access technologies in multi-cloud environments with significantly reduced Time to Market for new services. - Scalability with the combined computing power of VPU and CPU
Combining benefits of Intel CPU with DL-boost and Movidius VPU bringing significant Total Cost of Ownership reduction. Platform can be easily customized and optimized for many other workloads (RAN, Core, Industrial IoT, Automotive, Smart Cities etc.) - One-click scalable service deployment
Easy to deploy and performance-optimized Video analytic pedestrian detection solution proves the platform scalability, optimization potential as well as flexibility of handling a variety of the edge workloads.
