Application Behavior Learning (ABL)
At the core of the AppsOne® solution is Appnomic®’s patent pending behavior learning and analytics technology – Application Behavior Learning. ABL is a powerful application of “Big Data” analytics applied to the enormous and growing volume of metrics in the complex application environments of enterprise and cloud IT infrastructures.
The core of ABL is the analytics approach that applies a number of new cluster, regression, and machine learning analytical techniques to correlate three dimensions of metrics:
1. Real end-user application transaction experience
(e.g., responsiveness, slowness, availability)1
IT infrastructure key performance indicators
(KPIs – like cpu utilization, database IOPs, active connections, etc.)
- Naturally occurring load or Application Usage Patterns (AUPs)
Different from other APM or analytics solutions, the resulting correlations are not just time based (like comparing last Friday to this Friday) or event driven which the ABL approach will also capture. ABL’s correlations are driven by application usage patterns - actual usage patterns of real users AppsOne® identifies and which reflect the volumes of concurrently occurring transactions that are contending for underlying infrastructure component resources.
Application Usage Pattern Horizontal Bar Chart
Patterns are automatically discovered by AppsOne® for comparison to future behavior to assess if future behaviour is consistent with patterns reflected in desired or acceptable conditions. If a pattern identified on a Friday afternoon also appears at on a future Tuesday evening, AppsOne® will identify this application usage as statistically the same and do its work accordingly. If a news piece on a company in “off season” generates a high load reflective of a high season shopping day, AppsOne® will pick up this pattern – even though it is not high season – because of the actual workload approaching the application.
More details about how ABL identifies and matches these patterns are available through discussions with the company.