Self-terminating or self-shelving virtual machines and workloads

• US 10,394,588 B2
• Filed: 02/10/2016
• Issued: 08/27/2019
• Est. Priority Date: 01/06/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kaufer, Steven R., Matzek, Samuel D.
• Primary Examiner(s): Nguyen, Duy Khuong T
• Assistant Examiner(s): Headley, Melissa A
• Application Number:
  US15/040,809
• Publication Number:
  US 20170192809A1
• Time in Patent Office: 1,294 Days
• Field of Search: None
• CPC Class Codes: G06F 2009/45562 Creating, deleting, cloning virtual machine instances
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 2009/45595 Network integration; Enabling network access in virtual machine instances
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects

Abstract

Methods comprise receiving a request to perform a predefined operation on at least one of a virtual machine and a workload executing on a host in a first cloud computing environment, identifying a set of credentials to access the first cloud computing environment, and initiating performance of the predefined operation on the at least one of the virtual machine and the workload, wherein the predefined operation comprises at least one of: (i) deleting, and (ii) shelving the at least one of the virtual machine and the workload.

Claims

1. A method, comprising:

receiving, by a cloud tuning service from a first workload, a first abstract request to perform a shelving operation on the first workload, wherein the first workload is executing on a first virtual machine on a first host in a first cloud computing environment, of a plurality of cloud computing environments, wherein the cloud tuning service executes on a system external to each of the plurality of cloud computing environments, wherein the first abstract request identifies the first workload but does not identify the first host or the first cloud computing environment, does not include required credentials, and wherein the first abstract request does not include specific operations required to shelve the first workload;

determining, by the cloud tuning service, that use of a first system resource of a plurality of system resources of the first host by the first virtual machine does not exceed a threshold;

upon receiving the first abstract request, generating, by the cloud tuning service operating external to each of the plurality of cloud computing environments, a specific request that is compatible with the first cloud computing environment by;

determining, by the cloud tuning service, based on a predefined configuration, that the first workload is executing on the first host in the first cloud computing environment;

identifying a first set of commands that are specific to the first cloud computing environment based on the predefined configuration, wherein the first set of commands cause the first cloud computing environment to shelve the first workload and wherein the first set of commands includes at least one command that was not specified in the first abstract request; and

identifying a set of login credentials needed to access the first cloud computing environment; and

initiating, by the cloud tuning service, performance of the shelving operation on the first workload using the specific request, wherein the specific request includes the set of login credentials and the first set of commands, and wherein shelving the first workload removes the first workload from the first virtual machine and the first host and stores an image of the first workload in a data store.

2. The method of claim 1, wherein translating the first abstract request comprises:

identifying, by the cloud tuning service, the first set of commands specific to the first cloud computing environment required to fulfill the first abstract request to shelve the first workload.

3. The method of claim 2, wherein the first workload is configured to generate the first abstract request when the first workload completes processing a set of tasks, the method further comprising:

issuing the first set of commands by the cloud tuning service to the first cloud computing environment to initiate shelving of the first workload.

4. The method of claim 1, wherein the set of login credentials comprise:

(i) a login and a password required to initiate performance of the shelving operation on the first workload in the first cloud computing environment, (ii) an indication of the first cloud computing environment, and (iii) an indication of a host machine executing the at least one of the first virtual machine and the first workload.

5. The method of claim 1, further comprising:

monitoring, by the cloud tuning service, use of each of the plurality of system resources by the first workload;

determining, by the cloud tuning service, that the use of a first system resource of the plurality of system resources by the first workload does not exceed the threshold; and

determining, by the cloud tuning service based on the use of the first system resource by the first workload not exceeding the threshold, that the first workload has completed processing a set of tasks.

6. The method of claim 1, wherein the shelving operation is performed on the first workload prior to expiration of a timeout value of the first workload, wherein expiration of the timeout value comprises a time threshold for performing the shelving operation on the first workload.

7. The method of claim 1, further comprising:

monitoring, by the cloud tuning service, use of each of a plurality of system resources by a second workload executing on a second virtual machine on a second host in a second cloud computing environment, of the plurality of cloud computing environments;

determining, by the cloud tuning service, that use of first system resource of the plurality of system resources by the second workload on the second virtual machine on the second host in the second cloud computing environment does not exceed the threshold;

identifying, by the cloud tuning service, a command specific to the second cloud computing environment for deleting the second workload in the second cloud computing environment;

identifying a set of login credentials to access the second cloud computing environment; and

issuing, by the cloud tuning service to the second cloud computing environment, the command specific to the second cloud computing environment for deleting the second workload in the second cloud computing environment.

8. The method of claim 7, further comprising:

monitoring, by the cloud tuning service, use of each of the plurality of system resources by the second virtual machine on the second host in the second cloud computing environment;

determining, by the cloud tuning service, that the use of the first system resource by the second virtual machine on the second host in the second cloud computing environment does not exceed the threshold;

identifying, by the cloud tuning service, a command specific to the second cloud computing environment for deleting the second virtual machine in the second cloud computing environment; and

issuing, by the cloud tuning service to the second cloud computing environment, the command specific to the second cloud computing environment for deleting the second virtual machine in the second cloud computing environment.

9. The method of claim 8, further comprising:

receiving, by the cloud tuning service from a third workload in a third cloud computing environment, of the plurality of cloud computing environments, a request to delete the third workload in the third cloud computing environment;

identifying, by the cloud tuning service, a command specific to the third cloud computing environment for deleting the third workload in the third cloud computing environment; and

issuing, by the cloud tuning service to the third cloud computing environment, the command specific to the third cloud computing environment for deleting the third workload in the third cloud computing environment.

10. The method of claim 9, further comprising:

receiving, by the cloud tuning service from a third virtual machine executing the third workload in the third cloud computing environment, a request to delete the third virtual machine in the third cloud computing environment;

identifying, by the cloud tuning service, a command specific to the third cloud computing environment for deleting the third virtual machine in the third cloud computing environment; and

issuing, by the cloud tuning service to the third cloud computing environment, the command specific to the third cloud computing environment for deleting the third virtual machine in the third cloud computing environment.