Microsoft Technology Licensing, LLC

Brian Eugene Kihneman

Dolly Sobhani

Steven Miles Greenberg

Shen Wang

Vijayalakshmi Ramkumar

Clinton Dee Covington

Pavel R Karimov

Zachary P Woodall

Dhruv Joshi

Joseph Milan Filcik

Robert Scott Cooper

Eric Leighton Smith

Chris Seitzinger

Heron Arzaquel Anzures Reyes

Siddharth Dahiya

Todd Haugen

Peter P Baer

Peter Alan Carlin

Sumit Chauhan

Michael Hopkins Smith

Matthew Joseph Koscumb

David William Brown

Alexander Alexandrovich Spiridonov

Gregory L Chan

Daniel J Cole

Russell Sinclair

Tobias Joakim Bertil Ternström

David Michael Jade

Christopher Todd Seitzinger

Ritu Singh

Ankit Kapur

Ajanta Mahato

Kristopher Wayne Langohr

Medhavin Vadhanasindhu

Methods, systems, and computer programs are presented for generating a usage model for predicting user commands in an app. One method includes receiving model information from client devices. The model is obtained at each client device by training a machine-learning program with app usage data. The server generates synthetic data using the models from the client devices. A machine-learning program is trained using the synthetic data to obtain a global model, which receives as input information about recent commands entered on the app and generates an output with a prediction for the next command expected to be received by the app. The information of the global model is transmitted to a first client device, and the app provides at least one command option in the app user interface based on a prediction, generated by the global model, of the next command expected.

App usage models with privacy protection

A system and method for sampling telemetry events are provided. The method includes receiving, by a cloud-based server, a plurality of telemetry events, related to an application, from a plurality of client devices; generating, by the cloud-based server, a sampling model for collecting a telemetry event based on the plurality of telemetry events, where the sampling model defines under what conditions the telemetry event is to be reported by a client device; generating, by the cloud-based server, an instruction for determining whether or not to report an incoming same telemetry event by the client device based on the sampling model; and providing, by the cloud-based server, the instruction to the client device, to allow the client device to determine whether or not to report the incoming same telemetry event based on the instruction.

Sampling of telemetry events to control event volume cost and address privacy vulnerability

Aspects of the present disclosure relate to techniques for mitigating inadvertent user information collection in telemetry data. In examples, user information is used to evaluate telemetry data associated prior to transmission to a server device. If an instance of user information is identified within the telemetry data, a warning indication is generated. The warning indication may be transmitted to the server device either instead of or in combination with the telemetry data. As a result of the warning indication, the software may be modified to resolve the issue that caused the introduction of the user information into the telemetry data, thereby avoiding future instances of inadvertent data collection. In response to the warning indication, the server may be configured to reject similar telemetry data from other devices, thereby avoiding collecting such data from the other devices. The server device may also use the warning indication to remove or otherwise censor previously collected user information from stored telemetry data.

Mitigating inadvertent user information collection in telemetry data

Technologies are disclosed that help developers determine server resource usage caused by client application generated events. Embodiments may be employed while an application is under development to balance the benefit of a given event with an estimated cost to process the event once the application is deployed. One aspect of the present disclosure provides a telemetry application that receives application generated events and estimates a resource cost they cause to data collection servers. The resource cost may be based on historic data captured from similar or related events, as well as data about how often the event and related events are raised by the application.

Real time telemetry monitoring tool

Technologies are described herein for providing a two-tier failover service. A request to access content by an application associated with an application identifier may be identified. A first record corresponding to the application identifier may be retrieved from a database information table. The first record may include a reference identifier, a database name of a database, and a failover value. A second record corresponding to the reference identifier may be retrieved from a server information table. The second record may include an indication of a first server computer as a primary server computer and an indication of a second server computer as a secondary server computer. A connection specification to either the first server computer or the second server computer may be generated based on the first record and the second record.

Two-tier failover service for data disaster recovery

Creating web application using cloud-based friction-free databases without web hosting knowledge. User credentials are received at a web application service for initiating a web application task via client software. The user credentials are analyzed to determine whether to grant the user permission to initiate the requested web application task. The web application task is initiated when the permission is granted. Data associated with the initiated web application task is received at the web application service for analysis of the data to host and render a web application based solely on received data provided without basis of web hosting knowledge.

Creating web applications using cloud-based friction-free databases without requiring web hosting knowledge

A method and system for the graphical specification and modification of reports is disclosed which enables data reports to be easily created via a report design dialogue. The report design dialogue includes a group-level outline panel containing controls for grouping, as well as other report controls such as those for sorting and aggregating. A method and system for creating a group-level outline panel using an existing database report is also disclosed. Finally, a computer-readable medium storing a computer-interpretable data structure that stores one or more report specifications is disclosed.

Easy-to-use data report specification

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Seattle, WA, United States of America

Brian Eugene Kihneman