Merging scaled-down container clusters using vitality metrics

Patent metadata

Field	Value
Publication number	US-10379908-B2
Application number	US-201715608633-A
Country	US
Kind code	B2
Filing date	May 30, 2017
Priority date	May 30, 2017
Publication date	Aug 13, 2019
Grant date	Aug 13, 2019

Abstract

A system for container migration includes containers running instances of an application running on a cluster, an orchestrator with a controller, a memory, and a processor in communication with the memory. The processor executes to monitor a vitality metric of the application. The vitality metric indicates that the application is in either a live state or a dead state. Additionally, horizontal scaling for the application is disabled and the application is scaled-down until the vitality metric indicates that the application is in the dead state. Responsive to the vitality metric indicating that the application is in the dead state, the application is scaled-up until the vitality metric indicates that the application is in the live state. Also, responsive to the vitality metric indication transitioning from the dead state to the live state, the application is migrated to a different cluster while the horizontal scaling of the application is disabled.

First claim

The invention is claimed as follows:

1. A system comprising:
a plurality of containers running one or more instances of an application, wherein the application runs on a cluster;
an orchestrator with a controller;
a memory; and
at least one processor in communication with the memory, wherein the at least one processor executes to:
monitor a vitality metric of the application in the cluster, wherein the vitality metric indicates that the application is in one of a live state and a dead state;
disable horizontal scaling for the application;
scale-down the application until the vitality metric indicates that the application is in the dead state;
responsive to the vitality metric indicating that the application is in the dead state, scale-up the application until the vitality metric indicates that the application is in the live state; and
responsive to the vitality metric indication transitioning from the dead state to the live state, migrate the application to a different cluster, wherein the migration occurs while the horizontal scaling of the application is disabled.

2. The system of claim 1 , wherein the processor executes to cause the controller to scale-up and scale-down the application.

3. The system of claim 2 , wherein the controller scales-down the application by deleting application instances from a database, and the cluster watches the database to kill an application instance that has been deleted from the database.

4. The system of claim 1 , wherein a binary search is utilized in scaling-down and scaling-up the application to obtain an optimum vitality metric for the application.

5. The system of claim 1 , wherein scaling-down the application includes reducing a quantity of application instances of the application.

6. The system of claim 1 , wherein scaling-up the application includes increasing a quantity of application instances of the application.

7. The system of claim 1 , wherein scaling-down and scaling-up the application includes at least one of adjusting disk space allocated to the application, adjusting CPU capacity available to the application, and adjusting memory available to the application.

8. A method comprising:
monitoring, by at least one container, a vitality metric of an application of a plurality of applications in a cluster, wherein the vitality metric indicates that the application is in one of a live state and a dead state;
disabling horizontal scaling for the application;
scaling-down, by a controller, the application until the vitality metric indicates that the application is in the dead state;
responsive to the vitality metric indicating that the application is in the dead state, scaling-up, by the controller, the application until the vitality metric indicates that the application is in the live state; and
responsive to the vitality metric indication transitioning from the dead state to the live state, migrating the application to a different cluster, wherein the migration occurs while the horizontal scaling of the application is disabled.

9. The method of claim 8 , further comprising:
migrating a different application from the plurality of applications in the cluster to the different cluster;
responsive to migrating the plurality of applications in the cluster to the different cluster, enabling horizontal scaling for the plurality of applications; and
horizontally scaling the plurality of applications.

10. The method of claim 8 , wherein the controller scales-down the application by deleting application instances from a database, and the cluster watches the database to kill an application instance that has been deleted from the database.

11. The method of claim 8 , wherein a binary search is utilized in scaling-down and scaling-up the application to obtain an optimum vitality metric for the application.

12. The method of claim 8 , wherein scaling-down the application includes reducing a quantity of application instances of the application.

13. The method of claim 8 , wherein scaling-up the application includes increasing a quantity of application instances of the application.

14. The method of claim 8 , wherein scaling-down and scaling-up the application includes at least one of adjusting disk space allocated to the application, adjusting CPU capacity available to the application, and adjusting memory available to the application.

15. A non-transitory machine readable medium storing code, which when executed by at least one processor, causes the at least one processor to:
monitor a vitality metric of an application of a plurality of applications in a cluster, wherein the vitality metric indicates that the application is in one of a live state and a dead state;
disable horizontal scaling for the application;
scale-down the application until the vitality metric indicates that the application is in the dead state;
responsive to the vitality metric indicating that the application is in the dead state, scale-up the application until the vitality metric indicates that the application is in the live state; and
responsive to the vitality metric indication transitioning from the dead state to the live state, migrate the application to a different cluster, wherein the migration occurs while the horizontal scaling of the application is disabled.

16. The non-transitory machine readable medium of claim 15 , wherein the at least one processor is further caused to:
migrate a different application from the plurality of applications in the cluster to the different cluster;
responsive to migrating the plurality of applications in the cluster to the different cluster, enable horizontal scaling for the plurality of applications; and
horizontally scale the plurality of applications.

17. The non-transitory machine readable medium of claim 15 , wherein a binary search is utilized in scaling-down and scaling-up the application to obtain an optimum vitality metric for the application.

18. The non-transitory machine readable medium of claim 15 , wherein scaling-down the application includes reducing a quantity of application instances of the application.

19. The non-transitory machine readable medium of claim 15 , wherein scaling-up the application includes increasing a quantity of application instances of the application.

20. The non-transitory machine readable medium of claim 15 , wherein scaling-down and scaling-up the application includes at least one of adjusting disk space allocated to the application, adjusting CPU capacity available to the application, and adjusting memory available to the application.

Assignees

• Red Hat Inc

Inventors

• Vyas Jay
• Chen Huamin

Classifications

• G06F9/45558

  Hypervisor-specific management and integration aspects · CPC title

• G06F9/5083

  Techniques for rebalancing the load in a distributed system · CPC title

• G06F11/3055

  Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available (error or fault processing without redundancy G06F11/0703; error detection or correction by redundancy in data representation G06F11/08; error detection or correction of the data by redundancy in operations G06F11/14; error detection or correction by redundancy in hardware G06F11/16) · CPC title

• G06F11/3003

  Monitoring arrangements specially adapted to the computing system or computing system component being monitored · CPC title

• G06F9/5005

  to service a request · CPC title