DYNAMIC APPLICATION LANDSCAPE PROCESSING SYSTEM

• US 20180232463A1
• Filed: 02/16/2017
• Published: 08/16/2018
• Est. Priority Date: 02/16/2017
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chakraborty, Amitava, Dasgupta, Diptiman, Rakshit, Sarbajit K., Sengupta, Sandipan, Sinha, Shantanu
• Application Number:
  US15/434,555
• Publication Number:
  US 20180232463A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/9038 Presentation of query results
• CPC Class Codes: G06F 16/907 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

A system, method and program product for application landscape processing. A system is disclosed that includes: a contextual analysis engine that analyzes structured and unstructured data from external source information, internal source information, and application usage patterns to identify performance indicators; a system for storing metadata for each application in an application landscape, wherein metadata for each application specifies a set of application parameters and associated values; and a priority calculator that calculates a priority score for applications in the application landscape, wherein the priority score for a selected application is determined by evaluating performance indicators that correlate to metadata of the selected application.

Claims

1. An application landscape processing system, comprising:

a contextual analysis engine that analyzes structured and unstructured data from external source information, internal source information, and application usage patterns to identify performance indicators;

a system for storing metadata for each application in an application landscape, wherein metadata for each application specifies a set of application parameters and associated values; and

a priority calculator that calculates a priority score for applications in the application landscape, wherein the priority score for a selected application is determined by evaluating performance indicators that correlate to the metadata of the selected application.

2. The application landscape processing system of claim 1, wherein the contextual analysis engine utilizes at least one of natural language processing and machine learning to identify performance indicators from the unstructured data.

3. The application landscape processing system of claim 2, wherein the contextual analysis engine further utilizes statistical analysis of the application usage patterns to quantify performance indicators.

4. The application landscape processing system of claim 1, wherein the application parameters are selected from at least one of:

domain, business area, business problem being solved, or relevant key performance indicators.

5. The application landscape processing system of claim 1, further comprising:

a system for calculating a scalability score for each application based on inputted feeds that are selected from at least one of;

system resource utilization, type of data center, an external capacity model or future business growth; and

a visualization interface that displays an interactive application landscape diagram that visually conveys a degree of scalability of each application based on the scalability score, wherein the degree of scalability includes visual information showing an amount each application can be stretched.

6. The application landscape processing system of claim 1, further comprising a visualization interface for displaying an application landscape diagram that conveys at least one of application priority and application scalability.

7. The application landscape processing system of claim 1, wherein the external source information includes content having at least one of:

a media report, a social media feed, a government publication or a published report.

8. A computer program product stored on a computer readable storage medium, which when executed by a computing system, processes an application landscape, the program product comprising:

program code that contextually analyzes structured and unstructured data from external source information, internal source information, and application usage patterns to identify performance indicators;

program code for storing metadata for each application in the application landscape, wherein metadata for each application specifies a set of application parameters and assigned values; and

program code that calculates a priority score for applications in the application landscape, wherein the priority score for a selected application is determined by evaluating performance indicators that correlate to the metadata of the selected application.

9. The program product of claim 8, wherein the contextual analysis utilizes at least one of natural language processing and machine learning to identify performance indicators from the unstructured data.

10. The program product of claim 9, wherein the contextual analysis further utilizes statistical analysis of the application usage patterns to identify performance indicators.

11. The program product of claim 8, wherein the application parameters include at least one of:

domain, business area, business problem being solved or relevant key performance indicators.

12. The program product of claim 8, further comprising program code for calculating a scalability score for each application based on inputted feeds that are selected from at least one of:

system resource utilization, type of data center, an external capacity model, or future business growth.

13. The program product of claim 8, further comprising program code for displaying an application landscape diagram that conveys at least one of application priority and application scalability.

14. The program product of claim 8, wherein the external source information includes content having at least one of:

a media report, a social media feed, a government publication or a published report.

15. A computerized method for processing an application landscape, comprising:

contextually analyzing structured and unstructured data from external source information, internal source information, and application usage patterns to identify performance indicators;

storing metadata for each application in the application landscape, wherein metadata for each application specifies a set of application parameters and assigned values; and

calculating a priority score for applications in the application landscape, wherein the priority score for a selected application is determined by evaluating performance indicators that correlate to the metadata of the selected application.

16. The computerized method of claim 15, wherein the contextual analysis utilizes at least one of natural language processing and machine learning to identify performance indicators from the unstructured data.

17. The computerized method of claim 16, wherein the contextual analysis further utilizes statistical analysis of the application usage patterns to identify performance indicators.

18. The computerized method of claim 15, wherein the application parameters are selected from at least one of:

domain, business area, business problem being solved or relevant key performance indicators.

19. The computerized method of claim 15, further comprising calculating a scalability score for each application based on inputted feeds that are selected from at least one of:

system resource utilization, type of data center, an external capacity model or future business growth.

20. The computerized method of claim 15, further comprising displaying an application landscape diagram that conveys at least one of application priority and application scalability.