Microsoft Technology Licensing, LLC

Esha Sharma

Rahul Nigam

Mark Raymond Gilbert

Donovan Allen Isaak

Peter Kenneth Harwood

Chandramouleeswaran Krishnaswamy

Jianfeng Cai

Mustafaraj M Dhrolia

Jay Lu

Eladio Guzman

Mark Gilbert

Mangalam Rathinasabapathy

Divyachapan Sridharan Padur

Ilker Celikyilmaz

Vinod Mukundan Menon

Vadi Ramalingam

Vadivelan Ramalingam

Vinod Menon

A system enables initiation of request driven peak-hour builds to override 'off-peak' patching schedules for updating server applications. An 'off-peak' patching schedule is generated to minimize disruption from installing builds of patches. Notwithstanding the &#x201c;off-peak&#x201d; patching schedule, a tenant administrator initiates request driven peak-hour builds when some performance failure occurs during peak business hours. For example, the tenant administrator may generate a service request that includes incident data that is usable to identify and/or develop a particular patch for resolving the performance failure. Based on the service request, the &#x201c;off-peak&#x201d; patching schedule is overridden to expedite an out-of-sequence installation of a particular patch. In this way, a tenant administrator that becomes aware that some performance failure is disrupting information workers during a peak usage time-range (e.g., business hours) is empowered to initiate a request driven peak-hour build to quickly resolve the performance failure during the peak usage time-range.

Enabling tenant administrators to initiate request driven peak-hour builds to override off-peak patching schedules

In non-limiting examples of the present disclosure, systems, methods and devices for monitoring telemetry data from a cloud-based application service are presented. Telemetry data for a plurality of operations for the cloud-based application service may be analyzed, wherein the analysis comprises comparing a first time series with a second time series, and where data from the second time series relates to operations that were executed prior in time compared with execution of operations related to the first time series. One or more operational changes in the cloud-based application service may be identified based on the analysis, and at least one telemetry monitor may be dynamically configured based on the one or more operational changes that were identified.

Dynamic monitoring on service health signals

A support data generation system detects an indication of a problem within a flighted infrastructure. Based on the detected indication, a feature undergoing implementation within the flighted infrastructure is identified. The identification occurs automatically after the indication is detected. An alert comprises the detected indication and the identified feature is generated and output on a user interface.

Intelligent listening system for agile delivery of cloud services

Methods and systems for managing a flighted software feature. One embodiment provides a system for disabling a flighted software feature enabled for selected users in a computing environment. The system includes a memory storing instructions and an electronic processor coupled to the memory. The electronic processor configured to execute the instructions to determine a set of related service requests submitted by a plurality of users in the computing environment, and, for each of the plurality of users, query a server servicing the user for a list of flighted software features enabled for the user during a predetermined time period. The electronic processor is also configured to determine, based on the list of flighted software features enabled for each of the plurality of users during the predetermined time period, a common flighted software feature, and automatically disable the common flighted software feature for at least one of the plurality of users.

Automated recovery of flighted features based on service requests

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Redmond, WA, United States of America

Esha Sharma