Data repository selection within a storage environment

• US 8,234,470 B2
• Filed: 08/25/2009
• Issued: 07/31/2012
• Est. Priority Date: 08/25/2009
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Tevis, Gregory John, Peretz, Ofer, Raichstein, Eran, Van Hise, David Gregory, Wolf, Oren, Wolloch, Uri
• Primary Examiner(s): DUDEK JR, EDWARD J
• Application Number:
  US12/547,412
• Publication Number:
  US 20110055293A1
• Time in Patent Office: 1,071 Days
• Field of Search: 711/162, 711/170, 711/E12.002, 710/38
• US Class Current: 711/162
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/256 in federated or virtual databases

Abstract

Described is a method, system, and computer program product for selecting a data repository within a computing environment. The data repository can exist on multiple target computing systems as a logical entity called a volume or a file system. When selecting at least one data repository, a data protection system of the computing environment analyzes the incoming data from a source computing system, in conjunction with information describing the data repositories. The data repository information, or repository characteristic information, can be stored on a repository volume table (RVT) of the data protection system. By determining a weighted selection score from the analysis of all the information available to the data protection system, the data protection system can intelligently select a data repository for storing data from the source computing system. Further, by tracking repository characteristic information on a continuous or periodic basis, the data protection system can enable emulated views of data that has been stored on the data repositories of the computing environment.

Claims

1. A computing device implemented method for performing data operations within a computing environment, comprising:

a repository volume table module storing repository characteristic information in a repository volume table (RVT) concerning a plurality of data repositories storing data from data sources;

determining an occurrence of a data backup operation to backup data from the data sources;

in response to determining the occurrence of the data backup operation, selecting one of the data repositories for performing the determined data backup operation by using a selection module, wherein the selection module analyzes the repository characteristic information and incoming data information from the data sources for the occurring data backup operation to select at least one of the data repositories, wherein different repositories are selected for different occurring data backup operations with respect to the data sources depending on the selection module analysis of the repository characteristic information and the incoming data information for the data backup operation; and

providing an emulated view of data stored on the data repositories providing backups and a logical view of the data in the data sources at a point-in-time, wherein the logical view provides access and restore of backup data as of the point-in-time.

2. The computing device implemented method of claim 1, further comprising providing the emulated view with the loss of at least one data repository.

3. The computing device implemented method of claim 1, further comprising a selection score determined from analyzing the repository characteristic information and incoming data information.

4. The computing device implemented method of claim 3, wherein the repository characteristic information includes at least one of:

current active job information, current capacity utilization information, current performance utilization information, performance configuration information, availability configuration information, affinity information, and operation type information.

5. The computing device implemented method of claim 4, wherein the selection score includes at least one weighted value to determine if any single repository characteristic information is more or less important than another.

6. The computing device implemented method of claim 1, further comprising maintaining the RVT continuously or on a periodic basis.

7. A method of selecting a data repository of a distributed storage management system, the distributed storage management system containing at least one source computing system coupled to at least one target computing system, the method comprising:

storing repository characteristic information in a repository volume table (RVT) concerning a plurality of data repositories storing data from the at least one source computing system of a data protection system of the distributed management system by using a repository volume table module;

determining an occurrence of a data backup operation to backup data from the at least one source computing system;

in response to determining the occurrence of the data backup operation, selecting one of the data repositories from at least one target computing system for performing the determined data backup operation by using a selection module of the data protection system, wherein the selection module analyzes the repository characteristic information and incoming data information from the at least one source computing system to select at least one of the data repositories, wherein different repositories are selected for different occurring data backup operations with respect to the at least one source computing system depending on the selection module analysis of the repository characteristic information and the incoming data information for the data backup operation; and

providing an emulated view of data stored on the data repositories of at least one target computing system providing backups and a logical view of the data in the data sources at a point-in-time, wherein the logical view provides access and restore of backup data as of the point-in-time.

8. The method of claim 7, further comprising providing the emulated view with the loss of at least one data repository.

9. The method of claim 7, further comprising a selection score determined from analyzing the repository characteristic information and incoming data information.

10. The method of claim 9, wherein the repository characteristic information includes at least one of:

current active job information, current capacity utilization information, current performance utilization information, performance configuration information, availability configuration information, affinity information, and operation type information.

11. The method of claim 10, wherein the selection score includes at least one weighted value to determine if any single repository characteristic information is more or less important than another.

12. The method of claim 7, further comprising maintaining the RVT continuously or on a periodic basis.

13. A computing environment, comprising:

a source computing system having source information;

a data protection system coupled to the source computing system, wherein the data protection system includes a processor and memory, the memory storing instructions executed by the processor to perform operations, the operations comprising;

obtaining repository characteristic information concerning a plurality of data repositories storing data from the source computing system from a repository volume table (RVT);

determining an occurrence of a data backup operation to backup data from the source computing system;

in response to determining the occurrence of the data backup operation, selecting one of the data repositories for performing the determined data backup operation by using a selection module, wherein the selection module analyzes the repository characteristic information and incoming data information from the data sources for the occurring data backup operation to select at least one of the data repositories, wherein different repositories are selected for different occurring data backup operations with respect to the source computing system depending on the selection module analysis of the repository characteristic information and the incoming data information for the data backup operation; and

providing an emulated view of data stored on the data repositories providing backups and a logical view of the data in the source computing system at a point-in-time, wherein the logical view provides access and restore of backup data as of the point-in-time.

14. The computing environment of claim 13, wherein the emulated view is a logical view of data stored on at least one data repository.

15. The computing environment of claim 14, wherein data can be inaccessible because of bad blocks of at least one data repository.

16. The computing environment of claim 13, further comprising a selection score determined by the processor based on analyzing the repository characteristic information and incoming data information.

17. The computing environment of claim 16, wherein the incoming data information includes at least one of:

a source computing system identifier, a service level objective, an application identifier, a volume identifier and data to be protected.

18. The computing environment of claim 16, wherein the repository characteristic information includes at least one of:

current active job information, current capacity utilization information, current performance utilization information, performance configuration information, availability configuration information, affinity information, and operation type information.

19. The computing environment of claim 18, wherein the selection score includes at least one weighted value to determine if any single repository characteristic information is more or less important than another.

20. The computing environment of claim 13, further comprising maintaining the RVT continuously or on a periodic basis.