Abstract: Provides methods, systems and apparatus for generating alerts for a system process that obtains raw channel data over time from one or more monitored channel of the system process. An example method includes processing the raw channel data to form time dependent signals based one or more user specified processing rules. The method produces alerts based on the deviation in behavior in one or more channels, where the deviation is quantified by a numeric level computed by comparing signals for varying time intervals with historically normal baseline signals. The method may include filtering the alerts to selectively form reportable alerts that are presented to the user based on user specified filtering rules.

Abstract: A method and system for enterprise monitoring maps monitor events to elements of a component business model of the enterprise and displays the mapped events using the component business model. Rules are used to determine whether events captured from a monitor source are monitor events. An enterprise monitor metamodel linking monitor artifacts and elements of a component business model is used to annotate monitor events with data from the component business model of the enterprise.

Abstract: Provides methods, systems and apparatus for generating alerts for a system process that obtains raw channel data over time from one or more monitored channel of the system process. An example method includes processing the raw channel data to form time dependent signals based one or more user specified processing rules. The method produces alerts based on the deviation in behavior in one or more channels, where the deviation is quantified by a numeric level computed by comparing signals for varying time intervals with historically normal baseline signals. The method may include filtering the alerts to selectively form reportable alerts that are presented to the user based on user specified filtering rules.

Abstract: A system for detecting clusters in space and time using input data on occurrences of a phenomenon and characteristics at a plurality of locations and times comprises an expectation generation module determining expected occurrences of a phenomena, and an occurrence modeling module determining actual occurrences of the phenomena. The system further comprises a search module searching the expected occurrences and the actual occurrences for a plurality of candidate solutions, wherein each solution is represented as a set of points in the three-dimensional space, and wherein each point corresponds to a location at a time. The system comprises a convex container module determining at least one solution corresponding to a selected convex container shape from the plurality of candidate solutions, and a solution evaluation module determining a strength metric for each solution determined by the convex container module, the search module selecting a dominant cluster in the input data.