Abstract: An integrity management system predicts abnormalities in complex systems before they occur based upon the prior history of abnormalities within the complex system. A topology of the nodes of a complex system is generated and data is collected from the system based on predetermined metrics. In combination with dynamic thresholding, fingerprints of the relevant nodes within a complex system at various time intervals prior to the occurrence of the abnormality are captured and weighted. The fingerprints can then be applied to real-time data to provide alerts of potential abnormality prior to their actual occurrence.

Abstract: According to a feature of the present disclosure, a method is provided for the determination of anomalous events in complex systems, such as problems, inefficiencies, and failures, and a tool is provided for the detection of these events. Many complex systems are non-stationary or experience periodic fluctuations or spikes in values that are outside of normal ranges, but constitute normal behavior nevertheless. The method accounts for both non-stationarity, as well as fluctuations and spikes. Additional novel features include both a threshold setting initialization method and a regression method for the determination of the start points and end points of events.

Abstract: An integrity management system predicts abnormalities in complex systems before they occur based upon the prior history of abnormalities within the complex system. A topology of the nodes of a complex system is generated and data is collected from the system based on predetermined metrics. In combination with dynamic thresholding, fingerprints of the relevant nodes within a complex system at various time intervals prior to the occurrence of the abnormality are captured and weighted. The fingerprints can then be applied to real-time data provide alerts of potential abnormality prior to their actual occurrence.

Abstract: A system and method is provided for capturing and using problem fingerprints in an Information Technology (IT) infrastructure for integrity management. A fingerprint of the transaction topology in an IT infrastructure is automatically captured at various time intervals prior to the occurrence of an event leading to a problem, such as a failure, hard threshold violation, defined transaction violation or user-provided occurrence. The fingerprint provides an indication of the activity and operation of the IT infrastructure immediately preceding the problem event. The captured fingerprint is then used to monitor real-time data in the IT infrastructure operation and activity to look for activity that matches a captured fingerprint to provide an indication of a pending problems before the problems occur.

Abstract: According to a feature of the present disclosure, a method is provided for the determination of anomalous events in complex systems, such as problems, inefficiencies, and failures, and a tool is provided for the detection of these events. Many complex systems are non-stationary or experience periodic fluctuations or spikes in values that are outside of normal ranges, but constitute normal behavior nevertheless. The method accounts for both non-stationarity, as well as fluctuations and spikes. Additional novel features include both a threshold setting initialization method and a regression method for the determination of the start points and end points of events.

Abstract: An integrity management system predicts abnormalities in complex systems before they occur based upon the prior history of abnormalities within the complex system. A topology of the nodes of a complex system is generated and data is collected from the system based on predetermined metrics. In combination with dynamic thresholding, fingerprints of the relevant nodes within a complex system at various time intervals prior to the occurrence of the abnormality are captured and weighted. The fingerprints can then be applied to real-time data provide alerts of potential abnormality prior to their actual occurrence.