Alive Behavioral Analytics:
Intelligently Reduce Alert Volumes and Deliver Actionable Intelligence
Alive Behavioral Analytics provides real-time, automated analysis of IT performance data to deliver actionable intelligence for identifying, resolving and preventing problems.
To do so, Behavioral Analytics uses the following process:
- Continuously collects data from your IT environment and builds models of the normal behavior of each resource.
- Determines the normal range of values for any metric, detecting and accounting for cyclical patterns as they're observed. This is called Dynamic Threshold Analysis.
- Compares the real-time measurements of metrics with the expected range of values to determine when a metric triggers a threshold violation.
- Dynamic Thresholding illuminates abnormal behaviors that are precursors to real problems and require action, virtually eliminates the problem of wasting resources on false alerts.
- Uses advanced algorithms that are sensitive to the magnitude, duration, and scope of threshold violations. These algorithms also quickly adapt to change and can differentiate between changes in normal behavior and genuinely abnormal events.
- When abnormal events are detected, Alive uses business service topology to consolidate alerts and roll them up to the device, tier, or business-service level for more efficient problem solving.
Alive's Behavioral Analytics and Correlation Analytics work together to reduce alert volume. Before a real-time abnormality results in an alert, Alive verifies whether or not there is an existing alert that is highly correlated. If there is, Alive updates the existing alert with information about the new abnormality instead of issuing an entirely new one. This alert unification eliminates "alert storms," while providing more actionable information to get problem-solving off to a fast start.










