Capacity planning and data placement management in multi-cloud computing environment
In a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, a method maintains a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system. Further, the method manages capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system that represents at least one of one or more pricing models associated with each cloud platform and one or more regulatory policies associated with each cloud platform to enable an environment-wide view of at least one of the pricing models and the regulatory policies of the plurality of cloud platforms.
1. A method comprising:
in a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, maintaining a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system;
managing capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system and generating an environment-wide view of at least one of one or more pricing models associated with the plurality of cloud platforms, one or more regulatory policies associated with the plurality of cloud platforms and data capacity usage of the plurality of cloud platforms;
generating one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data;
selecting one or more generated recommendations; and
causing the implementation of the selected one or more generated recommendations in the multi-cloud computing environment;
wherein generating a given one of the one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data comprises:
identifying one or more modified pricing models and one or more modified regulatory policies associated with respective ones of the plurality of cloud platforms based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
predicting future data capacity usage for at least one of the primary data and the copies of the primary data based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
determining a forecast of where at least a portion of at least one of the primary data and the copies of the primary data should be moved from a current storage location on at least a first one of the plurality of cloud platforms to a new storage location on at least a second one of the plurality of cloud platforms based on the identified one or more modified pricing models, the identified one or more modified regulatory policies and the predicted future data capacity usage; and
determining a change in cost and whether there are any regulatory compliance violations associated with movement of the at least a portion of the at least one of the primary data and the copies of the primary data from the current storage location on at least the first one of the plurality of cloud platforms to the new storage location on at least the second one of the plurality of cloud platforms;
wherein the method is implemented via one or more processing devices each comprising a processor coupled to a memory.
2. The method of claim 1 , wherein the transaction data is time stamped before insertion into the distributed ledger system.
3. The method of claim 1 , wherein the managing step further comprises storing one or more regulatory policies established by the enterprise as at least a portion of the transaction data in the distributed ledger system.
4. The method of claim 1 , wherein the one or more recommendations take into account: violations of the one or more regulatory policies; and costs associated with the one or more pricing models.
5. The method of claim 1 , wherein the environment-wide view captures a complete cost of data capacity distributed across the plurality of cloud platforms.
6. The method of claim 1 , wherein the managing step further comprises projecting multi-cloud computing environment growth over time based on the stored transaction data, and making one or more data placement recommendations based on the projecting step.
7. The method of claim 1 , wherein the managing step further comprises one or more of modeling future pricing for current or future services of a given one of the plurality of cloud platforms and monitoring changes to the one or more regulatory policies, and making one or more data placement recommendations based on the modeling and monitoring steps.
8. The method of claim 7 , wherein the one or more recommendations are based on a current data capacity associated with the multi-cloud computing environment.
9. The method of claim 7 , wherein the one or more recommendations are based on a future data capacity associated with the multi-cloud computing environment.
10. The method of claim 1 , wherein managing capacity planning and data placement for the primary data and the copies of the primary data comprises data that is at least one of publicly available and privately available.
11. An article of manufacture comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes said at least one processing device to perform steps of:
in a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, maintaining a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system;
managing capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system and generating an environment-wide view of at least one of one or more pricing models associated with the plurality of cloud platforms, one or more regulatory policies associated with the plurality of cloud platforms and data capacity usage of the plurality of cloud platforms;
generating one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data;
selecting one or more generated recommendations; and
causing the implementation of the selected one or more generated recommendations in the multi-cloud computing environment;
wherein generating a given one of the one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data comprises:
identifying one or more modified pricing models and one or more modified regulatory policies associated with respective ones of the plurality of cloud platforms based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
predicting future data capacity usage for at least one of the primary data and the copies of the primary data based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
determining a forecast of where at least a portion of at least one of the primary data and the copies of the primary data should be moved from a current storage location on at least a first one of the plurality of cloud platforms to a new storage location on at least a second one of the plurality of cloud platforms based on the identified one or more modified pricing models, the identified one or more modified regulatory policies and the predicted future data capacity usage; and
determining a change in cost and whether there are any regulatory compliance violations associated with movement of the at least a portion of the at least one of the primary data and the copies of the primary data from the current storage location on at least the first one of the plurality of cloud platforms to the new storage location on at least the second one of the plurality of cloud platforms.
12. The article of claim 11 , wherein the one or more recommendations take into account: violations of the one or more regulatory policies; and costs associated with the one or more pricing models.
13. The article of claim 11 , wherein the managing step further comprises storing one or more regulatory policies established by the enterprise as at least a portion of the transaction data in the distributed ledger system.
14. The article of claim 11 , wherein the managing step further comprises one or more of modeling future pricing for current or future services of a given one of the plurality of cloud platforms and monitoring changes to the one or more regulatory policies, and making one or more data placement recommendations based on the modeling and monitoring steps.
15. The article of claim 14 , wherein the one or more recommendations are based on a future data capacity associated with the multi-cloud computing environment.
16. A system comprising:
one or more processing devices configured to:
in a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, maintain a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system;
managing capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system and generating an environment-wide view of at least one of one or more pricing models associated with the plurality of cloud platforms, one or more regulatory policies associated with the plurality of cloud platforms and data capacity usage of the plurality of cloud platforms;
generate one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data;
select one or more generated recommendations; and
cause the implementation of the selected one or more generated recommendations in the multi-cloud computing environment;
wherein generating a given one of the one or more recommendations for the enterprise as to data placement of one of the primary data and the copies of the primary data based on the stored transaction data comprises:
identifying one or more modified pricing models and one or more modified regulatory policies associated with respective ones of the plurality of cloud platforms based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
predicting future data capacity usage for at least one of the primary data and the copies of the primary data based at least in part on at least a portion of the transaction data stored in the distributed ledger system;
determining a forecast of where at least a portion of at least one of the primary data and the copies of the primary data should be moved from a current storage location on at least a first one of the plurality of cloud platforms to a new storage location on at least a second one of the plurality of cloud platforms based on the identified one or more modified pricing models, the identified one or more modified regulatory policies and the predicted future data capacity usage; and
determining a change in cost and whether there are any regulatory compliance violations associated with movement of the at least a portion of the at least one of the primary data and the copies of the primary data from the current storage location on at least the first one of the plurality of cloud platforms to the new storage location on at least the second one of the plurality of cloud platforms.
17. The system of claim 16 , wherein the managing step further comprises storing one or more regulatory policies established by the enterprise as at least a portion of the transaction data in the distributed ledger system.
18. The system of claim 16 , wherein the one or more recommendations take into account: violations of the one or more regulatory policies; and costs associated with the one or more pricing models.
19. The system of claim 16 , wherein the managing step further comprises projecting multi-cloud computing environment growth over time based on the stored transaction data, and making one or more data placement recommendations based on the projecting step.
20. The system of claim 16 , wherein the managing step further comprises one or more of modeling future pricing for current or future services of a given one of the plurality of cloud platforms and monitoring changes to the one or more regulatory policies, and making one or more data placement recommendations based on the modeling and monitoring steps.