Microsoft Technology Licensing, LLC

Eli Cortez

Marcus Felipe Fontoura

Ricardo Gouvea Bianchini

Anand Bonde

Thomas Moscibroda

Ajay Mani

Nisarg Tarakkumar Sheth

Ana-Maria Constantin

Yong Xu

Qingwei Lin

Karthikeyan Subramanian

John Lawrence Miller

Si Qin

Shandan Zhou

Shanti Kemburu

Christopher Cowdery

The present disclosure relates to systems, methods, and computer readable media for predicting deployment growth on one or more node clusters and selectively permitting deployment requests on a per cluster basis. For example, systems disclosed herein may apply tenant growth prediction system trained to output a deployment growth classification indicative of a predicted growth of deployments on a node cluster. The system disclosed herein may further utilize the deployment growth classification to determine whether a deployment request may be permitted while maintaining a sufficiently sized capacity buffer to avoid deployment failures for existing deployments previously implemented on the node cluster. By selectively permitting or denying deployments based on a variety of factors, the systems described herein can more efficiently utilize cluster resources on a per-cluster basis without causing a significant increase in deployment failures for existing customers.

Allocating cloud resources in accordance with predicted deployment growth

The present disclosure relates to systems, methods, and computer readable media that utilize a low-impact live-migration system to reduce unfavorable impacts caused as a result of live-migrating computing containers between physical server devices of a cloud computing system. For example, systems disclosed herein evaluates characteristics of computing containers on server devices to determine a predicted unfavorable impact of live-migrating the computing containers between the server devices. Based on the predicted impact, the systems disclosed herein can selectively identify which computing containers to live-migrate as well as carry out live-migration of the select computing containers in such a way the significantly reduces unfavorable impacts to a customer or client device associated with the computing containers.

Minimizing impact of migrating virtual services

A system receives a request to deploy a virtual machine (VM) on one of a plurality of nodes running a plurality of VMs in a cloud computing system. The system receives a predicted lifetime for the VM and an indication of an average lifetime of VMs running on each of the plurality of nodes. The system allocates the VM to a first node when a first policy of collocating VMs with similar lifetimes on a node is adopted and the predicted lifetime is within a predetermined range of the average lifetime of VMs running on the first node. The system allocates the VM to a second node when a second policy of collocating VMs with dissimilar lifetimes on a node is adopted and the predicted lifetime is not within the predetermined range of the average lifetime of VMs running on the second node.

Method for deploying virtual machines in cloud computing systems based on predicted lifetime

A system receives a request to deploy a virtual machine on a node from a plurality of nodes running a plurality of virtual machines in a cloud computing system. The system selects one of the plurality of nodes having a hard disk drive (HDD) input output operations per second (IOPS) value less than an observed HDD IOPS value for the plurality of nodes running the plurality of virtual machines. The system receives a predicted HDD IOPS value for the virtual machine and determines a new HDD IOPS value for the selected node based on the HDD IOPS value for the selected node and the predicted HDD IOPS value for the virtual machine. The system instantiates the virtual machine on the selected node when the new HDD IOPS value for the selected node is less than or equal to the observed HDD IOPS value for the plurality of nodes.

Resource management for virtual machines in cloud computing systems

A system receives a request to deploy a virtual machine on one of a plurality of nodes running a plurality of virtual machines in a cloud computing system. The system receives a predicted lifetime for the virtual machine and an indication of an average lifetime of virtual machines running on each of the plurality of nodes. The system allocates the virtual machine to a first node when a first policy of collocating virtual machines with similar lifetimes on a node is adopted and the predicted lifetime is within a predetermined range of the average lifetime of virtual machines running on the first node. The system allocates the virtual machine to a second node when a second policy of collocating virtual machines with dissimilar lifetimes on a node is adopted and the predicted lifetime is not within the predetermined range of the average lifetime of virtual machines running on the second node.

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Redmond, WA, United States of America

Eli Cortez