IP Library Granted Patent US 10,331,383
Granted Patent B2
US 10,331,383 · App. 15/191,609 · Granted Jun 25, 2019

Updating storage migration rates

Inventors: John V. Delaney (Kildalkey, IE); Anthony M. Hunt (Hopewell Junction, NY); Maeve M. O'Reilly (Rathdrum, IE); Daniel P. Toulan (Leland, NC); Clea A. Zolotow (Key West, FL)
Assignee: International Business Machines Corporation
G06F3/067G06F3/061G06F3/0647
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Quick Facts
Patent No.
US 10,331,383
App. No.
15/191,609
Granted
Jun 25, 2019
Kind
B2
Abstract

A computer-implemented method includes identifying a storage migration. The storage migration is associated with a storage area network. The storage migration has a storage migration rate associated therewith. The method includes identifying an input/output throughput. The input/output throughput is associated with the storage area network. The input/output throughput stores a throughput rate for the storage area network. The method includes identifying a service level agreement rate for the input/output throughput. The method includes identifying a non-essential workload. The non-essential workload stores a non-essential workload rate associated therewith. The non-essential workload includes that portion of said input/output throughput that is for one or more background processes. The method includes determining an analyzed rate based on the throughput rate, the service level agreement rate, and the non-essential workload rate. The method includes updating the storage migration rate based on the analyzed rate.

Claims (45)

1. A computer-implemented method comprising:

identifying a storage migration, said storage migration being associated with a storage area network, said storage migration having a storage migration rate associated therewith;

identifying an input/output throughput, said input/output throughput being associated with said storage area network, said input/output throughput storing a throughput rate for said storage area network;

identifying a service level agreement rate for said input/output throughput;

identifying a non-essential workload, said non-essential workload storing a non-essential workload rate associated therewith, said non-essential workload comprising that portion of said input/output throughput that is for one or more background processes;

determining an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate; and

updating said storage migration rate based on said analyzed rate.

2. The computer-implemented method of claim 1 , wherein updating said storage migration based on said analyzed rate includes updating a priority level associated with said storage migration.

3. The computer-implemented method of claim 1 , wherein updating said storage migration based on said analyzed rate includes reducing said non-essential workload rate.

4. The computer-implemented method of claim 1 , wherein analyzing said throughput rate, said service level agreement rate, and said non-essential workload rate to yield an analyzed rate is based on predictive analytics, the predictive analytics predicting how removing said non-essential workload from said input/output throughput will impact said storage migration rate.

5. The computer-implemented method of claim 4 , wherein said predictive analytics is based on a normal autoregressive integrated moving average model.

6. The computer-implemented method of claim 1 , wherein determining an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate includes generating an analytics profile, the analytics profile storing variables associated with previous rates.

7. The computer-implemented method of claim 6 , further comprising:

updating said storage migration rate based on said analyzed rate and said analytics profile.

8. A computer program product comprising:

one or more computer readable storage media and program instructions stored on said one or more computer readable storage media, said program instructions comprising instructions to:

identify a storage migration, said storage migration being associated with a storage area network, said storage migration having a storage migration rate associated therewith;

identify an input/output throughput, said input/output throughput being associated with said storage area network, said input/output throughput storing a throughput rate for said storage area network;

identify a service level agreement rate for said input/output throughput;

identify a non-essential workload, said non-essential workload storing a non-essential workload rate associated therewith, said non-essential workload comprising that portion of said input/output throughput that is for one or more background processes;

determine an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate; and

update said storage migration rate based on said analyzed rate.

9. The computer program product of claim 8 , wherein instructions to update said storage migration based on said analyzed rate includes instructions to update a priority level associated with said storage migration.

10. The computer program product of claim 8 , wherein instructions to update said storage migration based on said analyzed rate includes instructions to reduce said non-essential workload rate.

11. The computer program product of claim 8 , wherein instructions to analyze said throughput rate, said service level agreement rate, and said non-essential workload rate to yield an analyzed rate is based on predictive analytics, the predictive analytics predicting how removing said non-essential workload from said input/output throughput will impact said storage migration rate.

12. The computer program product of claim 11 , wherein said predictive analytics is based on a normal autoregressive integrated moving average model.

13. The computer program product of claim 8 , wherein instructions to determine an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate includes instructions to generate an analytics profile, the analytics profile storing variables associated with previous rates.

14. The computer program product of claim 13 , further comprising instructions to:

update said storage migration rate based on said analyzed rate and said analytics profile.

15. A computer system comprising:

one or more computer processors;

one or more computer readable storage media;

computer program instructions; and

said computer program instructions being stored on said computer readable storage media for execution by at least one of said one or more processors, said computer program instructions comprising instructions to:

identify a storage migration, said storage migration being associated with a storage area network, said storage migration having a storage migration rate associated therewith;

identify an input/output throughput, said input/output throughput being associated with said storage area network, said input/output throughput storing a throughput rate for said storage area network;

identify a service level agreement rate for said input/output throughput;

identify a non-essential workload, said non-essential workload storing a non-essential workload rate associated therewith, said non-essential workload comprising that portion of said input/output throughput that is for one or more background processes;

determine an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate; and

update said storage migration rate based on said analyzed rate.

16. The computer system of claim 15 , wherein instructions to update said storage migration based on said analyzed rate includes instructions to update a priority level associated with said storage migration.

17. The computer system of claim 15 , wherein instructions to update said storage migration based on said analyzed rate includes instructions to reduce said non-essential workload rate.

18. The computer system of claim 15 , wherein instructions to analyze said throughput rate, said service level agreement rate, and said non-essential workload rate to yield an analyzed rate is based on predictive analytics, the predictive analytics predicting how removing said non-essential workload from said input/output throughput will impact said storage migration rate.

19. The computer system of claim 18 , wherein said predictive analytics is based on a normal autoregressive integrated moving average model.

20. The computer system of claim 15 , wherein instructions to determine an analyzed rate based on said throughput rate, said service level agreement rate, and said non-essential workload rate includes instructions to generate an analytics profile, the analytics profile storing variables associated with previous rates.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 13, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: KYNDRYL, INC.
Reel/Frame 057885/0644 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 24, 2016
From: DELANEY, JOHN V.; HUNT, ANTHONY M.; O'REILLY, MAEVE M.; TOULAN, DANIEL P.; ZOLOTOW, CLEA A.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 039001/0536 →
Continuity (1)
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