Microsoft Technology Licensing, LLC

Srivatsan Parthasarathy

Robert M Fries

Alan C Shi

Ashvinkumar J Sanghvi

James P Finnigan

Michael Grier

William L Scheidel

Dwayne Richard Need

David James Armour

Aravind Ramarathinam

John David Ballard

Ranganathan Srikanth

Jeremy Winter

Benjamin W Slivka

Hadi Partovi

David J D'Souza

Sanjay G Shenoy

RoseMarie FitzSimons

Galen Clyde Hunt

Michael Joseph Toutonghi

Michael V Sliger

Jonathan A Forbes

Michael L Michael

Jeremy D Stone

Craig T Sinclair

Steven J Pratschner

Micheal Dunn

Charles E Kindel, Jr

Scott Field

Edward F Reus

Michael Joseph Healy

Shon Kiran Shah

Eric Joseph Winner

Joseph Dadzie

Peter M Wilson

Charles E Kindel

Vipul Malhotra

Michael Dunn

Rohit Bhardwaj

Chirag Gupta

Prasanna H Sridhar

Alan H Goodman

Evan Herschel Brodie Hissey

Biddappa Nanaiah Berera

Rajeet Nair

Rakesh Malhotra

Shon K Shah

Alan Shi

Michael Michael

Deployment and servicing tasks associated with multi-tier, distributed applications, application environments and data centers are automated so that a person does not have to manually perform these tasks. All of the information describing and defining the distributed service is modeled and stored in a re-useable service template that can be used to drive an automated system to programmatically deploy and manage the service over time. Deployment and servicing of a distributed application can be automated using re-useable models that capture hardware and workload definitions. The re-useable models in the form of service templates enable delta-based servicing of the application. The service can be deployed to one or more physical machines, one or more virtual machines or to a combination thereof. A default deployment plan can be customized with instance-specific customizations of service parameters.

Automated deployment and servicing of distributed applications

Analyzing log data. The method includes obtaining a first bucket of a log data. The first bucket of log data includes a plurality of log lines. The method further includes analyzing the first bucket of log data to identify different sets of similar log lines. The method further includes providing to a user in a user interface one or more summaries of the different sets of similar lines. The summary comprises at least one user selectable indicator representing differences in log lines in a set of similar log lines that when selected by a user in the user interface reveals specific differences in the log lines in the set of similar log lines.

Log summarization and diff

A method includes acts for establishing a subscription for an entity. The method includes receiving, at a cloud service provider, a request from an entity to establish a subscription. The request includes credentials for the entity that are not proper credentials for an organization associated with the entity that the entity should use to access services for the organization. The method further includes performing a corrective action based on detecting one or more factors to determine that the entity is associated with the organization. The method further includes providing services based on the corrective action.

Multi cloud policy enactment via organizations to cloud-provider partnerships

A logical communication path is provided between a target virtual machine (VM) and a host or application communicating with the VM. The target VM runs on a hypervisor host that has a hypervisor and a proxy agent. The hypervisor manages execution of the VM. A mapping is maintained indicating which VMs execute on which hosts. When the host or application is to send a message or packet to the target VM, the mapping is consulted and the hypervisor host hosting the target VM is identified. The message or packet, which may identify the target VM, is transmitted to the hypervisor host. A proxy agent at the hypervisor host selects a communication channel between the hypervisor and the target VM. The hypervisor then passes the message or packet through the selected channel to the target VM.

Host enabled management channel

A system in which a virtual machine manager determines tasks that are to be performed on virtual machines executing on a host computing system. The host computing system further executes an intermediary virtual machine task management module that receives virtual machine tasks from the virtual machine manager. Upon request from the virtual machines, the intermediary module identifies the tasks that are to be performed on the requesting virtual machine to the requesting virtual machine. The virtual machines may perhaps also initiate the performance of such identified tasks. Since the virtual machine itself is initiating contact with the intermediary module, and is not interacting directly with the virtual machine manager, the virtual machine manager need not be in the same sphere of trust as the virtual machine.

Allocating identified intermediary tasks for requesting virtual machines within a trust sphere on a processing goal

Techniques are described to allow substation of blocks into a virtual machine image of an executing virtual machine. A patch may be applied to a first virtual machine image. One or more blocks modified by the patch are identified and copied to a host having a virtual machine executing from a virtual machine image that is based on the first virtual machine image (prior to the patch). While the virtual machine is executing, the substitution blocks are applied (supersede) corresponding original blocks in the virtual machine image. A guest operating system in the virtual machine may either begin using an executable file in a substitution block. In addition, the guest operating system may be forced to flush from memory and cache executable code replaced by the substitution block.

Virtual machine block substitution

Techniques for analyzing virtual machine images are described. In one embodiment, a subset of settings is extracted from one or more virtual machine images, the virtual machine images store therein values of the settings. The settings are used by software executing in virtual machines of the virtual machine images, respectively. A target one of the virtual machine images is selected and target values of the settings are obtained from the target virtual machine image. Sample values of the settings are obtained from a plurality of virtual machine images. The subset formed by identifying similarities and differences of the values between the virtual machine images.

Virtual machine image analysis

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Seattle, WA, United States of America

Srivatsan Parthasarathy