Automation aided by reliably correlated topology

EXFO is running with a North European Tier 1 operator to roll out its real-time topology utility to automate the identity of not unusual causes behind network outages. Previously, large-scale outages and the protracted prognosis of faults took days (from time to time weeks) to investigate. The manual strategies used to address these outages generally worried gathering a collection of valuable, rather in-demand subject count experts (SMEs) in a conflict room to identify and remedy the troubles. Human logic became used to determine which clients were affected by the outage, manually hint lower back from the customer location and find the faulty network equipment. This resulted in sluggish response times and elevated operational costs.

But today, real-time topology, an crucial community visibility tool, lets in us to song and understand the configuration of the entire community across all sources. To assist perceive the maximum likely not unusual- motive customer issues, a “symptom set” is made from which it is viable to see common and shared performance issues that seem across a big set of endpoints. Common, repeated and simultaneous signs mean a not unusual reason. This method that the symptom set may be used to automate a topological analysis algorithm called “commonplace motive evaluation,” by way of which a symptom set is created and fed to the EXFO topology engine. The device then makes use of its cross-domain topological version to locate the particular set of community nodes that each one entities within the symptom set share. Network Troubleshooting ways