Abstract:
A method for real-time capture of analytics from real users of a native mobile application (app) includes storing a custom metric/timer definition for a native mobile application (app) in a configuration file on a server. The custom metric/timer definition includes one or more identifiers of an element or object of the native mobile app selected by touch gesture input via a user interface on a mobile device running the native mobile app in a special mode. The configuration file is downloaded from the server to real users running the native mobile app on associated mobile devices. Immediately thereafter, one or more collector servers receive data beaconed in real-time from the associated mobile devices of the real users. The beaconed data includes custom metric/timer data obtained from the custom metric/timer definition.
Abstract:
A method for real-time capture of analytics from real users of a native mobile application (app) includes storing a custom metric/timer definition for a native mobile application (app) in a configuration file on a server. The custom metric/timer definition includes one or more identifiers of an element or object of the native mobile app selected by touch gesture input via a user interface on a mobile device running the native mobile app in a special mode. The configuration file is downloaded from the server to real users running the native mobile app on associated mobile devices. Immediately thereafter, one or more collector servers receive data beaconed in real-time from the associated mobile devices of the real users. The beaconed data includes custom metric/timer data obtained from the custom metric/timer definition.
Abstract:
A method for real-time capture of analytics from real users of a native mobile application (app) includes storing a custom metric/timer definition for a native mobile application (app) in a configuration file on a server. The custom metric/timer definition includes one or more identifiers of an element or object of the native mobile app selected by touch gesture input via a user interface on a mobile device running the native mobile app in a special mode. The configuration file is downloaded from the server to real users running the native mobile app on associated mobile devices. Immediately thereafter, one or more collector servers receive data beaconed in real-time from the associated mobile devices of the real users. The beaconed data includes custom metric/timer data obtained from the custom metric/timer definition.
Abstract:
A method for real-time capture of actual user experiences on a website, web application or mobile app includes receiving, in first servers, one or more beacons, each containing data items. Each beacon is generated in real-time from a user session. The data items are aggregated in one or more first sets of N data buckets associated with each of the first servers. Each of the first servers transmits the data items of each of the N data buckets to a second server over a network, which further aggregates the data items received in one or more sets of N data buckets corresponding to and identically configured as the data buckets of the first servers. The corresponding data contents of the one or more second sets of N data buckets is aggregated into one or more final sets of N data buckets used in generating a real-time analytic dashboard.
Abstract:
A method for real-time capture of actual user experiences on a website, web application or mobile app includes receiving, in first servers, one or more beacons, each containing data items. Each beacon is generated in real-time from a user session. The data items are aggregated in one or more first sets of N data buckets associated with each of the first servers. Each of the first servers transmits the data items of each of the N data buckets to a second server over a network, which further aggregates the data items received in one or more sets of N data buckets corresponding to and identically configured as the data buckets of the first servers. The corresponding data contents of the one or more second sets of N data buckets is aggregated into one or more final sets of N data buckets used in generating a real-time analytic dashboard.
Abstract:
An automated method for provisioning a grid used to run a load test on a target website includes sending one or more requests in a multi-threaded manner to at least one cloud provider, the one or more requests for an allocation of N load server instances and M result server instances which comprise the grid. Requests received back from the cloud provider are also handled in a multi-threaded manner; any errors occurring during the allocation being corrected automatically. The N load server instances and the M result server instances are then verified to be operational and correctly running software deployed to provide defined test services. Errors identified during the verification are automatically corrected either by attempting to restart a failed instance or allocating a different instance.
Abstract:
A method for real-time capture of actual user experiences on a website, web application or mobile app includes receiving, in first servers, one or more beacons, each containing data items. Each beacon is generated in real-time from a user session. The data items are aggregated in one or more first sets of N data buckets associated with each of the first servers. Each of the first servers transmits the data items of each of the N data buckets to a second server over a network, which further aggregates the data items received in one or more sets of N data buckets corresponding to and identically configured as the data buckets of the first servers. The corresponding data contents of the one or more second sets of N data buckets is aggregated into one or more final sets of N data buckets used in generating a real-time analytic dashboard.
Abstract:
An automated method for provisioning a grid used to run a load test on a target website includes sending one or more requests in a multi-threaded manner to at least one cloud provider, the one or more requests for an allocation of N load server instances and M result server instances which comprise the grid. Requests received back from the cloud provider are also handled in a multi-threaded manner; any errors occurring during the allocation being corrected automatically. The N load server instances and the M result server instances are then verified to be operational and correctly running software deployed to provide defined test services. Errors identified during the verification are automatically corrected either by attempting to restart a failed instance or allocating a different instance.