STORAGE AREA NETWORK (SAN) FORECASTING IN A HETEROGENEOUS ENVIRONMENT

• US 20090077340A1
• Filed: 09/14/2007
• Published: 03/19/2009
• Est. Priority Date: 09/14/2007
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Johnson, Randy S., Malone, Christopher M., Northway, Tedrick N.
• Granted Patent: US 7,870,360 B2
• Time in Patent Office: Days
• US Class Current: 711/171
• CPC Class Codes: G06F 3/0605 by facilitating the interaction with a user or administrator
• CPC Class Codes: G06F 3/0653 Monitoring storage devices or systems
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]

Abstract

The present invention provides an approach for SAN forecasting in a heterogeneous environment. Specifically, under the present invention capacity data on the heterogeneous environment is gathered. Capacity management techniques will then be used to analyze the SAN utilization, identify growth trends and patterns. Proactively, plans are made to account for these changes. Thereafter, a Capacity Planning Margin (CPM) will be applied to the forecast to reflect actual customer usage. The CPM adjusted forecasts will then be reviewed. Then, the SAN environment can be monitored by comparing actual vs. planned and return to adjust the forecast accordingly.

Claims

1. A method for forecasting Storage Area Network (SAN) storage in a heterogeneous environment, comprising:

gathering capacity data on the heterogeneous environment;

performing a capacity forecast to analyze the SAN utilization and to identify growth trends and patterns; and

calculating a Capacity Planning Margin (CPM); and

applying the CPM to the capacity forecast.

2. The method of claim 1, further comprising:

reviewing the capacity forecast after applying the CPM; and

monitoring the heterogeneous environment for any variances in the capacity forecast.

3. The method of claim 1, the calculating comprising calculating the following algorithm:

1−

((Allocated SAN*Allocation Threshold)/SAN Install Base)

Where;

i. Allocated SAN=a sum of all SAN storage allocated to each of a set of categories;

ii. Allocation Threshold=a maximum desired utilization level;

iii. SAN Install base=a sum of all installed SAN storage.

4. The method of claim 1, further comprising generating output of the forecasting.

5. The method of claim 1, the output comprising at least one chart depicting storage trends.

6. A system for forecasting Storage Area Network (SAN) storage in a heterogeneous environment, comprising:

a module gathering capacity data on the heterogeneous environment;

a module for performing a capacity forecast to analyze the SAN utilization and to identify growth trends and patterns; and

a module for calculating a Capacity Planning Margin (CPM); and

a module applying the CPM to the capacity forecast.

7. The system of claim 6, further comprising:

a module for reviewing the capacity forecast after applying the CPM; and

a module for monitoring the heterogeneous environment for any variances in the capacity forecast.

8. The system of claim 6, the module for calculating comprising calculating the following algorithm:

1−

((Allocated SAN*Allocation Threshold)/SAN Install Base)

Where;

i. Allocated SAN=a sum of all SAN storage allocated to each of a set of categories;

ii. Allocation Threshold=a maximum desired utilization level;

iii. SAN Install base=a sum of all installed SAN storage.

9. The system of claim 6, further comprising a module for generating output of the forecasting.

10. The system of claim 6, the output comprising at least one chart depicting storage trends.

11. A program product stored on a computer readable medium for forecasting Storage Area Network (SAN) storage in a heterogeneous environment, the computer readable medium comprising program code for causing a computer system to:

gather capacity data on the heterogeneous environment;

perform a capacity forecast to analyze the SAN utilization and to identify growth trends and patterns; and

calculate a Capacity Planning Margin (CPM); and

apply the CPM to the capacity forecast.

12. The program product of claim 11, the computer readable medium further comprising program code for causing the computer system to:

review the capacity forecast after applying the CPM; and

monitor the heterogeneous environment for any variances in the capacity forecast.

13. The program product of claim 11, the computer readable medium further comprising program code for causing the computer system to calculate the CPM using the following algorithm:

1−

((Allocated SAN*Allocation Threshold)/SAN Install Base)

Where;

i. Allocated SAN=a sum of all SAN storage allocated to each of a set of categories;

ii. Allocation Threshold=a maximum desired utilization level;

iii. SAN Install base=a sum of all installed SAN storage.

14. The program product of claim 11, the computer readable medium further comprising program code for causing the computer system to:

generate output of the forecasting.

15. The method of claim 11, the output comprising at least one chart depicting storage trends.

16. A method for deploying a system for forecasting Storage Area Network (SAN) storage in a heterogeneous environment, comprising:

providing a computer infrastructure being operable to;

gather capacity data on the heterogeneous environment;

perform a capacity forecast to analyze the SAN utilization and to identify growth trends and patterns; and

calculate a Capacity Planning Margin (CPM); and

apply the CPM to the capacity forecast.

17. The method of claim 16, the computer infrastructure being further operable to:

review the capacity forecast after applying the CPM; and

monitor the heterogeneous environment for any variances in the capacity forecast.

18. The method of claim 16, the computer infrastructure being further operable to calculate the following algorithm:

1−

((Allocated SAN*Allocation Threshold)/SAN Install Base)

Where;

i. Allocated SAN=a sum of all SAN storage allocated to each of a set of categories;

ii. Allocation Threshold=a maximum desired utilization level;

iii. SAN Install base=a sum of all installed SAN storage.

19. The method of claim 16, the computer infrastructure being further operable to generate output of the forecasting.

20. The method of claim 16, the output comprising at least one chart depicting storage trends.