Predictive layer pre-provisioning in container-based virtualization

Patent metadata

Field	Value
Publication number	US-10146563-B2
Application number	US-201615227233-A
Country	US
Kind code	B2
Filing date	Aug 3, 2016
Priority date	Aug 3, 2016
Publication date	Dec 4, 2018
Grant date	Dec 4, 2018

Abstract

Using a metadata of a layer, a prediction factor including a level of participation of the layer in a set of container images is computed. Each container image includes a corresponding set of layers and is usable to configure a container in a container-based virtualized data processing environment. Using a set of levels of participation corresponding to a set of layers, and using a condition in a prediction algorithm, a subset of layers that have to be pre-provisioned at a node is predicted. The subset of layers is adjusted, to form an adjusted subset of layers, by looking ahead at a container requirement of a workload that is planned for processing at a future time. The adjusted subset of layers is caused to be provisioned on the node prior to the future time.

First claim

What is claimed is:

1. A method comprising:
computing, using a metadata of a layer, a prediction factor comprising a level of participation of the layer in a set of container images, each container image in the set of container images comprising a corresponding set of layers and being usable to configure a container in a container-based virtualized data processing environment;
predicting, using a set of levels of participation corresponding to a set of layers, and using a condition in a prediction algorithm, a subset of layers that have to be pre-provisioned at a node;
adjusting the subset of layers to form an adjusted subset of layers, by looking ahead at a container requirement of a workload that is planned for processing at a future time; and
causing the adjusted subset of layers to be provisioned on the node prior to the future time.

2. The method of claim 1 , further comprising:
further adjusting the adjusted subset of layers to form a second adjusted subset of layers, by removing a second layer from the adjusted subset, the second layer being likely to be already provisioned on the node at the future time.

3. The method of claim 1 , further comprising:
further adjusting the adjusted subset of layers to form a second adjusted subset of layers, by adding a second layer to the adjusted subset, the second layer being likely to be needed on the node due to the workload at the future time.

4. The method of claim 1 , wherein the node is identified by only a node type.

5. The method of claim 1 , further comprising:
selecting from the set of levels a subset of levels, each level in the subset of levels exceeding a threshold level of participation; and
selecting the subset of layers corresponding to the selected subset of levels.

6. The method of claim 1 , further comprising:
computing a second prediction factor comprising a frequency at which a second layer is requested for configuring the container; and
including, responsive to the frequency exceeding a threshold frequency, the second layer in the subset of layers.

7. The method of claim 1 , further comprising:
determining, as a second prediction factor, whether the layer depends on a second layer for configuring the container; and
including, responsive to the layer depending on the second layer, the second layer in the subset of layers.

8. The method of claim 1 , further comprising:
determining, as a second prediction factor, a size of a second layer; and
including, responsive to the size of the second layer exceeding a threshold size, the second layer in the subset of layers.

9. The method of claim 1 , wherein the condition comprises a type of a workload that is likely to be sent to the host.

10. The method of claim 1 , wherein the condition comprises a type of a workload that is likely to be sent to the host at the future time.

11. The method of claim 1 , wherein the condition comprises another container that is likely to be configured on the host at the future time.

12. The method of claim 1 , wherein the condition comprises another workload that is likely to be processed on the host at the future time.

13. The method of claim 1 , wherein the condition comprises an availability of another node where the workload can be processed at the future time.

14. The method of claim 1 , wherein the condition comprises a level of access associated with at least one of (i) the workload, (ii) the node, and (iii) the container.

15. The method of claim 1 , wherein the condition comprises an availability of a license to a software product to process the workload at the future time.

16. The method of claim 1 , wherein the metadata of the layer include information identifying each container image from the set of container images in which the layer is participating.

17. The method of claim 1 , further comprising:
constructing an instruction, the instruction specifying the adjusted subset of layers, the node;
sending the instruction to a provisioning system, the sending causing the provisioning prior to the future time.

18. The method of claim 17 , wherein the instruction further specifies the future time.

19. A computer usable program product comprising a computer-readable storage medium, and program instructions stored on the computer-readable storage medium, the stored program instructions comprising:
program instructions to compute, using a metadata of a layer, a prediction factor comprising a level of participation of the layer in a set of container images, each container image in the set of container images comprising a corresponding set of layers and being usable to configure a container in a container-based virtualized data processing environment;
program instructions to predict, using a set of levels of participation corresponding to a set of layers, and using a condition in a prediction algorithm, a subset of layers that have to be pre-provisioned at a node;
program instructions to adjust the subset of layers to form an adjusted subset of layers, by looking ahead at a container requirement of a workload that is planned for processing at a future time; and
program instructions to cause the adjusted subset of layers to be provisioned on the node prior to the future time.

20. The computer usable program product of claim 19 , further comprising:
program instructions to further adjust the adjusted subset of layers to form a second adjusted subset of layers, by removing a second layer from the adjusted subset, the second layer being likely to be already provisioned on the node at the future time.

21. The computer usable program product of claim 19 , further comprising:
program instructions to further adjust the adjusted subset of layers to form a second adjusted subset of layers, by adding a second layer to the adjusted subset, the second layer being likely to be needed on the node due to the workload at the future time.

22. The computer usable program product of claim 19 , wherein the node is identified by only a node type.

23. The computer usable program product of claim 19 , wherein the computer usable code is stored in a computer readable storage device in a data processing system, and wherein the computer usable code is transferred over a network from a remote data processing system.

24. The computer usable program product of claim 19 , wherein the computer usable code is stored in a computer readable storage device in a server data processing system, and wherein the computer usable code is downloaded over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system.

25. A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to compute, using a metadata of a layer, a prediction factor comprising a level of participation of the layer in a set of container images, each container image in the set of container images comprising a corresponding set of layers and being usable to configure a container in a container-based virtualized data processing environment;
program instructions to predict, using a set of levels of participation corr

Assignees

• IBM

Inventors

• Dettori Paolo
• Low Andrew R
• Quirk Aaron J
• Seelam Seetharami R
• Spreitzer Michael J
• Steinder Malgorzata
• Sun Lin

Classifications

• G06F9/5022

  Mechanisms to release resources · CPC title

• G06F9/45533

  Hypervisors; Virtual machine monitors · CPC title

• G06F9/5016

  the resource being the memory · CPC title

• G06F9/5027

  the resource being a machine, e.g. CPUs, Servers, Terminals · CPC title

• G06F9/45558

  Hypervisor-specific management and integration aspects · CPC title