Ca, Inc.

Netqos, Inc.

Peter William Mullarkey

Michael Charles Johns

Kevin Eugene Davis

Jason D Goldman

Scott W Strobel

Mark S LoSacco

Aby Paul

Michael C Johns

In embodiments, a known network relation is generated from a known topology of a network and is sent to a first data source agent associated with a first tool configured to monitor the network. A first contextual topology of the network is received from the first data source agent and is based on the known network relation and first data associated with the first tool. An extended topology is generated by reconciling the known topology with at least the first contextual topology. In further embodiments, a derived network relation is received from the first data source agent. The derived network relation is sent to a second data source agent. Second contextual topology based, at least in part, on the derived network relation can be received from the second data source agent. An updated extended topology based, at least in part, on the second contextual topology can be generated.

Extending a known topology of a network using data obtained from monitoring the network

A method for a diagnostic headline system using simple linguistic terms is described. The method comprises receiving historical and current performance data for a component of a system. An anomaly is determined in the current performance data by comparing the current performance data and the historical performance data for the component. The anomaly is determined whether or not it indicates an error in the system. The cause of the anomaly is determined. Steps for addressing the cause of the anomaly are recommended. A display is formatted of the current performance data, the error, and the recommended steps for addressing the cause of the anomaly.

Presenting diagnostic headlines using simple linguistic terms

A method for diagnosing system anomalies and presenting recommended solutions is described. The method comprises receiving current component performance data and historical component performance data regarding performance of a component of a multi-tier system. A baseline tier performance for each tier and a baseline component performance is determined. A cause of an anomaly in the performance of the component is determined by discovering deviations in current component performance data and current tier performance in compared to their baseline values. Based on these deviations, a recommended procedure for addressing the cause of the anomaly is determined. A display is formatted within a user interface of the recommended procedure for addressing the cause of the anomaly in the performance of the component.

Diagnosing anomalies based on deviation analysis

An anomaly detection method and system determine network status by monitoring network activity. A statistics based profile for said network over a period is generated to analyze potentially anomalous network activity to determine if said network activity is anomalous by comparing current activity against the profile. Using the profile as a reference, the anomaly detection system and process estimate and prioritize potentially anomalous network activity based on the probability that the behavior is anomalous. The level of severity that the anomaly detection process uses to determine if an alarm is needed is based on comparing user-adjustable thresholds to the current probability. If the threshold has been breached, the user is alerted, subject to other quality checks. After a reporting cycle concludes, the anomaly detection system and process recompiles the statistics based profile to take into account the information observed in the previous reporting cycle.

Statistical method and system for network anomaly detection

Techniques for visualizing and monitoring the quality of service for a computer network. Herein, a method and system monitor network transactions and behaviors for the computing network, which computing network includes one or more client subnets accessing one or more servers, The monitoring may be independent of client site monitors. Statistical data is gathered for relating to at least the network, the server, and the applications for generating a plurality of measurements. The measurements assess at least one quality of service indicator associated with the performance of the computer network. The method and system graphically display the plurality of measurements of the quality of service indicator according to the date and time of gathering the statistical data and further display graphically the degree by which each of the measurements of the quality of service indicator varies from a predetermined threshold quality of service level for the computing network. Also, dynamic quality of service indicators are monitored against average quality of service indicators.

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Fort Collins, CO, United States of America

Peter William Mullarkey