Abstract: An approach is provided for detecting and analyzing an anomaly in application performance in a client-server connection via a network. A status code of a response sent by a server to a client, a round trip latency time (RTT) of the response, and a time out of a connection between client and server are determined. Using a k-means clustering algorithm, buckets of RTT values clustered into lower and higher values, and running counts and means for the RTT values in each bucket, an RTT value is determined to exceed a threshold value. Based on the status code, the RTT value exceeding the threshold, and the connection time out, the anomaly is detected. Based on temporal and textual analyses of log entries and an environment analysis, candidate root causes of a failure that resulted in the anomaly are determined.

Abstract: An approach is provided for detecting and analyzing an anomaly in application performance in a client-server connection via a network. A status code of a response sent by a server to a client, a round trip latency time (RTT) of the response, and a time out of a connection between client and server are determined. Using a k-means clustering algorithm, buckets of RTT values clustered into lower and higher values, and running counts and means for the RTT values in each bucket, an RTT value is determined to exceed a threshold value. Based on the status code, the RTT value exceeding the threshold, and the connection time out, the anomaly is detected. Based on temporal and textual analyses of log entries and an environment analysis, candidate root causes of a failure that resulted in the anomaly are determined.

Abstract: An approach is provided for detecting and analyzing an anomaly in application performance in a client-server connection via a network. A request time and an Internet Protocol (IP) address of the client are determined. Based on the request time and the IP address, log entries relevant to the request are selected. A response code, a round trip latency time (RTT) of the response, and an indication of whether the connection timed out are determined. Based on the status code, the RTT, and the indication of whether connection timed out, the anomaly is detected. Based on temporal and textual analyzes of log entries associated with the anomaly and an environment analysis that determines activity of the client, server, and network, candidate root causes of a failure that resulted in the anomaly are determined.

Abstract: An approach is provided for detecting and analyzing an anomaly in application performance in a client-server connection via a network. A request time and an Internet Protocol (IP) address of the client are determined. Based on the request time and the IP address, log entries relevant to the request are selected. A response code, a round trip latency time (RTT) of the response, and an indication of whether the connection timed out are determined. Based on the status code, the RTT, and the indication of whether connection timed out, the anomaly is detected. Based on temporal and textual analyses of log entries associated with the anomaly and an environment analysis that determines activity of the client, server, and network, candidate root causes of a failure that resulted in the anomaly are determined.

Abstract: Embodiments of the present invention provide a method, system and computer program product for interest contour computation and management based upon user generated content and associated meta-data. In an embodiment of the invention, an interest contour computation and management method is provided. The method includes crawling content sources disposed about a computer communications network for authored content created by an end user. The method further includes identifying meta data provided for the authored content and adding the meta data to a user interests profile of the end user. The meta-data further can include extracted text from the content. Of note, the method can further include receiving from the end user a specified time period and limiting the addition of the meta data to meta data applied to the authored content during the specified time period.

Abstract: A method, system and computer program product for providing a framework to enable a builder to construct a situational application, wherein the framework provides access to one or more background data sources. A graphical user interface is displayed to receive feedback inputs, including one or more inputs which describe the problem detected within a data item of a situational application, by an end-user. Feedback inputs may include a unique identifier of the problem data item and identification details of the service from which the data originates. A second input may be of a note, which provides suggestions for improving the data within the data item. Preference information is provided to a notification agent within the framework of the situational application about whether the owner of the data allows direct correction of the data and whether feedback input has to be stored in a problem cache.

Abstract: Embodiments of the present invention provide a method, system and computer program product for interest contour computation and management based upon user generated content and associated meta-data. In an embodiment of the invention, an interest contour computation and management method is provided. The method includes crawling content sources disposed about a computer communications network for authored content created by an end user. The method further includes identifying meta data provided for the authored content and adding the meta data to a user interests profile of the end user. The meta-data further can include extracted text from the content. Of note, the method can further include receiving from the end user a specified time period and limiting the addition of the meta data to meta data applied to the authored content during the specified time period.

Abstract: A method, system and computer program product for providing a framework to enable a builder to construct a situational application, wherein the framework provides access to one or more background data sources. A graphical user interface is displayed to receive feedback inputs, including one or more inputs which describe the problem detected within a data item of a situational application, by an end-user. Feedback inputs may include a unique identifier of the problem data item and identification details of the service from which the data originates. A second input may be of a note, which provides suggestions for improving the data within the data item. Preference information is provided to a notification agent within the framework of the situational application about whether the owner of the data allows direct correction of the data and whether feedback input has to be stored in a problem cache.