Infrastructure correlation engine and related methods

Patent metadata

Field	Value
Publication number	US-10049335-B1
Application number	US-97359910-A
Country	US
Kind code	B1
Filing date	Dec 20, 2010
Priority date	Oct 6, 2009
Publication date	Aug 14, 2018
Grant date	Aug 14, 2018

Abstract

A method includes displaying to a user, via a display element, a user interface that allows a user to characterize business demand of an organization; receiving, from a user, via one or more input devices, input characterizing business demand; automatically comparing, utilizing one or more processors and one or more memory elements of a computer system, qualities of business demand to attributes of ensembles comprising implementations of reusable patterns, the qualities of business demand being based at least in part on the received input characterizing business demand; determining, based on the comparing step, a recommended ensemble; and displaying to a user, via a display element, the recommended ensemble and other possible ensembles as well as a visualization comparing the recommended ensemble and the other possible ensembles to business demand.

First claim

What is claimed is:

1. A method for allocating and configuring a network of data processing devices, the method comprising:
displaying to a user of a computer system, via a display element, a user interface that allows a user to characterize electronic data processing demand of the network;
receiving, from the user, via one or more input devices, input characterizing data processing demand;
comparing, utilizing one or more processors and one or more memory elements of a computer system, qualities of electronic data processing demand to attributes of ensembles comprising implementations of reusable patterns, the qualities of electronic data processing demand being categorical metrics and being based at least in part on the received input characterizing electronic data processing demand, wherein the comparing includes correlating a fit between the qualities associated with electronic data processing demand and the attributes associated with ensembles using one or more statistical inference techniques and calculating a value corresponding to a level of fit for each ensemble based on such correlation; wherein the reusable patterns contain application patterns; wherein an application pattern includes a functional pattern that define the application; wherein the patterns represent reusable code;
determining, utilizing one or more processors and one or more memory elements of the computer system, based on said comparing step, one or more recommended ensembles, the one or more recommended ensembles being determined based on their calculated level of fit values; wherein the ensembles are estimated by mapping an application to one or more electronic data processing activities; wherein performance indicators and electronic data processing demand characteristics predict an optimal quality profile of the demand characteristics; wherein the ensemble includes an application quality profile; wherein the application quality profile is synthesized from electronic data processing activity quality profiles for all of the electronic data processing activities the application has been mapped to in an associated application pattern;
automatically generating, based on said comparing and determining steps, utilizing one or more processors and one or more memory elements of a computer system, one or more visualizations comparing the recommended one or more ensemble to electronic data processing demand;
displaying to the user, via a display element, the one or more visualizations; and generating, for each visualization, a data processing configuration blueprint, the data processing configuration blueprint comprising information for use by one or more users in implementing an ensemble of servers, storage devices, and network communications accessories; wherein the blueprint comprises a reference system architecture and design pattern which define functionality and represent data processing requirements, wherein the blueprint represents a data processing configuration transformation of the network of data processing devices; wherein the blueprint further includes a portfolio of computer applications; wherein the blueprint further profiles workload distribution utilizing functional patterns;
allowing the user to select, via a user interface displayed via a display element, the recommended ensemble or one of the other possible ensembles and receiving, from a user, input selecting a first one of the recommended ensemble or the other possible ensembles; and
reconfiguring the network of data processing devices according to the selected ensemble and corresponding data processing configuration blueprint.

2. The method of claim 1 , wherein said step of determining, based on said comparing step, a recommended ensemble comprises determining based at least in part on statistical inference logic, a recommended ensemble.

3. The method of claim 1 , wherein said step of displaying to a user, via a display element, a user interface that allows the user to characterize electronic data processing demand of an organization comprises displaying to the user, via a display element, a user interface that allows the user to characterize key performance indicators of the organization.

4. The method of claim 1 , wherein the method further includes a step of deriving a quality profile based on the received input characterizing electronic data processing demand.

5. The method of claim 1 , wherein the reusable patterns comprise system of patterns whose behavior is specified by a quality profile.

6. The method of claim 5 , wherein the patterns include one or more design architecture patterns.

7. The method of claim 5 , wherein the patterns include one or more technology architecture patterns.

8. The method of claim 5 , wherein the patterns include one or more functional architecture patterns.

9. The method of claim 5 , wherein the patterns include one or more deployment architecture patterns.

10. The method of claim 5 , wherein the patterns include one or more information architecture patterns.

11. The method of claim 1 , wherein the attributes include qualities associated with resources.

12. The method of claim 11 , wherein the qualities associated with resources include qualities associated with processing resources.

13. The method of claim 11 , wherein the qualities associated with resources include qualities associated with memory resources.

14. The method of claim 11 , wherein the qualities associated with resources include qualities associated with network resources.

15. The method of claim 11 , wherein the qualities associated with resources include qualities associated with storage resources.

16. The method of claim 1 wherein the patterns comprise utilizing qualities, which represent categorical metrics, attributes, and/or constraints relating to the pattern.

17. A method for allocating and configuring a network of data processing devices, the method comprising:
displaying to a user of a computer system, via a display element, a user interface that allows the user to characterize electronic data processing demand of an organization;
receiving, from the user, via one or more input devices, input characterizing electronic data processing demand;
loading, in response to said step of receiving input characterizing electronic data processing demand, in one or more memory elements of the computer system, nonnumeric values for a plurality of categorical metrics associated with electronic data processing demand;
loading, from a data repository of the computer system, nonnumeric values for a plurality of categorical metrics associated with one or more architectural patterns;
automatically comparing, utilizing one or more processors and one or more memory elements of the computer system, the stored nonnumeric values for categorical metrics associated with electronic data processing demand to the loaded nonnumeric values for a plurality of categorical metrics associated with one or more architectural patterns by correlating a fit between the stored nonnumeric values for categorical metrics associated with electronic data processing demand and the loaded nonnumeric values for a plurality of categorical metrics associated with one or more architectural patterns using one or more statistical inference techniques and calculating a value corresponding to a level of fit for each of the architectural patterns based on such correlation; wherein the reusable patterns contain application patterns; wherein an application pattern includes a functional pattern that define the application; wherein the patterns represent reusable code;
automatically det

Assignees

• Narkier Sheppard David
• Bishop Anthony Bennett
• Renaud Paul Edward
• Pecoraro Alexis Salvatore
• Wanish Paul John
• Emc Ip Holding Co Llc

Inventors

• Narkier Sheppard David
• Bishop Anthony Bennett
• Renaud Paul Edward
• Pecoraro Alexis Salvatore
• Wanish Paul John

Classifications

• G06Q10/0631

  Resource planning, allocation, distributing or scheduling for enterprises or organisations · CPC title

• G06Q10/0637 Primary

  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 title