Guavus Proactive Ops
Replacing Reactive with Proactive Network Operations
Visibility methods and tools have been all about reacting to network issues as they happen but what about predicting an incident and resolving it without human intervention? Guavus uses artificial intelligence to proactively anticipate events that may cause network problems, identify which ones will have the biggest customer impact and take automated actions as needed. It enables Operation Centers to reduce and prioritize alarms, suggest corrective actions based on machine generated alerts, and predict which equipment changes will maximize network uptime.
Guavus Proactive Ops is a big data analytics module that enables Network Operation Centers to become more effective. It correlates and prioritizes network alarms, identifies the root issues of the alarms faster and predicts which equipment failures will cause the largest impact on your customer base. Proactive Ops ingests and correlates millions of network, telemetry and customer events per day from various disparate sources such as network alarms, alerts, and trouble tickets. Streaming data from these various events is normalized and joined together with data-at-rest such as customer care interactions, firmware versions and network topology, to create an enriched set of events.
Using advanced algorithms, millions of time series events are analyzed to automatically group alarms types and establish parent/child relationships between alarms and events. Guavus uses artificial intelligence to apply confidence scores and predict the cause/effect relationship in the pattern of events, even extending beyond known patterns, to predict incidents or equipment failures that have never been seen before. Preemptive, closed loop actions can be taken and network incidents avoided.