Root cause analysis of performance problems

• US 10,552,390 B2
• Filed: 01/06/2017
• Issued: 02/04/2020
• Est. Priority Date: 01/06/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Anand, Manish, Khan, Pathan Niyazulla, Singh, Sweta
• Primary Examiner(s): Lau, Tung S
• Application Number:
  US15/400,048
• Publication Number:
  US 20180196835A1
• Time in Patent Office: 1,124 Days
• Field of Search: None
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 2201/80 Database-specific techniques

Abstract

A method, computer program product, and system for analyzing performance of a computer system where at a plurality of time intervals, a set of KPIs of a database and database performance outputs are monitored. A database performance value is calculated based on the monitored KPIs and one or more database performance outputs. In response to determining the database performance value is below a first threshold, a KPI correlation coefficient is calculated. The calculated KPI correlation coefficient with the greatest value is selected as a target KPI. In response to determining that a count of functions of the target KPI meets a second threshold, a dynamic tabular representation of the determined target KPI is generated. A correlation matrix is generated based on the generated tabular representation and the plurality of time intervals and a first set of target functions are identified based on the generated correlation matrix.

Claims

1. A method for identifying a computer performance bottleneck, wherein the computer performance bottleneck is a root cause and performance degradation during a root cause analysis (RCA) by analyzing performance of a computer system based on key performance indicators (KPIs), the method comprising:

at a plurality of time intervals, monitoring a set of KPIs of a database and database performance outputs, wherein a KPI is associated with execution of one or more functions;

calculating a database performance value based on the monitored KPIs and one or more database performance outputs;

in response to determining the database performance value is below a first threshold, calculating a KPI correlation coefficient representing a correlation between the set of KPIs and corresponding database performance values;

selecting the calculated KPI correlation coefficient with the greatest value as a target KPI;

in response to determining that a count of functions of the target KPI meets a second threshold, generating a dynamic tabular representation of the determined target KPI, wherein the columns represent KPIs and the rows represent functions;

generating a correlation matrix based on the generated tabular representation and the plurality of time intervals; and

identifying a first set of target functions, associated with the correlation coefficient with the greatest value, based on the generated correlation matrix; and

identifying the computer performance bottleneck based on the tabular representation of the target KPI.

2. The method of claim 1, wherein determining a database performance value includes determining a database performance correlation for one or more KPIs in the set of KPIs based on a difference between the performance of the one or more KPIs in the set of KPIs and a statistical model.

3. The method of claim 1, further comprising, in response to determining a count of functions meets a third threshold, filtering a top count of functions based on the generating a dynamic tabular representation of the determined target KPI.

4. The method of claim 1, wherein generating a correlation matrix further comprises:

mapping the one or more functions of the target KPI and a corresponding time interval in which the one or more functions were executed; and

calculating a Pearson product-moment correlation coefficient for the one or more mapped functions.

5. The method of claim 4, wherein identifying a first set of target functions further comprises:

determining one or more target functions based on one or more mapped functions with associated Pearson product-moment correlation coefficients of the highest value.

6. The method of claim 5, further comprising:

calculating a time spent value for the one or more functions of the target KPI;

calculating a correlation weight value for the one or more functions, wherein the correlation weight value is based on the time spent value and the monitored time interval; and

determining a second set of one or more target function based on the calculated correlation weight and the generated correlation matrix.

7. The method of claim 1, wherein the database performance outputs are based on one or more of network bandwidth use, computer processor resource use, memory resource use, and disk use.

8. The method of claim 1, wherein the generated correlation matrix is generated via JOIN function.

9. The method of claim 1, further comprising:

generating a graphical representation of the first set of target functions and the target KPI.

10. The method of claim 1, wherein the generated tabular representation contains columns and rows, wherein the columns contain labels based on the target KPI and the rows contain labels based on the one or more functions of the target KPI.

11. A computer program product for identifying a computer performance bottleneck, wherein the computer performance bottleneck is a root cause and performance degradation during a root cause analysis (RCA) by analyzing performance of a computer system based on key performance indicators (KPIs), the computer program product comprising:

one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising;

at a plurality of time intervals, instructions to monitor a set of KPIs of a database and database performance outputs, wherein a KPI is associated with execution of one or more functions;

instructions to calculate a database performance value based on the monitored KPIs and one or more database performance outputs;

in response to instructions to determine the database performance value is below a first threshold, instructions to calculate a KPI correlation coefficient representing a correlation between the set of KPIs and corresponding database performance values;

instructions to select the calculated KPI correlation coefficient with the greatest value as a target KPI;

in response to instructions to determine that a count of functions of the target KPI meets a second threshold, instructions to generate a dynamic tabular representation of the determined target KPI, wherein the columns represent KPIs and the rows represent functions;

instructions to generate a correlation matrix based on the generated tabular representation and the plurality of time intervals; and

instructions to identify a first set of target functions, associated with the correlation coefficient with the greatest value, based on the generated correlation matrix; and

instructions to identify the computer performance bottleneck based on the tabular representation of the target KPI.

12. The computer program product of claim 11, wherein instructions to determine a database performance value includes instructions to determine a database performance correlation for one or more KPIs in the set of KPIs based on a difference between the performance of the one or more KPIs in the set of KPIs and a statistical model.

13. The computer program product of claim 11, further comprising, in response to instructions to determine a count of functions meets a third threshold, instructions to filter a top count of functions based on the instructions to generate a dynamic tabular representation of the determined target KPI.

14. The computer program product of claim 11, wherein instructions to generate a correlation matrix further comprises:

instructions to map the one or more functions of the target KPI and a corresponding time interval in which the one or more functions were executed; and

instructions to calculate a Pearson product-moment correlation coefficient for the one or more mapped functions.

15. The computer program product of claim 14, wherein instructions to identify a first set of target functions further comprises:

instructions to determine one or more target functions based on one or more mapped functions with associated Pearson product-moment correlation coefficients of the highest value.

16. The computer program product of claim 15, further comprising:

instructions to calculate a time spent value for the one or more functions of the target KPI;

instructions to calculate a correlation weight value for the one or more functions, wherein the correlation weight value is based on the time spent value and the monitored time interval; and

instructions to determine a second set of one or more target function based on the calculated correlation weight and the generated correlation matrix.

17. The computer program product of claim 11, wherein the database performance outputs are based on one or more of network bandwidth use, computer processor resource use, memory resource use, and disk use.

18. The computer program product of claim 11, wherein the generated correlation matrix is generated via JOIN function.

19. The computer program product of claim 11, further comprising:

instructions to generate a graphical representation of the first set of target functions and the target KPI.

20. A computer system for identifying a computer performance bottleneck, wherein the computer performance bottleneck is a root cause and performance degradation during a root cause analysis (RCA) by analyzing performance of a computer system based on key performance indicators (KPIs), the computer system comprising:

one or more computer processors;

one or more computer-readable storage media;

program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising;

at a plurality of time intervals, instructions to monitor a set of KPIs of a database and database performance outputs, wherein a KPI is associated with execution of one or more functions;

instructions to calculate a database performance value based on the monitored KPIs and one or more database performance outputs;

in response to instructions to determine the database performance value is below a first threshold, instructions to calculate a KPI correlation coefficient representing a correlation between the set of KPIs and corresponding database performance values;

instructions to select the calculated KPI correlation coefficient with the greatest value as a target KPI;

in response to instructions to determine that a count of functions of the target KPI meets a second threshold, instructions to generate a dynamic tabular representation of the determined target KPI, wherein the columns represent KPIs and the rows represent functions;

instructions to generate a correlation matrix based on the generated tabular representation and the plurality of time intervals; and

instructions to identify a first set of target functions, associated with the correlation coefficient with the greatest value, based on the generated correlation matrix; and

instructions to identify the computer performance bottleneck based on the tabular representation of the target KPI.