Soasta, Inc.

Oracle International Corporation

Akamai Technologies, Inc.

Tal Broda

Michael Hemmert

Kenneth C Gardner

Kendall Cosby

Matthew Solnit

Darrell Esau

Tana Christine Jackson

Charles A Vazac

Craig R Powers

Daniel J Bartow

Mukul Sharma

Blake T Sullivan

Edward Farrell

Philip Santosh Tellis

Xi Li

Ben Bubenheim

Wilson Stockman

Cliff Crocker

Kimberly McGraw

Yuan Gao

Max Starets

Dipankar Bajpai

Shailesh Vinayaka

Tim J Beauchamp

Geoffrey Deane Owen Nicholls

David Allen Schneider

Thomas M Lounibos

Bobby Kritzer

Fei Xie

Eric Ellis

Shilpi Nayak

Giri B Senji

Matt Solnit

Albert Hong

Ed Salazar

Ben Wood

Congxiao Lu

A method includes providing a graphical user interface (GUI) that allows a user to dynamically change virtual user (VU) distributions of a load test performed on a target website or web application during test run-time. The GUI allowing the user to make a change to a current ramp profile of one or more VU distributions responsive to application of first user input. The first input including dragging an icon to a position in a first graph, the position denoting a future number of VUs at a future time. Following application of the first input, the change to the current ramp profile is visually displayed on a second graph in real-time as the load test progresses.

Virtual user ramp controller for load test analytic dashboard

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 processor-implemented method includes providing an analytic dashboard with a graphical user interface (GUI) that outputs aggregated results streaming in real-time of a load test performed on a target website. The load test consists of a plurality of virtual users simulated by one or more load servers that execute a test composition on one or more webpages of the website. A waterfall chart is produced on the analytic dashboard that includes a plurality of timeline bars. Each of the timeline bars represents an aggregated result for a resource of the one or more webpages across all of the virtual users. The timeline bars change in real-time as the load test progresses.

System and method for real-time visualization of website performance data

A method for real-time analysis of results from a load test performed on a target website includes calculating 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 calculated from data points received by each of the load server instances from the target website. The first-level aggregated test results include a sum of the data points, a count of the number of the data points, a sum of squares of the data points, and an average of the data points. A standard deviation result (STDEV) is calculated and chart is generated on a display via a graphical user interface. The chart provides a visual representation of a performance metric for the load test based on the standard deviation result.

Load test charts with standard deviation and percentile statistics

A system for worldwide cloud-based testing of mobile applications includes a plurality of mobile computing devices geographically distributed across a plurality of different countries. One or more servers are connected with the mobile computing devices over one or more networks. The one or more servers run a program for playback of a test composition which includes a timed sequence of clips on the mobile computing devices. The timed sequence of clips include one or more messages each of which instructs a precise gesture-based action applied to at least one object displayed on the touch-sensitive display screen. The precise gesture-based action corresponds to a functional aspect of the mobile application and consists of a plurality of data elements previously captured from inside the mobile application while the mobile application was subject to the gesture-based user input entered via the touch-sensitive display screen.

Private device cloud for global testing of mobile applications

A method includes providing a graphical user interface (GUI) that displays a view of the globe as from outer space. The view including a geographic distribution of beacons having one or more visual attributes. Each beacon corresponds to one or more real users who are accessing a website, web application or mobile app from a geographic location. The visual attributes include an indicator of a performance metric representative of an experience of the one or more real users of the website, web application, or mobile app. Each beacon is generated in real-time from aggregated data obtained in real-time from one or more corresponding real user sessions on the website, web application or mobile app. The beacons are periodically refreshed with the visual attributes changing in response to measured changes in the geographic distribution, a total number of real users at the location, or the performance indicator at the location.

Animated globe showing real-time web user performance measurements

Active waterfall charts for continuous, real-time visualization of website performance data

A computer-implemented method includes scanning a clip of messages that includes message requests and message responses arranged in a sequence. The scanning is performed based on one or more search parameters and produces a list of one or more name/value pairs. The clip is utilized to perform a load test on a target website. Each name/value pair has a corresponding value. For each name/value pair in the list a message request in the clip is identified where the corresponding value is first used. Then, looking backwards in the sequence from the message request where the corresponding value is first used, prior message responses are located where the corresponding value is found. An extraction point is specified in the clip for the corresponding value as a latest message response in the sequence where the corresponding value was returned from the target website. The corresponding value is then stored as a property.

Session template packages for automated load testing

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 processor-implemented method includes providing an analytic dashboard with a graphical user interface (GUI) that outputs aggregated results streaming in real-time of a load test performed on a target website. Responsive to input of a user on the GUI, the input comprising selection of a source chart and a target chart, a single chart is automatically generated that represents either a combination or a statistical correlation of the source and target charts. The single chart has a left y-axis and an x-axis. The combination or the statistical correlation of the single chart changing in real-time as the load test progresses. A visual representation of the single chart is then produced on the analytic dashboard.

Analytic dashboard with user interface for producing a single chart statistical correlation from source and target charts during a load test

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

A method for cloud-based functional testing of a mobile application includes running a functional test program on a server. The functional test program provides a graphical user interface (GUI) that allows a user to select a mobile application and a mobile computing device having a touch-sensitive display screen for receiving user input. The mobile computing device is located remote to the server. The functional test program launches the mobile application on the mobile computing device via a wireless network connection. The server receives precision elements of each gesture-based input on the touch-sensitive display screen, the precision elements being captured and transmitted from the mobile computing device to the server during execution of the mobile application. The precision elements of each gesture-based input are then recorded in a test clip.

Functional test automation for gesture-based mobile applications

Growing community of inventors

Sunnyvale, CA, United States of America

Tal Broda