Methods and Apparatus for Managing Computing Deployment in Presence of Variable Workload

• US 20070240162A1
• Filed: 06/15/2007
• Published: 10/11/2007
• Est. Priority Date: 03/10/2003
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Surendra, Maheswaran, Raghavachari, Mukund, Ye, Peng, Hellerstein, Joseph, Froehlich, Steven, Wadia, Noshir, Coleman, David, Russell, Lance, Mummert, Todd, Hsiung, Lawrence, Lassettre, Edwin
• Granted Patent: US 8,386,995 B2
• Time in Patent Office: Days
• US Class Current: 718/104
• CPC Class Codes: G06F 11/008 Reliability or availability analysis

Abstract

Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Claims

1. An automated method of managing deployment of one or more resources in a computing environment based on varying workload levels, the method comprising the steps of:

predicting a future workload level based on data associated with the computing environment;

estimating whether a current resource deployment is one of insufficient, sufficient, and overly sufficient to satisfy the future workload level; and

causing one or more actions to be taken when the current resource deployment is estimated to be one of insufficient and overly sufficient to satisfy the future workload level.

2. The method of claim 1, further comprising the step of obtaining the data associated with the computing environment, used by the future workload level predicting step, via monitoring one or more of the resources.

3. The method of claim 1, wherein the action causing step further comprises causing the addition of one or more resources to address the future workload level when the current resource deployment is estimated to be insufficient.

4. The method of claim 1, wherein the action causing step further comprises causing the removal of one or more resources to address the future workload level when the current resource deployment is estimated to be overly sufficient.

5. The method of claim 1, wherein the action causing step further comprises causing the tuning of one or more configuration parameters associated with the resources.

6. The method of claim 1, wherein the action causing step further comprises causing the manipulation of admission queues on the resources.

7. The method of claim 1, wherein the estimating step further comprises estimating whether a current resource deployment is one of insufficient, sufficient, and overly sufficient based on one or more service objectives.

8. The method of claim 1, wherein the step of predicting the future workload level comprises forecasting based on a particular forecast horizon.

9. Apparatus for managing deployment of one or more resources in a computing environment based on varying workload levels, the apparatus comprising:

a memory; and

at least one processor coupled to the memory and operative to;

(i) predict a future workload level based on data associated with the computing environment;

(ii) estimate whether a current resource deployment is one of insufficient, sufficient, and overly sufficient to satisfy the future workload level; and

(iii) cause one or more actions to be taken when the current resource deployment is estimated to be one of insufficient and overly sufficient to satisfy the future workload level.

10. The apparatus of claim 9, wherein the at least one processor is further operative to obtain the data associated with the computing environment, used by the future workload level predicting step, via monitoring one or more of the resources.

11. The apparatus of claim 9, wherein the action causing operation further comprises causing the addition of one or more resources to address the future workload level when the current resource deployment is estimated to be insufficient.

12. The apparatus of claim 9, wherein the action causing operation further comprises causing the removal of one or more resources to address the future workload level when the current resource deployment is estimated to be overly sufficient.

13. The apparatus of claim 9, wherein the action causing operation further comprises causing the tuning of one or more configuration parameters associated with the resources.

14. The apparatus of claim 9, wherein the action causing operation further comprises causing the manipulation of admission queues on the resources.

15. The apparatus of claim 9, wherein the estimating operation further comprises estimating whether a current resource deployment is one of insufficient, sufficient, and overly sufficient based on one or more service objectives.

16. The apparatus of claim 9, wherein the operation of predicting the future workload level comprises forecasting based on a particular forecast horizon.

17. An article of manufacture for managing deployment of one or more resources in a computing environment based on varying workload levels, comprising a machine readable medium containing one or more programs which when executed implement the steps of:

predicting a future workload level based on data associated with the computing environment;

estimating whether a current resource deployment is one of insufficient, sufficient, and overly sufficient to satisfy the future workload level; and

causing one or more actions to be taken when the current resource deployment is estimated to be one of insufficient and overly sufficient to satisfy the future workload level.

18. The article of claim 17, further comprising the step of obtaining the data associated with the computing environment, used by the future workload level predicting step, via monitoring one or more of the resources.

19. The article of claim 17, wherein the action causing step further comprises causing the addition of one or more resources to address the future workload level when the current resource deployment is estimated to be insufficient.

20. The article of claim 17, wherein the action causing step further comprises causing the removal of one or more resources to address the future workload level when the current resource deployment is estimated to be overly sufficient.

21. The article of claim 17, wherein the action causing step further comprises causing the tuning of one or more configuration parameters associated with the resources.

22. The article of claim 17, wherein the action causing step further comprises causing the manipulation of admission queues on the resources.

23. The article of claim 17, wherein the estimating step further comprises estimating whether a current resource deployment is one of insufficient, sufficient, and overly sufficient based on one or more service objectives.

24. The article of claim 17, wherein the step of predicting the future workload level comprises forecasting based on a particular forecast horizon.

25. An automated system for managing deployment of one or more resources in a computing environment based on varying workload levels, the system comprising:

a solution manager operative to;

(i) predict a future workload level based on data associated with the computing environment;

(ii) estimate whether a current resource deployment is one of insufficient, sufficient, and overly sufficient to satisfy the future workload level; and

a deployment manager coupled to the solution manager and operative to;

(i) provide the data associated with the computing environment to the solution manager; and

(ii) effect one or more actions to be taken, in response to the solution manager, when the current resource deployment is estimated by the solution manager to be one of insufficient and overly sufficient to satisfy the future workload level.

26. The system of claim 25, wherein the one or more resources are deployable to implement execution of an application.

27. The system of claim 25, wherein at least one of the solution manager and deployment manager operate autonomically.

28. The system of claim 25, wherein the one or more actions comprise at least one of resource provisioning, resource tuning, and admission control.

29. The system of claim 25, wherein the solution manager estimates whether a current resource deployment is one of insufficient, sufficient, and overly sufficient based on one or more service objectives.

30. A method of attempting to ensure satisfaction of one or more service objectives associated with the execution of an application, the method comprising the steps of:

contracting a service provider to host the application in accordance with the one or more service objectives; and

contracting the service provider to implement an automated system for managing deployment of one or more resources in a computing environment used to execute the application, based on varying workload levels, the system being operative to;

(i) predict a future workload level based on data associated with the computing environment; and

(ii) estimate whether a current resource deployment is one of insufficient, sufficient, and overly sufficient to satisfy the future workload level based on the one or more service objectives; and

(iii) cause one or more actions to be taken when the current resource deployment is estimated to be one of insufficient and overly sufficient to satisfy the future workload level.