Automatic modeling of virtual resources with sizing recommendations

Patent metadata

Field	Value
Publication number	US-9553827-B2
Application number	US-201514626236-A
Country	US
Kind code	B2
Filing date	Feb 19, 2015
Priority date	Feb 19, 2015
Publication date	Jan 24, 2017
Grant date	Jan 24, 2017

Abstract

A method includes accessing a database comprising a respective non-linear scalability model for each of a plurality of physical resources and each of a plurality of virtual resources in a virtualization environment. The method also includes generating a respective capacity consumption model for each of the plurality of virtual resources based on the non-linear scalability models. The method further includes determining a deviation from a predetermined threshold range in the respective capacity consumption model for a first virtual resource in the plurality of virtual resources. The method additionally includes determining a slope of the respective capacity consumption model for the first virtual resource, and determining a sizing recommendation for components of the first virtual resource based on the slope and the deviation. The method also includes modifying at least one of the components of the first virtual resource based on the sizing recommendation.

First claim

What is claimed is:

1. A method, comprising:
accessing a database comprising a respective non-linear scalability model for each of a plurality of physical resources and each of a plurality of virtual resources in a virtualization environment;
generating, using a processor, a respective capacity consumption model for each of the plurality of virtual resources based on the non-linear scalability models;
determining a deviation from a predetermined threshold range in the respective capacity consumption model for a first virtual resource in the plurality of virtual resources;
determining a slope of the respective capacity consumption model for the first virtual resource;
determining a sizing recommendation for components of the first virtual resource based on the slope and the deviation; and
modifying at least one of the components of the first virtual resource based on the sizing recommendation.

2. The method of claim 1 , further comprising:
receiving a plurality of virtual resource templates, wherein determining the sizing recommendation further comprises determining a first virtual resource template in the plurality of virtual resource templates that accommodates the respective capacity consumption model for the first virtual resource.

3. The method of claim 1 , further comprising:
determining whether a resource pool for the virtualization environment can accommodate implementation of the sizing recommendation on the first virtual resource.

4. The method of claim 1 , further comprising:
consolidating the first virtual resource based on the sizing recommendation, wherein the predetermined threshold range comprises a lower bound, and wherein the deviation is determined based on values in the respective capacity consumption model for the first virtual resource that are below the lower bound.

5. The method of claim 1 , further comprising:
increasing virtual computing resources for the first virtual resource based on the sizing recommendation, wherein the predetermined threshold range comprises an upper bound, and wherein the deviation is determined based on values in the respective capacity consumption model for the first virtual resource that are above the upper bound.

6. The method of claim 1 , further comprising:
receiving a processing capacity consumption threshold range; and
receiving a memory capacity consumption threshold range, wherein the predetermined threshold range comprises the processing capacity consumption threshold range and the memory capacity consumption threshold range.

7. The method of claim 1 , further comprising:
automatically determining the predetermined threshold range based on historical performance of the respective capacity consumption model for the first virtual resource.

8. A computer configured to access a storage device, the computer comprising:
a processor; and
a non-transitory, computer-readable storage medium storing computer-readable instructions that when executed by the processor cause the computer to perform:
accessing a database comprising a respective non-linear scalability model for each of a plurality of physical resources and each of a plurality of virtual resources in a virtualization environment;
generating a respective capacity consumption model for each of the plurality of virtual resources based on the non-linear scalability models;
determining a deviation from a predetermined threshold range in the respective capacity consumption model for a first virtual resource in the plurality of virtual resources;
determining a slope of the respective capacity consumption model for the first virtual resource;
determining a sizing recommendation for components of the first virtual resource based on the slope and the deviation; and
modifying at least one of the components of the first virtual resource based on the sizing recommendation.

9. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
receiving a plurality of virtual resource templates, wherein determining the sizing recommendation further comprises determining a first virtual resource template in the plurality of virtual resource templates that accommodates the respective capacity consumption model for the first virtual resource.

10. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
determining whether a resource pool for the virtualization environment can accommodate implementation of the sizing recommendation on the first virtual resource.

11. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
consolidating the first virtual resource based on the sizing recommendation, wherein the predetermined threshold range comprises a lower bound, and wherein the deviation is determined based on values in the respective capacity consumption model for the first virtual resource that are below the lower bound.

12. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
increasing virtual computing resources for the first virtual resource based on the sizing recommendation, wherein the predetermined threshold range comprises an upper bound, and wherein the deviation is determined based on values in the respective capacity consumption model for the first virtual resource that are above the upper bound.

13. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
receiving a processing capacity consumption threshold range; and
receiving a memory capacity consumption threshold range, wherein the predetermined threshold range comprises the processing capacity consumption threshold range and the memory capacity consumption threshold range.

14. The computer of claim 8 , wherein the computer-readable instructions further cause the computer to perform:
automatically determining the predetermined threshold range based on historical performance of the respective capacity consumption model for the first virtual resource.

15. A computer program product comprising:
a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code comprising:
computer-readable program code configured to access a database comprising a respective non-linear scalability model for each of a plurality of physical resources and each of a plurality of virtual resources in a virtualization environment;
computer-readable program code configured to generate a respective capacity consumption model for each of the plurality of virtual resources based on the non-linear scalability models;
computer-readable program code configured to determine a deviation from a predetermined threshold range in the respective capacity consumption model for a first virtual resource in the plurality of virtual resources;
computer-readable program code configured to determine a slope of the respective capacity consumption model for the first virtual resource;
computer-readable program code configured to determine a sizing recommendation for components of the first virtual resource based on the slope and the deviation; and
computer-readable program code configured to modify at least one of the components of the first virtual resource based on the sizing recommendation.

16. The computer program product of claim 15 , wherein the computer-readable program code further comprises:
computer-readable program code configured to receive a plurality of virtual resource templates, wherein determining the sizing r

Assignees

• Ashby Jr John Wiley
• Varadaraju Balaji
• Ca Inc

Inventors

• Ashby Jr John Wiley
• Varadaraju Balaji

Classifications

• H04L41/024

  using relational databases for representation of network management data, e.g. managing via structured query language [SQL] · CPC title

• H04L43/0817

  by checking functioning · CPC title

• H04L41/0896

  Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities (flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76) · CPC title

• H04L47/78 Primary

  Architectures of resource allocation · CPC title

• H04L43/16

  Threshold monitoring · CPC title