Microsoft Technology Licensing, LLC

Doru Constantin Nica

Himanshu Misra

Srihari Busam

Nagaraj Patil

Kiran Nallabothula

Raghavendra Bhuthpur

Sathish Kumar Venkat Rangam

Minjun Wu

Nagaraju Palla

Alexandre Marciano Gimenez

Ansuman Kar

Achal K Shah

George W Routon

Ning Zhuang

Tyrone Sequeira

Shakeel Solkar

Dylan Symington

Katy Chen

Scott A Moody

Svetlana A Borodina

Kevin Matthew Dargie

Yuedong Yin

Ming Yang

Xiaoyu Li

Eddie Fong

Vijayaraghavan Vedantham

A client computing system detects when a problem is encountered with an application and identified problem-specific diagnostic data that is to be collected, given the detected problem. It also identifies one or more problem-specific test or diagnostic analyzers and executes those analyzers to generate additional data. The data that is collected and the data that is generated by the analyzers is packaged and sent to a service computing system for identifying a remedial action that can be performed to address the problem. The remedial action is received and surfaced for the user.

State-based remedial action generation

An issue is detected in the operation of a set of integrated applications. Assistive logic is launched and an application, causing the issue, is identified. Application running logic is controlled to roll the application back to a last known good state.

Integrated application issue detection and correction control

An assistance service through its local client application or agent at a user's device hardware and software environment information and monitor a health of one or more applications. Upon detecting an issue or being activated by the user, the assistance service may perform diagnostic and/or recovery actions. If predefined or dynamically determined recovery actions are inadequate to address the issue, the assistance service may engage a support service providing collected user device environment information and received server environment information to the support service. A history of attempted recovery actions and diagnostic results may also be provided. The assistance service may, through a user interface of its local, client or agent, facilitate communication with the supports service and perform recovery actions, suggested by the support service providing feedback to the support service. When needed, the assistance service may rollback a version of locally installed or server-side applications to address the issue.

On-demand or dynamic diagnostic and recovery operations in conjunction with a support service

Personalized diagnostics, troubleshooting, recovery, and notification based on application state is provided. In some examples, system, application, and device level configuration and usage data may be collected as telemetry data. Upon detection of a crash or similar problem, or upon user activation, an assistance service and/or a local assistance application component may execute diagnostics on the crashed application based on the telemetry data, user credentials, known problems, and other factors which may be recorded by the assistance application and/or other system elements. Suitable recovery actions may be taken. If recovery actions are unsuccessful, diagnostic information may be provided to a support system and the issue elevated. Moreover, collected information may be provided to a system database for generating data insights and determining error patterns.

Personalized diagnostics, troubleshooting, recovery, and notification based on application state

A client utilizes a backchannel messaging infrastructure and information matching logic to measure server performance characteristics at the client without requiring the server to correlate command responses to command requests. The backchannel messaging infrastructure facilitates the sending of messages between clients, and allows a client to send to the interested clients messages containing an activity start timestamp and identifying the requested activity when sending a command request to a server. The information matching logic enables each client to measure server performance by matching command requests, as indicated by the backchannel messages, and command responses based on message types, identification of the sender (i.e., the client that generated the original command request), and identifier attributes that are unique to the command requests and command responses.

Method and system for calculating performance metrics using backchannel messaging and information pattern matching

A facility executes on a central computer system and applies a time-varying load to an application program under test (AUT). The facility executes in a multiple number of modes or hierarchical levels as dictated by information provided in its configuration file. An instance of the facility executing at the highest or first-level of the hierarchy is responsible for spawning numerous subordinate or second-level instances of the facility on, for example, remote computer systems. These second-level instances of the facility may spawn additional subordinate or third-level executors on the same or remote computer systems. Ultimately, the lowest-level or leaf instances of the facility are spawned, and these leaf instances of the facility are responsible for launching the client test program instances that are used to test the AUT.

Method and system for generating and monitoring variable load on an application under test

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Doru Constantin Nica