Abstract: Techniques and structures to facilitate anomaly detection, including receiving performance metric data at a database system having a plurality of data point values, processing the plurality of data point values via an optimized Extreme Studentized Deviate (ESD) test to detect one or more anomalous data point values within the plurality of data point values, including storing a first set of values representing the largest values of the plurality of data point values and a second set of values representing the smallest values of the plurality of data point values, receiving a first of the plurality of data point values, determining whether the first data point value is to be included in the first set of values or the second set of values and determining that the first data point value is not an anomalous data point value upon a determination that the first data point value is not to be inserted into the first set of values or the second set of values and generating an incident alert upon a detection of one or m

Abstract: Techniques and structures to facilitate anomaly detection within a networking system, including receiving a plurality of performance metric messages at a database system, extracting a plurality of anomaly detection messages included in the performance metric messages, storing the plurality of anomaly detection messages in an in-memory database and executing a machine learning model to process the plurality of anomaly detection messages in the in-memory database to detect whether anomalous usage of the networking system has been detected.

Abstract: Methods and systems are described for creating and/or processing a definition for a dashboard with manually input code and user selections in a graphical user interface. In some implementations, user interface elements are displayed and selections from a user accepted. Responsive to the selections, definitions for one or more visualizations and datasources are automatically generated and displayed in a user interface element that accepts manually input customizations and code from the user. The resulting combination of code and definitions is stored as a definition for the dashboard, which when processed will transform data received from the at least one of the datasources, combine the transformed data with data from another of the datasources, and cause the display of a visualization based on the combined data.

Abstract: Methods and systems are described for creating and/or processing a definition for a dashboard with manually input code and user selections in a graphical user interface. In some implementations, user interface elements are displayed and selections from a user accepted. Responsive to the selections, definitions for one or more visualizations and datasources are automatically generated and displayed in a user interface element that accepts manually input customizations and code from the user. The resulting combination of code and definitions is stored as a definition for the dashboard, which when processed will transform data received from the at least one of the datasources, combine the transformed data with data from another of the datasources, and cause the display of a visualization based on the combined data.

Abstract: System and methods are described for a monitoring system to monitor operations of a distributed computing system and provide feedback to subscribers. The monitoring system includes a data collection engine to receive data items comprising events, metrics, or one or more configurations about a distributed computing system being monitored, and to store selected data items into a message queue. The monitoring system also includes a data processing engine to receive the selected data items from the queue, transform the selected data items into transformed data items based at least in part on one or more settings for a subscriber and the one or more configurations of the distributed computing system, and store the transformed data items into one or more of a database and a cache.

Abstract: Techniques and structures to facilitate anomaly detection within a networking system, including receiving a plurality of performance metric messages at a database system, extracting a plurality of anomaly detection messages included in the performance metric messages, storing the plurality of anomaly detection messages in an in-memory database and executing a machine learning model to process the plurality of anomaly detection messages in the in-memory database to detect whether anomalous usage of the networking system has been detected

Abstract: Techniques and structures to facilitate anomaly detection, including receiving performance metric data at a database system having a plurality of data point values, processing the plurality of data point values via an optimized Extreme Studentized Deviate (ESD) test to detect one or more anomalous data point values within the plurality of data point values, including storing a first set of values representing the largest values of the plurality of data point values and a second set of values representing the smallest values of the plurality of data point values, receiving a first of the plurality of data point values, determining whether the first data point value is to be included in the first set of values or the second set of values and determining that the first data point value is not an anomalous data point value upon a determination that the first data point value is not to be inserted into the first set of values or the second set of values and generating an incident alert upon a detection of one or m

Abstract: Providing offline map functionality. A geographic route from a geographic starting location to a geographic destination location is determined. A determination of whether wireless data coverage is unavailable for at least a portion of the geographic route is made. At least one offline map segment for the portion of the geographic route for which wireless data coverage is unavailable is downloaded to a mobile electronic device prior to the mobile electronic device arriving in the portion of the geographic route for which wireless data coverage is unavailable.