Microsoft Technology Licensing, LLC

Divyachapan Sridharan Padur

Zohar Raz

Min Shao

Shobana Krishnamoorthy

Ilker Celikyilmaz

Rahul Nigam

Nidhi Verma

Mark Raymond Gilbert

Brian G O'Connor

Peter Kenneth Harwood

Randy David Thomson

Chandramouleeswaran Krishnaswamy

Jianfeng Cai

Mustafaraj M Dhrolia

Ankur Jauhari

Donovan Allen Isaak

Mark Gilbert

Esha Sharma

Vadivelan Ramalingam

A method of and system for customizing a rollout process of application features includes providing a list of one or more application features for display on a user interface screen, the software application features being application features that are scheduled for a staged rollout, enabling selection of one of the application features for enrolling in late-stage rollout or opting out of the staged rollout, receiving a request for enrolling a user entity in late-stage rollout or opting the user entity out of the staged rollout, storing a property associated with the user entity in a data store, the property indicative of the user entity enrolling in late-stage rollout or opting out of the staged rollout, accessing the stored property, when selecting a plurality of enterprises or users for the staged rollout of the application feature, and depending on the accessed property, selecting the user entity for late-stage rollout or not selecting the user entity for the staged rollout.

Method and system for providing customized rollout of features

Issues may arise when customers that are highly engaged with application services do not receive reliable feature updates on a predictable schedule. For instance, releasing and updating features may burden cloud infrastructure and/or may not perform properly. Not only are unpredictable feature updates associated with inconsistent customer messaging and potential service disruptions, such unpredictable updates may cause a random end user experience and customer dissatisfaction with the product. The methods and systems address these issues by dynamically ranking tenants and distributing updates and releases to tenants with lower feature usage before distributing to tenants with higher feature usage. The ranking of the tenants may dynamically change based on current usage. In this way, higher ranked tenants receive access to new and updated features after additional regression testing. This quality-driven, phased release of features enables load level management of computing resources as well as a predictable feature experience for end users.

Predictable distribution of program instructions

Various systems and methods for flight delivery are disclosed herein. In one example, a system includes a processor to process a flight configuration delivery service instruction to schedule the flight by sending the flight to a service bus based on an identification of a temperature of the farm. The system may also include the service bus to alert the farm of the flight for the farm to consume, wherein the service bus returns a notification to the flight configuration deliver service for a farm that does not consume the flight. In an example, a memory stores, based on instructions from the flight configuration delivery service, an identification of the farm that did not consume the flight in the memory.

Flight delivery architecture

A system to reduce strain on server farm computing resources by over-riding 'off-peak' patching schedules in response to performance failures occurring on a server farm. Embodiments disclosed herein determine a patching schedule for causing builds of patches to be sequentially installed on server farms during an off-peak usage time-range. Responsive to a performance failure occurring on the server farm, embodiments disclosed herein identify a particular patch that is designed to resolve the performance failure. Then, the patching schedule is over-ridden to expedite an out-of-sequence installation of whichever build is first to include the particular patch. Because resolution of the performance failure is expedited, the impact of the performance failure on the computing resources of the server farm is reduced as compared to existing server farm patching systems.

Enhanced server farm patching system for enabling developers to override off-peak patching schedules

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

A hosted service may include multiple applications and have a large number of active features, each in varying stages of deployment, that are gradually rolled out in one or more deployment environments. The hosted service may include a flight state machine, which may provide policy based flight management for feature rollout. For example, in response to receipt of a flight request associated with a feature of the hosted service, the flight state machine may be configured to retrieve a policy associated with rollout of the feature, determine a flight state, and determine a deployment state of the feature. The flight state machine may then be configured to initiate or continue deployment of the feature in a current deployment environment or initiate deployment of the feature in a next environment based on the policy, the flight state, and the deployment state of the feature.

Policy driven flight management

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Bothell, WA, United States of America

Divyachapan Sridharan Padur