Methods and systems to evaluate data center resource allocation costs

• US 10,243,815 B2
• Filed: 06/29/2015
• Issued: 03/26/2019
• Est. Priority Date: 06/29/2015
• Status: Active Grant

• Current Assignee: VMware, Inc. (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Shapsa, Lior, Negbi, Mayan, Kochavi, Uri, Yakar, Nadav, Swisa, Elad, Uliel, Yochai, Ginzburg, Guy, Meymann, Yardena, Janovski, Ram
• Primary Examiner(s): Miah, Razu A
• Application Number:
  US14/754,232
• Publication Number:
  US 20160380862A1
• Time in Patent Office: 1,366 Days
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/0817 by checking functioning
• CPC Class Codes: H04L 43/16 Threshold monitoring

Abstract

This disclosure is directed to methods and systems to evaluate resource allocation costs of a data center. Methods and systems compute resource allocation costs of a cloud computing industry to obtain industry benchmarks that are compared with the resource allocation costs of the data center. The comparisons enable IT managers to objectively identify computational resource shortages, resource over investments, and where future investment in computational resources should be made for the data center.

Claims

1. A method executed using one or more processors of a computing environment to evaluate resource allocation costs of a data center, the method comprising:

collecting resource utilization data of a cloud computing industry, the cloud computing industry comprising a plurality of virtual machines (VMs) executed by a plurality of servers, the resource utilization data sent by a plurality of connectors distributed across multiple clouds;

computing resource allocation cost industry benchmarks of the cloud computing industry based on the resource utilization data of the plurality of VMs executed by the plurality of servers;

computing resource allocation costs of the data center based on resource utilization of data center resources of a portion of the plurality of VMs executed by the plurality of servers, the portion of the plurality of VMs being executed by a portion of the plurality of servers within the data center;

computing resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center;

computing monetary impact of the resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center; and

storing the resource allocation costs, the resource allocation gaps, and the monetary impact in one or more data storage devices.

2. The method of claim 1, wherein the resources further comprise central processing units (“

CPUs”

), memory, and data storage.

3. The method of claim 1, wherein computing the resource allocation cost industry benchmarks of the cloud computing industry further comprises:

computing CPU allocation cost industry benchmark based on a total CPU utilization of CPUs in the cloud computing industry;

computing total CPU cost industry benchmark based on a total CPU capacity of the cloud computing industry;

computing memory allocation cost industry benchmark based on a total memory utilization of memory in the cloud computing industry;

computing total memory allocation cost industry benchmark based on a total memory capacity of the cloud computing industry;

computing data storage allocation cost industry benchmark based on a total data storage utilization of data storage in the cloud computing industry;

computing data storage cost industry benchmark based on a total data storage capacity of the cloud computing industry; and

computing total allocation cost industry benchmark as a sum of the CPU, memory, and data storage allocation costs.

4. The method of claim 1, wherein computing the resource allocation costs of the data center further comprises:

computing CPU allocation cost based on a total CPU utilization of CPUs in data center;

computing total CPU cost based on a total CPU capacity of the data center;

computing memory allocation cost based on a total memory utilization of memory in the data center;

computing total memory allocation cost based on a total memory capacity of the data center;

computing data storage allocation cost based on a total data storage utilization of data storage in the data center;

computing data storage cost based on a total data storage capacity of the data center; and

computing total allocation cost as a sum of the CPU, memory, and data storage allocation costs.

5. The method of claim 1, wherein computing the resource allocation gaps further comprises:

computing CPU allocation fraction industry benchmark as a ratio of CPU allocation cost and total CPU cost of the cloud computing industry;

computing CPU allocation fraction of the data center as a ratio of CPU allocation cost and total CPU cost of the data center;

computing CPU allocation gap as a difference between the CPU allocation fraction cloud computing industry benchmark and the CPU allocation faction of the data center;

computing memory allocation fraction industry benchmark as a ratio of memory allocation cost and total memory cost of the cloud computing industry;

computing memory allocation fraction of the data center as a ratio of memory allocation cost and total memory cost of the data center;

computing memory allocation gap as a difference between the memory allocation fraction cloud computing industry benchmark and the memory allocation faction of the data center;

computing data storage allocation fraction industry benchmark as a ratio of data storage allocation cost and total data storage cost of the cloud computing industry;

computing data storage allocation fraction of the data center as a ratio of data storage allocation cost and total data storage cost of the data center; and

computing data storage allocation gap as a difference between the data storage allocation fraction cloud computing industry benchmark and the data storage allocation faction of the data center.

6. The method of claim 5, further comprises:

when an absolute value of the CPU allocation gap is greater than a CPU threshold, generating a CPU allocation alert;

when an absolute value of the memory allocation gap is greater than a memory threshold, generating a memory allocation alert; and

when an absolute value of the data storage allocation gap is greater than a data storage threshold, generating a data storage allocation alert.

7. The method of claim 1, wherein computing the resource allocation gaps further comprises:

computing total resource allocation fraction industry benchmark as a ratio of a total resource allocation cost and total virtual data center cost of the cloud computing industry;

computing total resource allocation fraction of the data center as a ratio of a total resource allocation cost and total virtual data center cost of the data center; and

computing total resource allocation gap as a difference between the total resource allocation fraction industry benchmark and the total resource allocation faction of the data center.

8. The method of claim 7, further comprises when an absolute value of the total resource allocation gap is greater than a total resource threshold, generating a total resource allocation alert.

9. The method of claim 1, wherein computing the monetary impact of the resource allocation gaps further comprises:

computing a monetary CPU allocation impact as a product of a CPU allocation gap and a total CPU cost for the data center;

computing a monetary memory allocation impact as a product of a memory allocation gap and the total memory cost for the data center;

computing a data storage allocation impact as a product of a data storage allocation gap and a total storage cost for the data center; and

computing a total resource allocation impact as a product of a total allocation gap and total virtual data center cost of the data center.

10. A system comprising:

one or more processors;

one or more data-storage devices; and

machine-readable instructions stored in the data-storage devices and executed using the one or more processors, the machine-readable instructions

collecting resource utilization data of a cloud computing industry, the cloud computing industry comprising a plurality of virtual machines (VMs) executed by a plurality of servers, the resource utilization data sent by a plurality of connectors distributed across multiple clouds;

computing resource allocation cost industry benchmarks of the cloud computing industry based on the resource utilization data of the plurality of VMs executed by the plurality of servers;

computing resource allocation costs of the data center based on resource utilization of data center resources of a portion of the plurality of VMs executed by the plurality of servers, the portion of the plurality of VMs being executed by a portion of the plurality of servers within the data center;

computing resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center;

computing monetary impact of the resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center; and

storing the resource allocation costs, the resource allocation gaps, and the monetary impact in the one or more data storage devices.

11. The system of claim 10, wherein the resources further comprise central processing units (“

CPUs”

), memory, and data storage.

12. The system of claim 10, wherein computing the resource allocation cost industry benchmarks of the cloud computing industry further comprises:

computing CPU allocation cost industry benchmark based on a total CPU utilization of CPUs in the cloud computing industry;

computing total CPU cost industry benchmark based on a total CPU capacity of the cloud computing industry;

computing memory allocation cost industry benchmark based on a total memory utilization of memory in the cloud computing industry;

computing total memory allocation cost industry benchmark based on a total memory capacity of the cloud computing industry;

computing data storage allocation cost industry benchmark based on a total data storage utilization of data storage in the cloud computing industry;

computing data storage cost industry benchmark based on a total data storage capacity of the cloud computing industry; and

computing total allocation cost industry benchmark as a sum of the CPU, memory, and data storage allocation costs.

13. The system of claim 10, wherein computing the resource allocation costs of the data center further comprises:

computing CPU allocation cost based on a total CPU utilization of CPUs in data center;

computing total CPU cost based on a total CPU capacity of the data center;

computing memory allocation cost based on a total memory utilization of memory in the data center;

computing total memory allocation cost based on a total memory capacity of the data center;

computing data storage allocation cost based on a total data storage utilization of data storage in the data center;

computing data storage cost based on a total data storage capacity of the data center; and

computing total allocation cost as a sum of the CPU, memory, and data storage allocation costs.

14. The system of claim 10, wherein computing the resource allocation gaps further comprises:

computing CPU allocation fraction industry benchmark as a ratio of CPU allocation cost and total CPU cost of the cloud computing industry;

computing CPU allocation fraction of the data center as a ratio of CPU allocation cost and total CPU cost of the data center;

computing CPU allocation gap as a difference between the CPU allocation fraction cloud computing industry benchmark and the CPU allocation faction of the data center;

computing memory allocation fraction industry benchmark as a ratio of memory allocation cost and total memory cost of the cloud computing industry;

computing memory allocation fraction of the data center as a ratio of memory allocation cost and total memory cost of the data center;

computing memory allocation gap as a difference between the memory allocation fraction cloud computing industry benchmark and the memory allocation faction of the data center;

computing data storage allocation fraction industry benchmark as a ratio of data storage allocation cost and total data storage cost of the cloud computing industry;

computing data storage allocation fraction of the data center as a ratio of data storage allocation cost and total data storage cost of the data center; and

computing data storage allocation gap as a difference between the data storage allocation fraction cloud computing industry benchmark and the data storage allocation faction of the data center.

15. The system of claim 14, further comprises:

when an absolute value of the CPU allocation gap is greater than a CPU threshold, generating a CPU allocation alert;

when an absolute value of the memory allocation gap is greater than a memory threshold, generating a memory allocation alert; and

when an absolute value of the data storage allocation gap is greater than a data storage threshold, generating a data storage allocation alert.

16. The system of claim 10, wherein computing the resource allocation gaps further comprises:

computing total resource allocation fraction industry benchmark as a ratio of a total resource allocation cost and total virtual data center cost of the cloud computing industry;

computing total resource allocation fraction of the data center as a ratio of a total resource allocation cost and total virtual data center cost of the data center; and

computing total resource allocation gap as a difference between the total resource allocation fraction industry benchmark and the total resource allocation faction of the data center.

17. The system of claim 16, further comprises when an absolute value of the total resource allocation gap is greater than a total resource threshold, generating a total resource allocation alert.

18. The system of claim 10, wherein computing the monetary impact of the resource allocation gaps further comprises:

computing a monetary CPU allocation impact as a product of a CPU allocation gap and a total CPU cost for the data center;

computing a monetary memory allocation impact as a product of a memory allocation gap and the total memory cost for the data center;

computing a data storage allocation impact as a product of a data storage allocation gap and a total storage cost for the data center; and

computing a total resource allocation impact as a product of a total allocation gap and total virtual data center cost of the data center.

19. A non-transitory computer-readable medium encoded with machine-readable instructions that implement a method carried out by one or more processors of a computer system to perform the operations of

collecting resource utilization data of a cloud computing industry, the cloud computing industry comprising a plurality of servers configured to execute a plurality of virtual machines (VMs), the resource utilization data comprising utilization of the VMs sent by a plurality of connectors distributed across multiple clouds;

computing resource allocation cost industry benchmarks of the cloud computing industry based on the resource utilization data of the plurality of VMs executed by the plurality of servers;

computing resource allocation costs of the data center based on resource utilization of data center resources of a portion of the plurality of VMs executed by the plurality of servers, the portion of the plurality of VMs being executed by a portion of the plurality of servers within the data center;

computing resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center;

computing monetary impact of the resource allocation gaps between the resource allocation cost industry benchmarks and the resource allocation costs of the data center; and

storing the resource allocation costs, the resource allocation gaps, and the monetary impact in the one or more data storage devices.

20. The medium of claim 19, wherein the resources further comprise central processing units (“

CPUs”

), memory, and data storage.

21. The medium of claim 19, wherein computing the resource allocation cost industry benchmarks of the cloud computing industry further comprises:

computing CPU allocation cost industry benchmark based on a total CPU utilization of CPUs in the cloud computing industry;

computing total CPU cost industry benchmark based on a total CPU capacity of the cloud computing industry;

computing memory allocation cost industry benchmark based on a total memory utilization of memory in the cloud computing industry;

computing total memory allocation cost industry benchmark based on a total memory capacity of the cloud computing industry;

computing data storage allocation cost industry benchmark based on a total data storage utilization of data storage in the cloud computing industry;

computing data storage cost industry benchmark based on a total data storage capacity of the cloud computing industry; and

computing total allocation cost industry benchmark as a sum of the CPU, memory, and data storage allocation costs.

22. The medium of claim 19, wherein computing the resource allocation costs of the data center further comprises:

computing CPU allocation cost based on a total CPU utilization of CPUs in data center;

computing total CPU cost based on a total CPU capacity of the data center;

computing memory allocation cost based on a total memory utilization of memory in the data center;

computing total memory allocation cost based on a total memory capacity of the data center;

computing data storage allocation cost based on a total data storage utilization of data storage in the data center;

computing data storage cost based on a total data storage capacity of the data center; and

computing total allocation cost as a sum of the CPU, memory, and data storage allocation costs.

23. The medium of claim 19, wherein computing the resource allocation gaps further comprises:

computing CPU allocation fraction industry benchmark as a ratio of CPU allocation cost and total CPU cost of the cloud computing industry;

computing CPU allocation fraction of the data center as a ratio of CPU allocation cost and total CPU cost of the data center;

computing CPU allocation gap as a difference between the CPU allocation fraction cloud computing industry benchmark and the CPU allocation faction of the data center;

computing memory allocation fraction industry benchmark as a ratio of memory allocation cost and total memory cost of the cloud computing industry;

computing memory allocation fraction of the data center as a ratio of memory allocation cost and total memory cost of the data center;

computing memory allocation gap as a difference between the memory allocation fraction cloud computing industry benchmark and the memory allocation faction of the data center;

computing data storage allocation fraction industry benchmark as a ratio of data storage allocation cost and total data storage cost of the cloud computing industry;

computing data storage allocation fraction of the data center as a ratio of data storage allocation cost and total data storage cost of the data center; and

computing data storage allocation gap as a difference between the data storage allocation fraction cloud computing industry benchmark and the data storage allocation faction of the data center.

24. The medium of claim 23, further comprises:

when an absolute value of the CPU allocation gap is greater than a CPU threshold, generating a CPU allocation alert;

when an absolute value of the memory allocation gap is greater than a memory threshold, generating a memory allocation alert; and

when an absolute value of the data storage allocation gap is greater than a data storage threshold, generating a data storage allocation alert.

25. The medium of claim 19, wherein computing the resource allocation gaps further comprises:

computing total resource allocation fraction industry benchmark as a ratio of a total resource allocation cost and total virtual data center cost of the cloud computing industry;

computing total resource allocation fraction of the data center as a ratio of a total resource allocation cost and total virtual data center cost of the data center; and

computing total resource allocation gap as a difference between the total resource allocation fraction industry benchmark and the total resource allocation faction of the data center.

26. The medium of claim 25, further comprises when an absolute value of the total resource allocation gap is greater than a total resource threshold, generating a total resource allocation alert.

27. The medium of claim 19, wherein computing the monetary impact of the resource allocation gaps further comprises:

computing a monetary CPU allocation impact as a product of a CPU allocation gap and a total CPU cost for the data center;

computing a monetary memory allocation impact as a product of a memory allocation gap and the total memory cost for the data center;

computing a data storage allocation impact as a product of a data storage allocation gap and a total storage cost for the data center; and

computing a total resource allocation impact as a product of a total allocation gap and total virtual data center cost of the data center.