Method and apparatus for capacity optimization and planning in an on-demand computing environment

a technology of capacity optimization and planning, applied in the field of computer resources, to achieve the effect of achieving the effect of reducing costs

Inactive Publication Date: 2006-12-07
IBM CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0007] It is therefore an object of the present invention to provide a system and method for optimally grouping multiple workloads and determining the best set of servers and other computing resources (e.g. memory, disk drives) to handle them.
[0021] A case study conducted on a set of 8 customers supported by pSeries computers has shown savings on CPU requirements of 55%. Even under conservative projected savings of 40%, the overall cost savings are estimated at 15-25%. In the highly competitive hosting marketplace, these are sizable savings.

Problems solved by technology

The choices made to deploy an on-demand utility raise some interesting and inter-related business problems: to make money in this environment implies that customers must share computing resources in a way that minimizes costs.

Method used

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  • Method and apparatus for capacity optimization and planning in an on-demand computing environment
  • Method and apparatus for capacity optimization and planning in an on-demand computing environment
  • Method and apparatus for capacity optimization and planning in an on-demand computing environment

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Embodiment Construction

[0031] Operation of the invention will now be described with reference to a set of example workloads, such as the four shown in FIG. 1, W1 (110), W2 (120), W3 (130) and W4 (140). Each of the workloads in FIG. 1 chart CPU utilization (y axis 150) percentage over time (x axis 160; hours) and have dashed lines showing the 10th (170), 50th (171) and 90th (172) percentiles, respectively. Workload could also be measured in terms of main memory, disk storage or other computing resources, but for the purposes of describing the invention it will be sufficient to consider the central processing resource.

[0032] The initial screen for a preferred embodiment of the invention is shown in FIG. 2. In this implementation there are three steps to operation of the invention. The first step 210 is to choose a file for storage of the workloads to be consolidated. Such a file 310 is shown in FIG. 3. The next step 220 is to select parameters as shown in FIG. 4. The last step 230 is to select and run a cl...

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Abstract

A method and apparatus are disclosed for determining the best cluster of computing resources to handle each of a plurality of workloads by optimally grouping multiple workloads and determining the best resource cluster to handle each group.

Description

BACKGROUND OF THE INVENTION [0001] 1. Field of the Invention [0002] The present invention generally relates to use of computer resources and, more particularly, capacity optimization and planning in an on-demand computing environment. [0003] 2. Background Description [0004] In the business of on-demand computing (or utility computing), a customer pays for what they use and the service provider is free to resell unused capacity to other customers. The resource required to handle a customer's workload is typically determined by the peak demand whereas the actual workload can fluctuate dramatically over time. A corollary to on-demand computing is that a customer with low average resource utilization would expect to save money by paying for what they use as opposed to the dedicated alternative and at the same time have the opportunity to access a pool of greater computing power for dealing with occasional surges of utilization. [0005] The concept of creating diversified portfolios to mi...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): G06F9/46
CPCG06F9/4812G06Q10/06312G06F2209/5012G06Q10/06393G06Q10/06315
Inventor LI, TA-HSINPALEOLOGO, GIUSEPPE ANDREABRIGGS, STEPHEN SCOTT
Owner IBM CORP
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