Today's advanced application and service environments are too large and complex for yesterday's rule based management approaches. As a result operations teams are either deluged with false alerts or glued to dashboards. They learn about too many problems from end-users and spend too much time troubleshooting instead of improving service levels.
But Anomaly Detective customers are changing that equation. Instead of wasting time writing 'known bad' behavior rules that generate useless alerts, they let machine learning algorithms automatically baseline normal behaviors and identify real problems in real-time. Instead of trial and error hunting through gigabytes of forensic data, they let advanced analytics cross-correlate causal data and slash troubleshooting times and team sizes up to 90%.
With all the free time they gain, Prelert customers use Anomaly Detective to focus their efforts on continual improvement processes that reduce incident rates and boost service levels.