Finnish telecommunications company Elisa Oyj has announced the successful deployment of its first fully automated edge data center for commercial service, which is able to reduce staff-hours by up to 90%.
This project combines Wind River Studio Cloud Platform as the production-grade distributed Kubernetes solution for managing cloud infrastructure, User Plane Function (UPF) application from Elisa’s current 5G core vendor, and the advanced capabilities of Wind River Studio Conductor, a platform that delivers a single pane of glass to manage and automate applications deployment in large-scale distributed environments.
Further improve customer satisfaction
”We are delighted to continue our efficient collaboration with Wind River and take the first Fully Automated Edge Data Center into commercial service", says Markus Kinnunen, Vice President, Cloud Services. "Constant automation development is our key to future success. Combined with Wind River´s distributed cloud capabilities, we are able to further improve our customer satisfaction by reducing the time to deploy and adding the quality of the process."
Major outcomes
The major outcomes can be grouped in three areas: time to prepare, time to deploy and quality of the process:
- Time to prepare. The biggest savings came from parameter settings followed by environment preparation work. The team was able to execute hundreds of tests and scripts before going into live network in the same amount of time that it would typically take to manually run much fewer tests in the traditional model.
- Time to deploy. The overall Operator time, measured in terms of man-hours, for commissioning the edge DC site from preparation, parameter settings to complete installation and testing is reduced by 90% as compared to doing the very same tasks manually. Furthermore, the overall deployment time is reduced by around 50% thanks to the automation of the processes.
- Quality of the process. Automation brings in additional benefits where multiple tasks can now be run in parallel with minimal probability of human errors, reducing time to service and enhancing network quality.
