Differentiated service identification in a networked computing environment

• US 9,213,582 B2
• Filed: 04/26/2012
• Issued: 12/15/2015
• Est. Priority Date: 04/26/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Narendra, Nanjangud C., Ponnalagu, Karthikeyan, Sivakumar, Gandhi
• Primary Examiner(s): Barry, Lance Leonard
• Assistant Examiner(s): Emdadi, Keyvan
• Application Number:
  US13/456,519
• Publication Number:
  US 20130290500A1
• Time in Patent Office: 1,328 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 9/5072 Grid computing
• CPC Class Codes: H04L 41/052 using standardised network management architectures, e.g. telecommunication management network [TMN] or unified network management architecture [UNMA]
• CPC Class Codes: H04L 67/51 Discovery or management thereof, e.g. service location protocol [SLP] or web services

Abstract

Embodiments of the present invention provide an approach for differentiated service identification/exposure in a networked computing environment (e.g., a cloud computing environment). In a typical embodiment, input model criteria will be generated. Such criteria may (among other things): identify service categories based on contextual bindings and domain centric functions; identify inter-service dependencies for a given business model (BPM); and/or provide dynamic validation of services to be exposed/identified. Embodiments of the present invention may further analyze service exposure criteria to provide efficient and accurate service exposure decisions as well as validation of the service exposure. This approach allows for consistent service exposure determinations based on decision histories of similarly (2-dimensional) aligned services in the past. This approach further allows for a validation assessment that is based on actual metrics of service usage verses an estimated usage at the time of service implementation.

Claims

1. A computer-implemented method for differentiated service identification in a networked computing environment, comprising:

identifying an architecture type with which to classify each of a set of candidate services, each of the set of candidate services being a cloud service of a cloud computing environment that requires qualification as a service;

identifying a service type with which to classify each of the set of candidate services;

determining a set of categories with which to categorize the set of candidate services;

categorizing each of the set of candidate services in the set of categories based on the service type using a configurable criteria list formed from inputs of previously categorized services;

defining a set of exposure criteria with which to classify the set of categories;

analyzing the set of exposure criteria based on a set of re-defined rules and at least one of;

historical data for service exposure decisions for previously categorized services or operational data of the previously categorized services;

generating a dynamic service litmus test (SLT) that is specific to the service based on the analysis of the exposure criteria; and

applying the dynamic SLT to the set of candidate services.

2. The computer-implemented method of claim 1, further comprising validating the set of candidate services based on the applying.

3. The computer-implemented method of claim 2, further comprising determining a layer of an architectural stack for hosting each of the set of candidate services, and generating a view of the architectural stack that represents the candidate services for each of the exposure criteria.

4. The computer-implemented method of claim 1, the architectural type comprising a model selected from a group consisting of:

a business model, a business process model, a logical data model, and a goal model.

5. The computer-implemented method of claim 1, further comprising determining dependencies between each of the set of candidate services.

6. The computer-implemented method of claim 1, the categorizing being further based on the architecture type.

7. The computer-implemented method of claim 1, the analyzing comprising unitizing historical data to identify a set of past services similar to the set of candidate services.

8. The computer-implemented method of claim 1, the networked computing environment comprising a cloud computing environment.

9. A system for differentiated service identification in a networked computing environment, comprising:

a memory medium comprising instructions;

a bus coupled to the memory medium; and

a processor coupled to the bus that when executing the instructions causes the system to;

identify an architecture type with which to classify each of a set of candidate services, each of the set of candidate services being a cloud service of a cloud computing environment that requires qualification as a service;

identify a service type with which to classify each of the set of candidate services;

determine a set of categories with which to categorize the set of candidate services;

categorize each of the set of candidate services in the set of categories based on the service type using a configurable criteria list formed from inputs of previously categorized services;

define a set of exposure criteria with which to classify the set of categories;

analyze the set of exposure criteria based on a set of re-defined rules and at least one of;

historical data for service exposure decisions for previously categorized services or operational data of the previously categorized services;

generate a dynamic service litmus test (SLT) that is specific to the service based on the analysis of the exposure criteria; and

apply the dynamic SLT to the set of candidate services.

10. The system of claim 9, the memory medium further comprising instructions for causing the system to:

validate the set of candidate services based on the applying;

determine a layer of an architectural stack for hosting each of the set of candidate services; and

generate a view of the architectural stack that represents the candidate services for each of the exposure criteria.

11. The system of claim 9, the architectural type comprising a model selected from a group consisting of:

a business model, a business process model, a logical data model, and a goal model.

12. The system of claim 9, the memory medium further comprising instructions for causing the system to determine dependencies between each of the set of candidate services.

13. The system of claim 9, the memory medium further comprising instructions for causing the system to utilize historical data to identify a set of past services similar to the set of candidate services.

14. The system of claim 9, the networked computing environment comprising a cloud computing environment.

15. A computer program product for differentiated service identification in a networked computing environment, the computer program product comprising a computer readable storage device, and program instructions stored on the computer readable storage device, to:

identify an architecture type with which to classify each of a set of candidate services, each of the set of candidate services being a cloud service of a cloud computing environment that requires qualification as a service;

identify a service type with which to classify each of the set of candidate services;

determine a set of categories with which to classify the set of candidate services;

categorize each of the set of candidate services in the set of categories based on the service type using a configurable criteria list formed from inputs of previously categorized services;

define a set of exposure criteria with which to classify the set of categories;

analyze the set of exposure criteria based on a set of re-defined rules and at least one of;

historical data for service exposure decisions for previously categorized services or operational data of the previously categorized services;

generate a dynamic service litmus test (SLT) that is specific to the service based on the analysis of the exposure criteria; and

apply the dynamic SLT to the set of candidate services.

16. The computer program product of claim 15, the computer readable storage device further comprising instructions to:

validate the set of candidate services based on the applying;

determine a layer of an architectural stack for hosting each of the set of candidate services; and

generate a view of the architectural stack that represents the candidate services for each of the exposure criteria.

17. The computer program product of claim 15, the architectural type comprising a model selected from a group consisting of:

a business model, a business process model, a logical data model, and a goal model.

18. The computer program product of claim 15, the computer readable storage device further comprising instructions to determine dependencies between each of the set of candidate services.

19. The computer program product of claim 15, the computer readable storage device further comprising instructions to utilize historical data to identify a set of past services similar to the set of candidate services.

20. A method for deploying a system for differentiated service identification in a networked computing environment, comprising:

providing a computer infrastructure being operable to;

identify an architecture type with which to classify each of a set of candidate services, each of the set of candidate services being a cloud service of a cloud computing environment that requires qualification as a service;

identify a service type with which to classify each of the set of candidate services;

determine a set of categories with which to classify the set of candidate services;

categorize each of the set of candidate services in the set of categories based on the service type using a configurable criteria list formed from inputs of previously categorized services;

define a set of exposure criteria with which to classify the set of categories;

analyze the set of exposure criteria based on a set of re-defined rules and at least one of;

historical data for service exposure decisions for previously categorized services or operational data of the previously categorized services;

generate a dynamic service litmus test (SLT) that is specific to the service based on the analysis of the exposure criteria; and

apply the dynamic SLT to the set of candidate services.