Deploying a virtual machine in a computing environment

• US 9,846,590 B2
• Filed: 08/22/2014
• Issued: 12/19/2017
• Est. Priority Date: 08/26/2013
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Chen, Li Long, Rendahl, Randy A., Zhu, Xiao Yang, Zou, Lin Zhi
• Primary Examiner(s): Kamran, Mehran
• Application Number:
  US14/904,970
• Publication Number:
  US 20160162308A1
• Time in Patent Office: 1,215 Days
• Field of Search: None
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 9/45533 Hypervisors; Virtual machine monitors
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects

Abstract

A method and associated system. A request to deploy a virtual machine in a computing environment is received. The request identifies an ordered sequence of attributes that the virtual machine to be deployed includes. In response to the request, a virtual machine resource usage pattern having attributes matching a subset of attributes in the ordered sequence of attributes is selected, based on an ordering of the attributes in the ordered sequence of attributes. A node on which the virtual machine is to be deployed is selected from two or more nodes in the computing environment, based on the selected virtual machine resource usage pattern and predicted runtime resource requirements of the virtual machine to be deployed.

Claims

1. A method, said method comprising:

receiving, by one or more processors of a computer system, a request to deploy a virtual machine in a computing environment, said request identifying an ordered sequence of attributes that the virtual machine to be deployed comprises;

in response to the request, said one or more processors selecting, from at least one virtual machine resource usage pattern stored in a virtual machine resource usage pattern library, a virtual machine resource usage pattern having attributes matching a subset of attributes in the ordered sequence of attributes, said selecting the virtual machine resource usage pattern based on an ordering of the attributes in the ordered sequence of attributes, wherein the virtual machine resource usage pattern library stores usage patterns for virtual machines previously deployed;

said one or more processors selecting, from a plurality of nodes in the computing environment, a node on which the virtual machine is to be deployed, said selecting the node based on the selected virtual machine resource usage pattern and predicted runtime resource requirements of the virtual machine to be deployed based on historical running data of a plurality of virtual machines;

said one or more processors configuring the virtual machine for being deployed on the selected node; and

said one or more processors deploying the virtual machine on the selected node.

2. The method of claim 1, wherein the at least one virtual machine resource usage pattern is a plurality of virtual machine resource usage patterns, wherein the attributes in the ordered sequence of attributes are denoted and sequenced as A₁, A₂, . . . , A_N, wherein N is at least 2, and wherein said selecting the virtual machine resource usage pattern comprises:

determining a maximum value of M in a range of 1 to N for which a condition is satisfied, wherein the condition is that one or more virtual machine resource usage patterns of the plurality of virtual machine resource usage patterns match A₁, A₂, . . . , A_M.

3. The method of claim 2, wherein said determining the maximum value of M comprises initially setting M=N and subsequently iteratively looping through the ordered sequence of attributes from A_M to A₁ to determine for each iteration of said looping whether the condition is satisfied, and if so then terminating said looping with a final value of M having been determined, and if not then decrementing M by 1 and performing a next iteration of said looping.

4. The method of claim 1, said method further comprising:

said one or more processors updating the selected virtual machine resource usage by using resource usage information of the virtual machine deployed on the selected node at runtime.

5. The method of claim 1, wherein said selecting the node comprises:

predicting the runtime resource requirements of the virtual machine to be deployed, wherein said predicting is based on the historical running data of the plurality of virtual machines, at the plurality of nodes, which have been previously deployed in the computing environment and which comprise the selected virtual machine resource usage pattern; and

selecting the node on which the virtual machine is to be deployed as one node of the plurality of nodes having available resources exceeding the predicted runtime resource requirements of the virtual machine to be deployed.

6. The method of claim 5, wherein the historical running data of the plurality of virtual machines comprises amounts of specified resources previously consumed at runtime by each virtual machine of the plurality of virtual machines.

7. The method of claim 6, wherein said predicting is based on an average of the amounts of each specified resource previously consumed at runtime by each virtual machine of plurality of virtual machines.

8. A computer program product, comprising one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement a method, said method comprising:

said one or more processors receiving a request to deploy a virtual machine in a computing environment, said request identifying an ordered of attributes that the virtual machine to be deployed comprises;

in response to the request, said one or more processors selecting, from at least one virtual machine resource usage pattern stored in a virtual machine resource usage pattern library, a virtual machine resource usage pattern having attributes matching a subset of attributes in the ordered sequence of attributes, said selecting the virtual machine resource usage pattern based on an ordering of the attributes in the ordered sequence of attributes, wherein the virtual machine resource usage pattern library stores usage patterns for virtual machines previously deployed;

said one or more processors selecting, from a plurality of nodes in the computing environment, a node on which the virtual machine is to be deployed, said selecting the node based on the selected virtual machine resource usage pattern and predicted runtime resource requirements of the virtual machine to be deployed based on historical running data of a plurality of virtual machines;

said one or more processors configuring the virtual machine for being deployed on the selected node; and

said one or more processors deploying the virtual machine on the selected node.

9. The computer program product of claim 8, wherein the at least one virtual machine resource usage pattern is a plurality of virtual machine resource usage patterns, wherein the attributes in the ordered sequence of attributes are denoted and sequenced as A₁, A₂, . . . , A_N, wherein N is at least 2, and wherein said selecting the virtual machine resource usage pattern comprises:

determining a maximum value of M in a range of 1 to N for which a condition is satisfied, wherein the condition is that one or more virtual machine resource usage patterns of the plurality of virtual machine resource usage patterns match A₁, A₂, . . . , A_M.

10. The computer program product of claim 9, wherein said determining the maximum value of M comprises initially setting M=N and subsequently iteratively looping through the ordered sequence of attributes from A_M to A₁ to determine for each iteration of said looping whether the condition is satisfied, and if so then terminating said looping with a final value of M having been determined, and if not then decrementing M by 1 and performing a next iteration of said looping.

11. The computer program product of claim 8, said method further comprising:

said one or more processors updating the selected virtual machine resource usage by using resource usage information of the virtual machine deployed on the selected node at runtime.

12. The computer program product of claim 8, wherein said selecting the node comprises:

predicting the runtime resource requirements of the virtual machine to be deployed, wherein said predicting is based on the historical running data of the plurality of virtual machines, at the plurality of nodes, which have been previously deployed in the computing environment and which comprise the selected virtual machine resource usage pattern; and

selecting the node on which the virtual machine is to be deployed as one node of the plurality of nodes having available resources exceeding the predicted runtime resource requirements of the virtual machine to be deployed.

13. A computer system, comprising one or more processors, one or more memories, and one or more computer readable hardware storage devices, said one or more hardware storage devices containing program code executable by the one or more processors via the one or more memories to implement a method, said method comprising:

in response to the request, said one or more processors selecting, from at least one virtual machine resource usage pattern stored in a virtual machine resource usage pattern library, a virtual machine resource usage pattern having attributes matching a subset of attributes in the ordered sequence of attributes, said selecting the virtual machine resource usage pattern based on an ordering of the attributes in the ordered sequence of attributes, wherein the virtual machine resource usage pattern library stores usage patterns for virtual machines previously deployed;

said one or more processors selecting, from a plurality of nodes in the computing environment, a node on which the virtual machine is to be deployed, said selecting the node based on the selected virtual machine resource usage pattern and predicted runtime resource requirements of the virtual machine to be deployed based on historical running data of a plurality of virtual machines;

said one or more processors configuring the virtual machine for being deployed on the selected node; and

said one or more processors deploying the virtual machine on the selected node.

14. The computer system of claim 13, wherein the at least one virtual machine resource usage pattern is a plurality of virtual machine resource usage patterns, wherein the attributes in the ordered sequence of attributes are denoted and sequenced as A₁, A₂, . . . , A_N, wherein N is at least 2, and wherein said selecting the virtual machine resource usage pattern comprises:

determining a maximum value of M in a range of 1 to N for which a condition is satisfied, wherein the condition is that one or more virtual machine resource usage patterns of the plurality of virtual machine resource usage patterns match A₁, A₂, . . . , A_M.

15. The computer system of claim 14, wherein said determining the maximum value of M comprises initially setting M=N and subsequently iteratively looping through the ordered sequence of attributes from A_M to A₁ to determine for each iteration of said looping whether the condition is satisfied, and if so then terminating said looping with a final value of M having been determined, and if not then decrementing M by 1 and performing a next iteration of said looping.

16. The computer system of claim 13, said method further comprising:

said one or more processors updating the selected virtual machine resource usage by using resource usage information of the virtual machine deployed on the selected node at runtime.

17. The computer system of claim 13, wherein said selecting the node comprises:

predicting the runtime resource requirements of the virtual machine to be deployed, wherein said predicting is based on the historical running data of the plurality of virtual machines, at the plurality of nodes, which have been previously deployed in the computing environment and which comprise the selected virtual machine resource usage pattern; and

selecting the node on which the virtual machine is to be deployed as one node of the plurality of nodes having available resources exceeding the predicted runtime resource requirements of the virtual machine to be deployed.