Abstract: A method, system, and computer program product for globalizing distributed software packages using a global API is disclosed. A text string in a source language is extracted from an independent package source code. An algorithm is used to calculate a resource message key for the text string. The resource message key and the text string are stored in a source language resource file. The text string is translated into an additional language to create a translated text string. The translated text string is stored with the resource message key in an additional language resource file. The independent package is distributed with the source language resource file, the additional language resource file, and the independent package program code bundled in the independent package.

Abstract: A computer monitoring system may predict near term and long term performance by comparing a segment of current time series data with previously observed time series to find matching segments. From a matching segment, a prediction of performance may be made by examining later observations in the time series. Each time series element may include a large number of parameters, and one mechanism for comparing segments may be treating the elements as multi-dimensional vectors and using cosine similarity for finding significant matches. A deployment mechanism may store time series segments in a searchable database, and search the database with a newly observed time series segment for matches.

Abstract: Recommendations may be generated while calculating performance metrics from multiple uses of a software component. A tracing service may collect trace data from multiple uses of a software component, where each use may be done on different conditions. The performance metric analysis may identify various factors that may affect the performance of a software component, then present those factors to a user in different delivery mechanisms. In one such mechanism, a recommended set of hardware and software configurations may be generated as part of an operational analysis of a software component.

Abstract: A method, system, and computer program product for globalizing distributed software packages using a global API is disclosed. A text string in a source language is extracted from an independent package source code. An algorithm is used to calculate a resource message key for the text string. The resource message key and the text string are stored in a source language resource file. The text string is translated into an additional language to create a translated text string. The translated text string is stored with the resource message key in an additional language resource file. The independent package is distributed with the source language resource file, the additional language resource file, and the independent package program code bundled in the independent package.

Abstract: A method, system, and computer program product for globalizing distributed software packages using a global API is disclosed. A text string in a source language is extracted from an independent package source code. An algorithm is used to calculate a resource message key for the text string. The resource message key and the text string are stored in a source language resource file. The text string is translated into an additional language to create a translated text string. The translated text string is stored with the resource message key in an additional language resource file. The independent package is distributed with the source language resource file, the additional language resource file, and the independent package program code bundled in the independent package.

Abstract: A method, system, and computer program product for globalizing distributed software packages using a global API is disclosed. A text string in a source language is extracted from an independent package source code. An algorithm is used to calculate a resource message key for the text string. The resource message key and the text string are stored in a source language resource file. The text string is translated into an additional language to create a translated text string. The translated text string is stored with the resource message key in an additional language resource file. The independent package is distributed with the source language resource file, the additional language resource file, and the independent package program code bundled in the independent package.

Abstract: Dimensionality reduction, such as principal component analysis, may be used at least in part to generate a model of time series observations of a computer application. The model may be applied to current and predicted observations. Outliers may be identified from current or predicted observations by analyzing those observations against the model, and statistically relevant outliers may generate alerts or corrective or other action to be taken. The outliers may be analyzed by searching for similar outliers that may have been previously observed, and predicting any future events based on similar observations of the past.

Abstract: Dimensionality reduction, such as principal component analysis, may be performed against a time series of performance observations for a computer application. A visual representation of the results may be displayed in one, two, or three dimensions, and often show clusters of operational behavior. The representation may be animated to show a sequence of observations and how the behavior of an application may change from one cluster of operation to another. The representation may be further applied to show both a historical view of the observations and new observations. The time series may contain performance and operational data, as well as metadata observed from a computer application.

Abstract: Visualizing execution of an application in a trace coverage graph includes receiving module trace data gathered during execution of an executable module. The module trace data includes data representing sequences of execution between individual executable components. A trace coverage graph is generated and displayed from the module trace data. The trace coverage graph includes graph nodes that each correspond to a different executable component. The trace coverage graph also includes graph edges that each visually connects two of the graph nodes. Each graph edge visually indicates an amount of trace data present for the sequence of execution between the graph nodes that are connected by the graph edge. Thicker graph edges represent the presence of a larger amount of trace data, and thinner graph edges represent the presence of a lesser amount of trace data.

Abstract: Recommendations may be generated while calculating performance metrics from multiple uses of a software component. A tracing service may collect trace data from multiple uses of a software component, where each use may be done on different conditions. The performance metric analysis may identify various factors that may affect the performance of a software component, then present those factors to a user in different delivery mechanisms. In one such mechanism, a recommended set of hardware and software configurations may be generated as part of an operational analysis of a software component.

Abstract: A module-specific tracing mechanism may trace the usage of a module on behalf of the module developer. The module may be used by multiple application developers, and the tracing system may collect and summarize data for the module in each of the different applications. The data may include usage data as well as performance data. Usage data may include anonymized data for each time the module may be invoked and called, and performance data may include the processing time, memory consumption, and other metrics. The module-specific tracing may be enabled or disabled by an application developer.

Abstract: A database of module performance may be generated by adding tracing components to applications, as well as by adding tracing components to modules themselves. Modules may be reusable code that may be made available for reuse across multiple applications. When tracing is performed on an application level, the data collected from each module may be summarized in module-specific databases. The module-specific databases may be public databases that may assist application developers in selecting modules for various tasks. The module-specific databases may include usage and performance data, as well as stability and robustness metrics, error logs, and analyzes of similar modules. The database may be accessed through links in module description pages and repositories, as well as through a website or other repository.

Abstract: A tracing system may trace applications and their modules, and may make module-specific data available through various interfaces. The tracing system may collect tracer data while an application executes, and may preprocess the data into application-specific and module-specific databases. An analysis engine may further analyze and process these databases to create application-specific views and module-specific views into the data. The application-specific views may be intended for a developer of the application, while the module-specific views may have a public version accessible to everybody and a module developer version that may contain additional details that may be useful to the module developer.

Abstract: A module-specific tracing mechanism may trace the usage of a module on behalf of the module developer. The module may be used by multiple application developers, and the tracing system may collect and summarize data for the module in each of the different applications. The data may include usage data as well as performance data. Usage data may include anonymized data for each time the module may be invoked and called, and performance data may include the processing time, memory consumption, and other metrics. The module-specific tracing may be enabled or disabled by an application developer.

Abstract: A module-specific tracing mechanism may trace the usage of a module on behalf of the module developer. The module may be used by multiple application developers, and the tracing system may collect and summarize data for the module in each of the different applications. The data may include usage data as well as performance data. Usage data may include anonymized data for each time the module may be invoked and called, and performance data may include the processing time, memory consumption, and other metrics. The module-specific tracing may be enabled or disabled by an application developer.

Abstract: A computer monitoring system may predict near term and long term performance by comparing a segment of current time series data with previously observed time series to find matching segments. From a matching segment, a prediction of performance may be made by examining later observations in the time series. Each time series element may include a large number of parameters, and one mechanism for comparing segments may be treating the elements as multi-dimensional vectors and using cosine similarity for finding significant matches. A deployment mechanism may store time series segments in a searchable database, and search the database with a newly observed time series segment for matches.

Abstract: Dimensionality reduction, such as principal component analysis, may be performed against a time series of performance observations for a computer application. A visual representation of the results may be displayed in one, two, or three dimensions, and often show clusters of operational behavior. The representation may be animated to show a sequence of observations and how the behavior of an application may change from one cluster of operation to another. The representation may be further applied to show both a historical view of the observations and new observations. The time series may contain performance and operational data, as well as metadata observed from a computer application.

Abstract: A monitoring system may compare currently observed time series segments to previously identified time series segments that may be precursors to an event. The event may be predicted when a correlation is observed between the time series segments. An event may be identified by a human observer who may identify and classify the event. In some cases, an event may be identified by observing an anomalous behavior and automatically identifying the behavior. The monitoring system may aggregate observed time series from multiple runs of the same application on the same or different execution platform, similar applications on the same or different execution platforms, similar or different users, or any other application on the same or different execution platforms. The identified events may be organized as a set of events that may be applied to new applications to predict events based on observations of other applications.

Abstract: Dimensionality reduction, such as principal component analysis, may be used at least in part to generate a model of time series observations of a computer application. The model may be applied to current and predicted observations. Outliers may be identified from current or predicted observations by analyzing those observations against the model, and statistically relevant outliers may generate alerts or corrective or other action to be taken. The outliers may be analyzed by searching for similar outliers that may have been previously observed, and predicting any future events based on similar observations of the past.

Abstract: A tracing system may trace applications and their modules, and may make module-specific data available through various interfaces. The tracing system may collect tracer data while an application executes, and may preprocess the data into application-specific and module-specific databases. An analysis engine may further analyze and process these databases to create application-specific views and module-specific views into the data. The application-specific views may be intended for a developer of the application, while the module-specific views may have a public version accessible to everybody and a module developer version that may contain additional details that may be useful to the module developer.