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Strategy-based closed-loop automated O&M improves the level of all-round automated O&M.
When an alarm is generated or performance KPI is abnormal, in policy center, the closed-loop policy control is triggered to drive the network self-healing automatically. When the failure cannot be recovered automatically, the work order is dispatched automatically to intelligently schedule related operation and maintenance resources. It realizes manual closed-loop management of network O&M.
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Multi-dimensional correlation perspective analysis enables all-round end-to-end assurance to the cloud network
The alarm correlation analysis provides vertical resource analysis of virtual networks, physical networks and services, and horizontal service analysis crossing wireless, transmission and core networks. With the help of multi-dimensional correlation analysis of resources / performance / alarm data, the root cause is located accurately and quickly.
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Building an AI analysis platform to promote the evolution of network intelligence
With the help of AI algorithm with RCA (Root Cause Analysis), the alarm history data is analyzed by intelligent machine learning. RCA rules are extracted automatically. AI algorithm helps O&M personnel to improve the efficiency of designing RCA rules. It changes the required RCA rule designer from end-to-end network service experts to general O&M personnel who do not need to know high-level skills. Thus, it gradually promotes the evolution of intelligent network O&M.
