US 11,386,371 B2Granted

Systems, apparatus and methods for cost and performance-based movement of applications and workloads in a multiple-provider system

AssigneeTurbonomic, Inc.

InventorsEnlin Xu, Endre Sara, David Olshefski, Ariel Tal, Mor Cohen

Life of this patent

Estimating the term…

Loading patent…

Abstract

Systems, methods and apparatus, including computer program products, are disclosed for regulating access of consumers (e.g., applications, containers, or VMs) to resources and services (e.g., storage). In one embodiment, this regulation occurs through the movement of consumers between different providers of a resource or service, such as a cloud service provider. Moving consumers includes, for example, determining the cost of moving the consumer from a first provider to a second provider. According to various embodiments, the cost of moving the consumer is compared to performance criteria associated with moving the consumer from the first provider to the second provider.

Claims21

Dependent claims

A computer-implemented method, comprising:

determining, by a consumer manager running on a data processor in a computer system, a cost of running a workload on a first provider in the computer system, wherein the first provider is a private datacenter service provider;
causing the workload to be run on the first provider based at least in part on a comparison of the determined cost of running the workload on the first provider with a value of the workload to a requesting computational entity;
determining, after a predetermined period of time has passed since the workload has been run on the first provider or after the determined cost of running the workload has increased by at least a predetermined amount, a cost of running the workload on a second provider in the computer system, wherein the second provider is a cloud-based service provider;
determining a cost of moving the workload to the second provider in the computer system;
determining a cumulative cost actually expended in running the workload on the first provider;
computing a utilization value for running the workload on the second provider based at least in part on the determined cost of running the workload on the second provider, the determined cost of moving the workload to the second provider, the value of the workload to the requesting computational entity, and the determined cumulative cost actually expended in running the workload on the first provider;
causing the workload to be moved to the second provider based at least in part on the utilization value after the utilization value has surpassed a predetermined value;
and
establishing terms of continued running of the workload on the second provider for a predetermined length of time after the workload has moved to the second provider.

6 more elements

A computer-implemented method, comprising:

determining, by a consumer manager running on a data processor in a computer system, a cost of running a workload on a first provider in the computer system, wherein the first provider is a private datacenter service provider, the workload having an associated budget capacity;
causing the workload to be run on the first provider based at least in part on a comparison of the determined cost of running the workload on the first provider with a value of the workload to a requesting computational entity;
determining, after a predetermined period of time has passed since the workload has been run on the first provider or after the determined cost of running the workload has increased by at least a predetermined amount, a cost of running the workload on a second provider in the computer system, wherein the second provider is a cloud-based service provider;
determining a cost of moving the workload to the second provider in the computer system;
determining a cumulative cost actually expended in running the workload on the first provider;
computing a utilization value for running the workload on the second provider based at least in part on the determined cost of running the workload on the second provider, the determined cost of moving the workload to the second provider, the value of the workload to the requesting computational entity, and the determined cumulative cost actually expended in running the workload on the first provider;
causing the workload to be moved to the second provider based at least in part on the utilization value after the utilization value has surpassed a predetermined value;
and
determining a remaining budget capacity of the workload for running on the second provider, the remaining budget capacity corresponding to a difference between the value of the workload to the requesting computational entity and the cumulative cost actually expended in running the workload on the first provider, wherein the utilization value is also based on the determined remaining budget capacity, and wherein the comparison of the determined cost of running the workload on the first provider with the value of the workload to the requesting computational entity depends at least in part on a value in virtual currency units ascribed to the workload by the requesting computational entity.

6 more elements

A computer-implemented method, comprising:

determining, by a consumer manager running on a data processor in a computer system, a cost of running a workload on a first provider in the computer system, wherein the first provider is a private datacenter service provider;
causing the workload to be run on the first provider based at least in part on a comparison of the determined cost of running the workload on the first provider with a value of the workload to a requesting computational entity;
determining, after a predetermined period of time has passed since the workload has been run on the first provider or after the determined cost of running the workload has increased by at least a predetermined amount, a cost of running the workload on a second provider in the computer system, wherein the second provider is a cloud-based service provider;
determining a cost of moving the workload to the second provider in the computer system;
determining a cumulative cost actually expended in running the workload on the first provider;
computing a utilization value for running the workload on the second provider based at least in part on the determined cost of running the workload on the second provider, the determined cost of moving the workload to the second provider, the value of the workload to the requesting computational entity, and the determined cumulative cost actually expended in running the workload on the first provider;
and
causing the workload to be moved to the second provider based at least in part on the utilization value after the utilization value has surpassed a predetermined value,
wherein the cost of running the workload on the second provider satisfies an equation:
1
(
1
-
U
)
2
×
Q
where U denotes a utilization rate of a resource for running the workload on the second provider, and Q denotes a ratio of a quantity of the resource for running the workload on the second provider to the largest capacity of the resource among the first and second providers.

16 more elements

A computer system for managing allocation of workloads, comprising:

a data processor;
and
a consumer manager executable by the data processor, the consumer manager being configured to:
determine a cost for running a workload on a first provider in the computer system, wherein the first provider is a private datacenter service provider;
cause the workload to be run on the first provider based at least in part on a comparison of the determined cost of running the workload on the first provider with a value of the workload to a requesting computational entity;
determine, after a predetermined period of time has passed since the workload has been run on the first provider or after the determined cost of running the workload has increased by at least a predetermined amount, a cost of running the workload on a second provider in the computer system, wherein the second provider is a cloud-based service provider;
determine a cost of moving the workload to the second provider in the computer system;
determine a cumulative cost actually expended in running the workload on the first provider;
compute a utilization value for running the workload on the second provider based at least in part on the determined cost of running the workload on the second provider, the determined cost of moving the workload to the second provider, the value of the workload to the requesting computational entity, and the determined cumulative cost actually expended in running the workload on the first provider;
cause the workload to be moved to the second provider based at least in part on the utilization value after the utilization value has surpassed a predetermined value;
and
establish terms of continued running of the workload on the second provider for a predetermined length of time after the workload has moved to the second provider.

9 more elements

A computer system for managing allocation of workloads, comprising:

a data processor;
and
a consumer manager executable by the data processor, the consumer manager being configured to:
determine a cost for running a workload on a first provider in the computer system, wherein the first provider is a private datacenter service provider;
cause the workload to be run on the first provider based at least in part on a comparison of the determined cost of running the workload on the first provider with a value of the workload to a requesting computational entity;
determine, after a predetermined period of time has passed since the workload has been run on the first provider or after the determined cost of running the workload has increased by at least a predetermined amount, a cost of running the workload on a second provider in the computer system, wherein the second provider is a cloud-based service provider;
determine a cost of moving the workload to the second provider in the computer system;
determine a cumulative cost actually expended in running the workload on the first provider;
compute a utilization value for running the workload on the second provider based at least in part on the determined cost of running the workload on the second provider, the determined cost of moving the workload to the second provider, the value of the workload to the requesting computational entity, and the determined cumulative cost actually expended in running the workload on the first provider;
and
cause the workload to be moved to the second provider based at least in part on the utilization value after the utilization value has surpassed a predetermined value,
wherein the consumer manager is further configured to determine the cost of running the workload on the second provider based on an equation:
1
(
1
-
U
)
2
×
Q
where U denotes a utilization rate of a resource for running the workload on the second provider, and U denotes a ratio of a quantity of the resource for running the workload on the second provider to the largest capacity of the resource among the first and second providers.

19 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/118,072Filed 10 Dec 2020 · continuation in part
Priority: 26 Jun 2009
Published: US 2022/0156661 A119 May 2022
Granted: 12 Jul 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification17 codes

G06Q 10/06315
Resource planning, allocation, distributing or scheduling for enterprises or organisations: needs-based resource requirements planning or analysis
G06F 9/45558
Hypervisors; Virtual machine monitors: hypervisor-specific management and integration aspects
G06F 9/5088
Techniques for rebalancing the load in a distributed system: involving task migration
G06Q 20/065
Private payment circuits, e.g. involving electronic currency used among participants of a common payment scheme: using e-cash

Family

Application12/492,890Parent of this continuation-in-part · filed 26 Jun 2009
Application62/077,860Us provisional application · filed 10 Nov 2014
Application62/077,898Us provisional application · filed 10 Nov 2014
Application62/077,852Us provisional application · filed 10 Nov 2014
Application14/539,973Parent of this continuation-in-part · filed 12 Nov 2014
US 8,914,511 B1Parent of this continuation-in-part · filed 16 Dec 2014
Application62/159,883Us provisional application · filed 11 May 2015
Application14/810,302Parent of this continuation-in-part · filed 27 Jul 2015
Application14/810,357Parent of this continuation-in-part · filed 27 Jul 2015
Application14/810,327Parent of this continuation-in-part · filed 27 Jul 2015
Application14/810,284Parent of this continuation-in-part · filed 27 Jul 2015
Application62/255,859Us provisional application · filed 16 Nov 2015
Application62/256,559Us provisional application · filed 17 Nov 2015
Application62/256,645Us provisional application · filed 17 Nov 2015
Application62/316,340Us provisional application · filed 31 Mar 2016
Application15/152,459Parent of this continuation-in-part · filed 11 May 2016
Application15/351,356Parent of this continuation · filed 14 Nov 2016
US 9,805,345 B1Parent of this continuation-in-part · filed 31 Oct 2017
US 9,830,566 B1Parent of this continuation-in-part · filed 28 Nov 2017
US 9,830,192 B1Parent of this continuation-in-part · filed 28 Nov 2017
US 9,852,011 B1Parent of this continuation-in-part · filed 26 Dec 2017
US 9,858,123 B1Parent of this continuation-in-part · filed 2 Jan 2018
US 9,888,067 B1Parent of this continuation-in-part · filed 6 Feb 2018
Application16/394,107Parent of this continuation · filed 25 Apr 2019
US 10,346,775 B1Parent of this continuation · filed 9 Jul 2019
Application16/888,278Parent of this continuation-in-part · filed 29 May 2020
US 10,671,953 B1Parent of this continuation · filed 2 Jun 2020
US 2022/0156661 A1Pre-grant publication · published 19 May 2022
Application16/888,278Parent of this continuation
Application15/351,356Parent of this continuation-in-part
US 11,386,371 B2This patent

From the US filing history. Foreign family members aren’t listed.