Soasta, Inc.

Akamai Technologies, Inc.

Matthew Solnit

Michael Hemmert

Tal Broda

Kenneth C Gardner

Kendall Cosby

Craig R Powers

Tana Christine Jackson

Charles A Vazac

Philip Santosh Tellis

Robert Charles Holcomb

Mukul Sharma

Ben Bubenheim

Thomas M Lounibos

Karl Wardlaw Stewart

Albert Hong

Ben Wood

Bobby Kritzer

Fei Xie

Eric Ellis

Avinash Shenoy

Shilpi Nayak

A computer-implemented method for automatically provisioning a device grid for use in cloud-based functional testing of an application includes providing a graphical user interface (GUI) that allows a user to input search criteria specifying a set of different device characteristics. A search is then performed across one or more device cloud providers to locate available physical devices that match at least one of the device characteristics. The available physical devices are displayed on the GUI. Responsive to selection input of the user, a number of each selected physical device for the device grid are reserved. An application program to test is then loaded on each reserved physical device.

Device cloud provisioning for functional testing of mobile applications

A computer-implemented method includes providing a user interface (UI) that allows a user to select an existing database having cloud storage volumes that contain historical data of one or more customers. A first command input on the UI replicates the existing database is to create one or more new databases. Each of the new databases has new cloud storage volumes created by taking a snapshot of a corresponding one of the volumes of the existing database. Each new database contains the historical data of the existing database such that a new set of databases results. A mapping algorithm is executed in a cloud-computing instance that maps the historical data of each of the one or more customers to produce a shard map. The mapping algorithm includes a round-robin partitioning of the historical data striped by date in a circular order across the new set of databases.

System and method for automated run-tme scaling of cloud-based data store

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.

Cloud-based custom metric/timer definitions and real-time analytics of mobile applications

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.

Real-time analytics of web performance using actual user measurements

A method for real-time analysis of results from a load test performed on a target website includes periodically computing first-level aggregated test results within each of a plurality of load server instances that generate a load on the target website. The first-level aggregated test results are computed from data received by each of the load server instances from the target website every first time interval. The first-level aggregated test results are then periodically sent from each of the load server instances to an associated one of a plurality of analytic server instances every second time interval. The first-level aggregated test results are aggregated by each of the analytic server instances to produce second-level aggregated test results, which test results may then further aggregated to produce third-level aggregated test results at a data storage instance in real-time.

Real-time, multi-tier load test results aggregation

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.

System and method for provisioning and running a cross-cloud test grid

In one embodiment, a graphical user interface ('GUI') enables the efficient composition and execution of a test of a message-based application, Web application, or SOA systems' capacity to receive, process and respond to message traffic. The GUI may be used to generate a test composition by dragging and dropping message clips onto one or more tracks. Each clip includes one or more message, with each track being organized into one or more bands. Each track and each band may run contemporaneously to send messages to a target device or application. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure.

Visual test automation tool for message-based applications, web applications and SOA systems

Growing community of inventors

San Jose, CA, United States of America

Matthew Solnit