Storage management in a cloud data store

1. A method comprising:

selecting, based at least upon a storage policy and upon one or more characteristics of storage data, one or more storage classes from among a plurality of storage classes of one or more data storage services, wherein selecting the one or more storage classes is further based upon an estimate for a proportion of live data in one or more data objects at a future point in time; and

storing the one or more data objects to the selected one or more storage classes.

2. The method of claim 1 , wherein the storage policy specifies parameters for storage costs.

3. The method of claim 1 , further comprising:

initiating, in response to determining that resources for continued storage of the one or more data objects in the one or more data storage services exceed resources for performing garbage collection on an estimated quantity of data eligible for garbage collection among the one or more data objects, garbage collection on the one or more data objects in the one or more data storage services.

4. The method of claim 3 , wherein initiating garbage collection is further based upon an expected cost savings based on storage cost savings from performing garbage collection compared against access cost expenses for performing one or more cloud-based operations to perform the garbage collection.

5. The method of claim 1 , wherein the estimate for the proportion of live data in the one or more data objects at the future point in time is based upon a model that predicts proportions of live data to garbage collection eligible data for the one or more data objects across multiple periods of time.

6. The method of claim 1 , wherein the one or more data storage services include a cloud-based storage system.

7. The method of claim 1 , wherein the one or more data storage services include a cloud services provider data object store.

8. The method of claim 1 , wherein the storage policy specifies parameters for storage operation response time.

9. The method of claim 1 , wherein the storage policy specifies parameters for data resiliency.

10. The method of claim 1 , wherein the storage policy specifies parameters for service level agreement specifications.

11. A computer program product disposed upon a computer readable storage medium, the computer program product comprising computer program instructions that, when executed, cause a computer to carry out the steps of:

selecting, based at least upon a storage policy and upon one or more characteristics of storage data, one or more storage classes from among a plurality of storage classes of one or more data storage services, wherein selecting the one or more storage classes is further based upon an estimate for a proportion of live data in one or more data objects at a future point in time; and storing the one or more data objects to the selected one or more storage classes.

12. The computer program product of claim 11 , wherein the storage policy specifies parameters for storage operation response time.

13. The computer program product of claim 11 , wherein the computer program instructions, when executed, further cause the computer to carry out the steps of:

initiating, in response to determining that resources for continued storage of the one or more data objects in the one or more data storage services exceed resources for performing garbage collection on an estimated quantity of data eligible for garbage collection among the one or more data objects, garbage collection on the one or more data objects in the one or more data storage services.

14. The computer program product of claim 13 , wherein initiating garbage collection is further based upon an expected cost savings based on storage cost savings from performing garbage collection compared against access cost expenses for performing one or more cloud-based operations to perform the garbage collection.

15. The computer program product of claim 11 , wherein the estimate for the proportion of live data in the one or more data objects at the future point in time is based upon a model that predicts proportions of live data to garbage collection eligible data for the one or more data objects across multiple periods of time.

16. A method comprising:

determining, for one or more data objects stored in a cloud-based data storage service, an estimated quantity of data eligible for garbage collection among the one or more data objects; and

initiating, in response to determining that resources for continued storage of the one or more data objects in the cloud-based data storage service exceed resources for performing garbage collection on the estimated quantity of data eligible for garbage collection among the one or more data objects, garbage collection on the one or more data objects in the cloud-based data storage service, wherein initiating garbage collection is further based upon an estimate for a proportion of live data in one or more data objects at a future point in time.

17. The method of claim 16 , wherein the estimate for the proportion of live data in the one or more data objects at the future point in time is based upon a model that predicts proportions of live data to garbage collection eligible data for the one or more data objects across multiple periods of time.

18. The method of claim 16 , wherein initiating garbage collection is further based upon an expected cost savings based on storage cost savings from performing garbage collection compared against access cost expenses for performing one or more cloud-based operations to perform the garbage collection.

19. The method of claim 16 , wherein the cloud-based data storage service comprises a cloud-based storage system.

20. The method of claim 16 , wherein the cloud-based data storage service is provided by a cloud services provider data object store.