Microsoft Technology Licensing, LLC

Kavitha Manivannan

Bradley Gene Calder

Ju Wang

Sriram Sankaran

Hemal Khatri

Yang Yang Zhang

Pradeep Kumar Gunda

Marvin McNett, Ii

Shyam Antony

Vaman Bedekar

Arild Einar Skjolsvold

Vanam Bedekar

Yang Zhang

Marvin Mcnett Ii

Systems and methods are provided for assigning and associating resources in a cloud computing environment. Virtual machines in the cloud computing environment can be assigned or associated with pools corresponding to users as dedicated, standby, or preemptible machines. The various states provide users with the ability to reserve a desired level of resources while also allowing the operator of the cloud computing environment to increase resource utilization.

Assignment of resources in virtual machine pools

In various embodiments, systems and methods are presented for providing resources by way of a platform as a service in a distributed computing environment to perform a job. The system may be comprised of a number of components, such as a task machine, a task location service machine, and a high-level location service machines that in combination are useable to accomplish functions provided herein. It is contemplated that the system performs methods for providing resources by determining resources of the system, such as virtual machines, and applying auto-scaling rules to the system to scale those resources. Based on the determination of the auto-scaling rules, the resources may be allocated to achieve a desired result.

Auto-scaling of pool of virtual machines based on auto-scaling rules of user associated with the pool

Systems and methods are presented for providing resources by way of a platform as a service in a distributed computing environment to perform a job. Resources of the system, job performing on the system, and schedulers of the jobs performing on the system are decoupled in a manner that allows a job to easily migrate among resources. It is contemplated that the migration of jobs from a first pool of resource to a second pool of resource is performed by the system without human intervention. The migration of a job may utilize different schedulers for the different resources. Further, it is contemplated that a pool of resources may automatically allocate additional or fewer resources in response to a migration of a job.

Migration of task to different pool of resources based on task retry count during task lease

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Redmond, WA, United States of America

Kavitha Manivannan