Microsoft Technology Licensing, LLC

Cristina Del Amo Casado

Stephen P DiAcetis

Fernando Gonzalez

Jonathan Matthew Kay

David Mahlon Hoover

Sanjib Saha

Janet Lynn Schneider

Lanny D Natucci, Jr

Jyh-Han Lin

Frank Gorgenyi

Abhishek Kumar Singh

Avnish Kumar Chhabra

Li Xiong

Hiep V Khuu

Chih-Wei Wang

Binit Ranjan Mishra

Mark A Inderhees

Priyanka Bhargavi Vegesna

Muhammad Usman Sharif

Li-Fen Wu

Stuart J Harper

Shaun C Hedrick

Harsh Gupta

Hariharan Jayaraman

Yevgeniy Olegovich Razuvayev

Reza Sherafat Kazemzadeh

Stephen P Diacetis

Lanny D Natucci

Lanny D Natucci Jr

Systems, methods and computer program products are described herein that can be used to help achieve a safe rollout of software in a production datacenter environment. In accordance with certain embodiments, cloud services requests from certain users of a cloud services system (e.g., users that are authorized to receive cloud services via computing devices running test versions of infrastructure software) are dynamically matched to clusters (groups of commonly-managed computing devices called nodes) that are capable of providing the requested services on nodes running test versions of infrastructure software. Within such clusters, the requested services are provided to the users on a subset of cluster nodes that run a test version of an infrastructure software component, while the remaining cluster nodes are not running the particular test version.

Partitioning and orchestrating infrastructure software deployments for safety and agility across diverse configurations and hardware types

Techniques described herein provide multi-factor authentication based on positioning data. Generally described, configurations disclosed herein enable a system to authorize a particular action using positioning data, and possibly other data, associated with an identity. For example, when a user wishes to change a password or access a secured account, the system can authenticate a user if a device associated with the user is located in the secure area. The system can authenticate a user if a requested operation and/or a predetermined pattern of movement associated with the user is detected. For instance, the system allows the user to change the password when the user's computer has followed a predetermined pattern of movement, and when one or more verification procedures meets one or more criteria while the location of the computing device is within the predetermined area.

Multi-factor authentication using positioning data

Techniques described herein provide location-based access control to secured resources. Generally described, configurations disclosed herein enable a system to dynamically modify access to secured resources based on one or more location-related actions. For example, techniques disclosed herein can enable a computing system to control access to resources such as computing devices, display devices, secured locations, and secured data. In some configurations, the techniques disclosed herein can enable controlled access to secured resources based, at least in part, on an invitation associated with a location and positioning data indicating a location of a user.

Location-based access control of secured resources

The location of a computing device is determined, and the location of an area of interest that is a geographic area referred to as a geo-fence is identified. The accuracy of the determined location of the computing device has an associated uncertainty, so the exact position of the computing device cannot typically be pinpointed. In light of this, the uncertainty associated with the determined location is evaluated relative to the size of the geo-fence in order to determine whether the computing device is inside the geo-fence or outside the geo-fence. Based on this determination, various actions can be taken if the user is entering the geo-fence, exiting the geo-fence, remaining in the geo-fence for at least a threshold amount of time, and so forth.

Detecting geo-fence events using varying confidence levels

A determination of whether a mobile computing device is indoors or outdoors can incorporate any of a variety of factors to make an efficient and accurate determination of indoor-outdoor status. Such a status can be useful for use in conjunction with positioning services. Features such as bounding boxes, activity determination, and the like can be used to strike a balance between power consumption and accuracy. A positive user experience with fewer false detections can result.

Accounting for indoor-outdoor transitions during position determination

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Cristina Del Amo Casado