Detecting resource consumption events over sliding intervals in cloud-based network

• US 8,782,192 B2
• Filed: 05/31/2011
• Issued: 07/15/2014
• Est. Priority Date: 05/31/2011
• Status: Active Grant

• Current Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Original Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Inventors: Morgan, Christopher Edwin
• Primary Examiner(s): Avellino, Joseph E
• Assistant Examiner(s): WU, TSUNG YIN
• Application Number:
  US13/149,235
• Publication Number:
  US 20120311153A1
• Time in Patent Office: 1,141 Days
• Field of Search: None
• US Class Current: 709/223
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/3072 where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
• CPC Class Codes: G06F 11/3433 for load management allocation of a server based on load conditions G06F9/505; load rebalancing G06F9/5083; redistributing the load in a network by a load balancer H04L67/1029
• CPC Class Codes: G06F 11/3438 monitoring of user actions tracking the activity of the user H04L67/535
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 2201/815 Virtual middleware or OS functionality using virtual machines to implement generic software techniques for error detection or fault masking G06F11/1484
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: H04L 12/00 Data switching networks interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units G06F13/00
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level

Abstract

Embodiments relate to systems and methods for detecting resource consumption events over sliding intervals in cloud-based network. A set of aggregate usage history data can record consumption of processor, software, or other resources subscribed to by a set of users, in one cloud or across multiple clouds. An entitlement engine can analyze the usage history data to identify a subscription margin for the subscribed resources, reflecting collective under-consumption of resources by the set of users on a collective basis, over different and/or dynamically updated subscription periods.

Claims

1. A method comprising:

accessing, by a processor, a set of subscription parameters comprising a resource consumption limit for a set of resources consumed by a set of virtual machines;

accessing, by the processor, a set of usage history data comprising at least a set of subscription events for the set of virtual machines;

generating, by the processor, a set of translatable time periods to which the set of subscription events can be assigned, wherein each of the set of translatable time periods is temporally shifted from others of the set of translatable time periods and each of the set of subscription events is assigned to one or more corresponding translatable time periods of the set of translatable time periods;

generating, by the processor, a set of translation outcomes for a user of the set of virtual machines for each of the translatable time periods in view of assigned subscription events, wherein the set of translation outcomes comprises at least an identified change in the set of subscription costs of the user over the set of translatable time periods;

identifying, by the processor, a translated base period from the set of translatable time periods for which the set of subscription parameters will be applied to the usage history in view of applying selection criteria to the set of translation outcomes; and

tracking, by the processor, resource usage of the user in view of the identified translated base period to determine a corresponding set of subscription costs.

2. The method of claim 1, wherein the set of subscription events comprises events exceeding the resource consumption limit for at least one resource in the set of resources.

3. The method of claim 2, wherein exceeding the resource consumption limit comprises exceeding the resource consumption limit by at least one virtual machine in the set of virtual machines.

4. The method of claim 3, wherein exceeding the resource consumption limit comprises exceeding the resource consumption limit by the set of virtual machines collectively.

5. The method of claim 1, wherein generating a set of translatable time periods comprises:

identifying a first time point in a first translatable time period, and

incrementing the first time point of each of the remaining translatable time periods in the set of translatable time periods.

6. The method of claim 5, wherein the incrementing the first time point comprises incrementing the first time point by the smallest time interval recorded in the set of usage history data.

7. The method of claim 1, wherein the identified change comprises determining that the set of subscription costs will decrease in view of the translated base period.

8. The method of claim 7, wherein determining that the set of subscription costs will decrease in view of the translated base period comprises determining that the set of subscription costs will be minimized in view of the translated base period.

9. The method of claim 1, wherein the identified change comprises determining that the set of subscription costs will increase in view of the translated base period.

10. The method of claim 9, wherein determining that the set of subscription costs will increase in view of the translated base period comprises determining that the set of subscription costs will be maximized in view of the translated base period.

11. The method of claim 1, further comprising generating a set of additional translated time periods in view of the translated base period.

12. The method of claim 1, wherein the set of virtual machines are hosted in a cloud-based network.

13. A system comprising:

an interface to a data store to store a set of usage history data for a set of virtual machines consuming a set of resources; and

a processor, to communicate with the data store via the interface, the processor to;

access a set of subscription parameters comprising a resource consumption limit for the set of resources consumed by a set of virtual machines,

access the set of usage history data for the set of virtual machines,

generate a set of translatable time periods to which the set of subscription events can be assigned, wherein each of the set of translatable time periods is temporally shifted from others of the set of translatable time periods and each of the set of subscription events is assigned to one or more corresponding translatable time periods of the set of translatable time periods,

generate a set of translation outcomes for a user of the set of virtual machines for each of the translatable time periods in view of assigned subscription events, wherein the set of translation outcomes comprises at least an identified change in the set of subscription costs of the user over the set of translatable time periods,

identify a translated base period from the set of translatable time periods for which the set of subscription parameters will be applied to the usage history in view of applying selection criteria to the set of translation outcomes, and

track resource usage of the user in view of the identified translated base period to determine a corresponding set of subscription costs.

14. The system of claim 13, wherein the set of subscription events comprises events exceeding the resource consumption limit for at least one resource in the set of resources.

15. The system of claim 14, wherein exceeding the resource consumption limit comprises exceeding the resource consumption limit by at least one virtual machine in the set of virtual machines.

16. The system of claim 15, wherein exceeding the resource consumption limit comprises exceeding the resource consumption limit by the set of virtual machines collectively.

17. The system of claim 13, wherein generating a set of translatable time periods comprises:

identifying a first time point in a first translatable time period, and

incrementing the first time point of each of the remaining translatable time periods in the set of translatable time periods.

18. The system of claim 17, wherein the incrementing the first time point comprises incrementing the first time point by the smallest time interval recorded in the set of usage history data.

19. The system of claim 13, wherein the identified change comprises determining that the set of subscription costs will decrease in view of the translated base period.

20. The system of claim 19, wherein determining that the set of subscription costs will decrease in view of the translated base period comprises determining that the set of subscription costs will be minimized in view of the translated base period.

21. The system of claim 13, wherein the identified change comprises determining that the set of subscription costs will increase in view of the translated base period.

22. The system of claim 21, wherein determining that the set of subscription costs will increase in view of the translated base period comprises determining that the set of subscription costs will be maximized in view of the translated base period.

23. The system of claim 13, the processor further to generate a set of additional translated time periods in view of the translated base period.

24. The system of claim 13, wherein the set of virtual machines are hosted in a cloud-based network.