Selecting a configuration for an application

1. A computer-implemented method for selecting from a plurality of full configurations of a storage system an operational configuration for executing an application, the method comprising:

obtaining application performance data for the application on each of a plurality of test configurations;

obtaining benchmark performance data with respect to execution of a benchmark on the plurality of full configurations, one or more degraded configurations of the full configurations and the plurality of test configurations;

estimating a metric for executing the application on each of the plurality of full configurations based on the application performance data and the benchmark performance data; and

selecting the operational configuration from among the plurality of full configurations based on the metric.

2. The computer-implemented method recited in claim 1 , wherein the metric comprises at least one performance characteristic.

3. The computer-implemented method recited in claim 1 , wherein the metric comprises at least one dependability characteristic.

4. The computer-implemented method recited in claim 1 , wherein the metric comprises at least one performability characteristic.

5. The computer-implemented method recited in claim 1 , wherein the metric relates to a desired service level.

6. The computer-implemented method recited in claim 1 , wherein configuration options that define the plurality of full configurations comprise a number of separate copies or fragments into which a data object is split, a number of parities fragments stored at a local datacenter, a number of additional parity fragments stored at a remote data center, and/or a number of parities to be written before a data write is considered complete.

7. The computer-implemented method recited in claim 1 , comprising:

assigning a probability of occurrence for each of the degraded configurations; and

taking into account the probability of occurrence for each of the degraded configurations when estimating the metric for executing the application on each of the plurality of full configurations.

8. The computer-implemented method recited in claim 1 , wherein the application employs a Key-Binary Large Object (Blob) Archive.

9. A computer system for estimating metrics for executing an application on each of a plurality of full configurations of a storage system, the computer system comprising:

a processor that is adapted to execute stored instructions; and

a memory device that stores instructions, the memory device comprising stored instructions that, when executed by the processor, cause the processor to:

obtain application performance data for the application on each of a plurality of test configurations;

obtain benchmark performance data with respect to execution of a benchmark on the plurality of full configurations, one or more degraded configurations of the full configurations and the plurality of test configurations; and

estimate a metric for executing the application on each of the plurality of full configurations based on the application performance data and the benchmark performance data.

10. The computer system recited in claim 9 , wherein the metric comprises at least one performance characteristic.

11. The computer system recited in claim 9 , wherein the metric comprises at least one dependability characteristic.

12. The computer system recited in claim 9 , wherein the metric comprises at least one performability characteristic.

13. The computer system recited in claim 9 , wherein the metric relates to a desired service level.

14. The computer system recited in claim 9 , wherein configuration options that define the plurality of full configurations comprise a number of separate copies or fragments into which a data object is split, a number of parities fragments stored at a local datacenter, a number of additional parity fragments stored at a remote data center, and/or a number of parities to be written before a data write is considered complete.

15. The computer system recited in claim 9 , wherein the memory device comprises stored instructions that, when executed by the processor, cause the processor to:

assign a probability of occurrence for each of the degraded configurations; and

take into account the probability of occurrence for each of the degraded configurations when estimating the metric for executing the application on each of the plurality of full configurations.

16. The computer system recited in claim 9 , wherein the application employs a Key-Binary Large Object (Blob) Archive.

17. A non-transitory, computer-readable medium, comprising code configured to direct a processor to:

obtain application performance data for an application on each of a plurality of test configurations;

obtain benchmark performance data with respect to execution of a benchmark on a plurality of full configurations, one or more degraded configurations of the full configurations and the plurality of test configurations; and

estimate a metric for executing the application on each of the plurality of full configurations based on the application performance data and the benchmark performance data.

18. The non-transitory, computer-readable medium recited in claim 17 , wherein the metric comprises at least one performability characteristic.

19. The non-transitory, computer-readable medium recited in claim 17 , wherein the metric relates to a desired service level.

20. The non-transitory, computer-readable medium recited in claim 17 , comprising code to direct a processor to:

assign a probability of occurrence for each of the degraded configurations; and

take into account the probability of occurrence for each of the degraded configurations when estimating the metric for executing the application on each of the plurality of full configurations.