Abstract: Cycles and other patterns within time-series data are determined. Time-series data are transformed into discretized sets of clustered data that are organized by time period. Comparison is made of the organized data to determine similar time periods and multiclusters of the similar time periods are formed. From the multicluster data, cycles are identified from which thresholds and other useful data may be derived, or the data used for other useful purposes.

Abstract: Cycles and other patterns within time-series data are determined. Time-series data are transformed into discretized sets of clustered data that are organized by time period. Comparison is made of the organized data to determine similar time periods and multiclusters of the similar time periods are formed. From the multicluster data, cycles are identified from which thresholds and other useful data may be derived, or the data used for other useful purposes.

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: 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: 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: 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: 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 method for establishing communications between monitoring software located on a monitoring server is disclosed. A remote server includes an SSH server application and a remote application to be accessed by the monitoring software. The address information for the remote server is obtained. A secure tunnel is established between the remote server and the monitoring server. The monitoring software generates a random host and port, which is mapped to the remote host and port such that all communications between the two servers are encrypted by the tunnel. In one embodiment, the monitoring software includes Java software adhering to the JDBC protocol for making queries to the remote application, which is a JDBC database application.