Abstract: Techniques that improve manageability of systems. Techniques are provided for creating different types of baselines that are more flexible and dynamic in nature. A future-based baseline may be created defining a period of time, wherein at least a portion of the period of time is in the future. A baseline may be created that is a composite of multiple baselines. In general, baselines may be specified having one or more periods of time that are either contiguous or non-contiguous. A template for creating a set of baselines based on a set of time periods may also be created, where the template can be used to create a baseline for each of the set of time periods. A moving window baseline may be created having an associated time window that changes with passage of time, where accordingly the data associated with the baseline may also dynamically change with passage of time.

Abstract: A method for determining event counts for a database system includes capturing samples for the active sessions based on a pre-defined sampling frequency and identifying events from the captured samples. The method further includes determining the wait time for each of the identified events and determining an event count for the active sessions using a harmonic mean. The harmonic mean is a summation of the maximum of either one or the ratio of the sampling frequency to the determined wait time for each of the identified events.

Abstract: Aspects of the present disclosure describe systems and methods for providing active session history data to users for use in database performance analysis. In various aspects, active session history data obtained from monitoring a database and/or database system over a period of time may be segmented into multiple dimensions. The segmented data may be subsequently provide and/or displayed on one or more interfaces, such as a graphical user interface, to users. The interface may visualize the dimensional ASH data in a variety of ways, such as through icons, graphs, charts, histograms, temporal delineations, treemaps, etc.

Abstract: Techniques that improve manageability of systems. Techniques are provided for creating different types of baselines that are more flexible and dynamic in nature. A future-based baseline may be created defining a period of time, wherein at least a portion of the period of time is in the future. A baseline may be created that is a composite of multiple baselines. In general, baselines may be specified having one or more periods of time that are either contiguous or non-contiguous. A template for creating a set of baselines based on a set of time periods may also be created, where the template can be used to create a baseline for each of the set of time periods. A moving window baseline may be created having an associated time window that changes with passage of time, where accordingly the data associated with the baseline may also dynamically change with passage of time.

Abstract: Techniques that improve manageability of systems. Techniques are provided for creating different types of baselines that are more flexible and dynamic in nature. A future-based baseline may be created defining a period of time, wherein at least a portion of the period of time is in the future. A baseline may be created that is a composite of multiple baselines. In general, baselines may be specified having one or more periods of time that are either contiguous or non-contiguous. A template for creating a set of baselines based on a set of time periods may also be created, where the template can be used to create a baseline for each of the set of time periods. A moving window baseline may be created having an associated time window that changes with passage of time, where accordingly the data associated with the baseline may also dynamically change with passage of time.

Abstract: Aspects of the present disclosure describe systems and methods for providing active session history data to users for use in database performance analysis. In various aspects, active session history data obtained from monitoring a database and/or database system over a period of time may be segmented into multiple dimensions. The segmented data may be subsequently provide and/or displayed on one or more interfaces, such as a graphical user interface, to users. The interface may visualize the dimensional ASH data in a variety of ways, such as through icons, graphs, charts, histograms, temporal delineations, treemaps, etc.

Abstract: A method for determining event counts for a database system includes capturing samples for the active sessions based on a pre-defined sampling frequency and identifying events from the captured samples. The method further includes determining the wait time for each of the identified events and determining an event count for the active sessions using a harmonic mean. The harmonic mean is a summation of the maximum of either one or the ratio of the sampling frequency to the determined wait time for each of the identified events.

Abstract: Techniques for systematically gathering, organizing, and storing diagnostic data related to multiple monitored systems (e.g., multiple instances of a product or multiple products). A centralized repository is provided that is organized in a hierarchical manner to facilitate proper organization of the diagnostic data related to multiple monitored systems. In one embodiment, a root directory comprising one or more subdirectories is provided for storing diagnostic data collected for each monitored system. Multiple root directories may be provided under a common base directory for storing diagnostic data corresponding to multiple monitored systems. This enables correlation of diagnostic data across multiple monitored systems.

Abstract: Particular embodiments generally relate to displaying database time using a treemap. A set of database time values is determined for a set of dimensions. The database time values measure performance of one or more databases by the time the database takes to respond to a request. The set of database time values is correlated to a set of cells in the treemap. A size of the cell is determined based on the database time value associated with it. For example, the database time value is correlated to an area of the cell. A layout of the set of cells is determined and the treemap is displayed using the layout. For example, the largest values of database time may be shown with the largest sized cells. This makes it easier for an administrator to review and analyze the database performance across multiple dimensions and determine problem areas affecting the performance of the one or more databases.

Abstract: A diagnosability system for automatically collecting, storing, communicating, and analyzing diagnostic data for one or more monitored systems. The diagnosability system comprises several components configured for the collection, storage, communication, and analysis of diagnostic data for a condition detected in monitored system. The diagnosability system enables targeted dumping of diagnostic data so that only diagnostic data that is relevant for diagnosing the condition detected in the monitored system is collected and stored. This in turn enables first failure analysis thereby reducing the time needed to resolve the condition detected in the monitored system.

Abstract: Particular embodiments generally relate to displaying database time using a treemap. A set of database time values is determined for a set of dimensions. The database time values measure performance of one or more databases by the time the database takes to respond to a request. The set of database time values is correlated to a set of cells in the treemap. A size of the cell is determined based on the database time value associated with it. For example, the database time value is correlated to an area of the cell. A layout of the set of cells is determined and the treemap is displayed using the layout. For example, the largest values of database time may be shown with the largest sized cells. This makes it easier for an administrator to review and analyze the database performance across multiple dimensions and determine problem areas affecting the performance of the one or more databases.

Abstract: Techniques for systematically gathering, organizing, and storing diagnostic data related to multiple monitored systems (e.g., multiple instances of a product or multiple products). A centralized repository is provided that is organized in a hierarchical manner to facilitate proper organization of the diagnostic data related to multiple monitored systems. In one embodiment, a root directory comprising one or more subdirectories is provided for storing diagnostic data collected for each monitored system. Multiple root directories may be provided under a common base directory for storing diagnostic data corresponding to multiple monitored systems. This enables correlation of diagnostic data across multiple monitored systems.

Abstract: Techniques that improve manageability of systems. Techniques are provided for creating different types of baselines that are more flexible and dynamic in nature. A future-based baseline may be created defining a period of time, wherein at least a portion of the period of time is in the future. A baseline may be created that is a composite of multiple baselines. In general, baselines may be specified having one or more periods of time that are either contiguous or non-contiguous. A template for creating a set of baselines based on a set of time periods may also be created, where the template can be used to create a baseline for each of the set of time periods. A moving window baseline may be created having an associated time window that changes with passage of time, where accordingly the data associated with the baseline may also dynamically change with passage of time.

Abstract: A diagnosability system for automatically collecting, storing, communicating, and analyzing diagnostic data for one or more monitored systems. The diagnosability system comprises several components configured for the collection, storage, communication, and analysis of diagnostic data for a condition detected in monitored system. The diagnosability system enables targeted dumping of diagnostic data so that only diagnostic data that is relevant for diagnosing the condition detected in the monitored system is collected and stored. This in turn enables first failure analysis thereby reducing the time needed to resolve the condition detected in the monitored system.

Abstract: A computer is programmed to fit exponential models to upper percentile subsets of observed measurements for performance metrics collected as attributes of a computer system. The subsets are defined from sets chosen to reduce model bias due to expected variations in system performance, e.g. those resulting from temporal usage patterns induced by end users and/or workload scheduling. Measurement levels corresponding to high cumulative probability, indicative of likely performance anomalies, are extrapolated from the fitted models generated from measurements of lower cumulative probability. These levels are used to establish and to automatically set warning and alert thresholds which signal to (human) administrators when performance anomalies are observed.

Abstract: A computer derives, from a current measurement of an attribute of a system, an instantaneous severity score based on a probability model that is determined from prior measurements. The computer then displays, for several successive moments in time, either the instantaneous severity score or an aggregated severity score obtained from a set of instantaneous severity scores (e.g. by averaging). Each set of scores to be aggregated may be identified by, e.g., a fixed-width time window located at a fixed offset from a moment in time at which the aggregated score is to be displayed. Aggregation suppresses or dampens momentary abnormalities, which would otherwise get displayed. In some embodiments, graphs for multiple categories of metrics are displayed on a single screen, aligned in time, to enable a human operator to form a visual correlation therebetween, e.g. to identify causes of atypical performance in the system.

Abstract: A method and apparatus for diagnosing database performance problems using a plurality of wait classes is provided. A set of statistical data that describes current activity within a database system is periodically retrieved. The set of statistical data may include information about the current activity of each user session connected to the database system. Thereafter, a set of cumulative statistical data that describes activity in the database system over a period of time is updated to reflect the retrieved set of statistical data. The set of cumulative statistical data includes statistics associated with each of a plurality of wait classes. A graphical user interface that displays the set of cumulative statistical data may be presented to a user. The graphical user interface allows the user to quickly ascertain the nature of the database performance problems by providing a view of the set of cumulative statistical data.