Method and system to monitor a diverse heterogeneous application environment

• US 20050262136A1
• Filed: 02/14/2005
• Published: 11/24/2005
• Est. Priority Date: 02/27/2004
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Lloyd, James, Eynon, Michael, Kumar, Abhinav, Hall, Faye Dai
• Granted Patent: US 7,526,670 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 11/3447 Performance evaluation by modeling
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/87 Monitoring of transactions

Abstract

A method to detect potential problems within a heterogeneous and diverse application environment. Operations data is received from a plurality of application servers within the application environment. The operations data pertains to operations performed at the plurality of application servers over a predetermined time interval. The operations data is aggregated. The aggregated data is compared to reference data, and a potential problem within the application environment is detected if the aggregated data deviates from the reference data in a predetermined manner.

Claims

1. A method to detect potential problems within a heterogeneous and diverse application environment, the method including:

receiving operations data from a plurality of application servers within the application environment, the operations data pertaining to operations performed at the plurality of application servers;

aggregating the operations data pertaining to the operations performed at the plurality of application servers over a predetermined time interval;

comparing the aggregated operations data to reference operations data; and

detecting a potential problem within the application environment if the aggregated operations data deviates from the reference operations data in a predetermined manner.

2. The method of claim 1, wherein the received operations data conforms to a common syntax.

3. The method of claim 2, wherein the common syntax defines at least one dimension variable and one analysis variable.

4. The method of claim 3, wherein the at least one dimension variable is a transaction type variable identifying an associated transaction as being one of a predetermined set of transaction types.

5. The method of claim 3, wherein the at least one dimension variable is a message class variable identifying a message class, of a predetermined set of a message classes, to which a message embodying at least a portion of operations data of a message belongs.

6. The method of claim 1, wherein the aggregation of the operations data includes generating a multidimensional data structure into which the operations data, pertaining to the transactions performed at the plurality of application servers over the predetermined time interval, is aggregated.

7. The method of claim 6, wherein the multidimensional data structure is a multidimensional OLAP data structure.

8. The method of claim 1, including generating the reference operations data based on historical operations data pertaining to the application environment.

9. The method of claim 8, wherein the generating of the reference operations data includes selecting the historical operations data based on the predetermined time interval.

10. The method of claim 9, wherein the historical operations data is selected as pertaining to a past time interval corresponding to the predetermined time interval.

11. The method of claim 10, wherein the past time interval corresponds to the predetermined time interval on at least one of a previous day, week and month.

12. The method of claim 10, wherein the past time interval corresponds to the predetermined time interval according to the time of day.

13. The method of claim 1, wherein the comparing of the aggregated operations data to the reference operations data includes performing comparisons on multiple dimensions common to the aggregated operations data and the reference operations data.

14. The method of claim 13, wherein the performance of the comparisons on the multiple dimensions includes generating a dimensional hierarchy common to the aggregated transactional data and the reference operations data, and performing comparisons at a plurality of levels of the dimensional hierarchy.

15. The method of claim 1, wherein the detecting of the potential problem includes generating at least one threshold based on the reference operations data, and determining whether the aggregated operations data transgresses the at least one threshold.

16. The method of claim 1, wherein the detecting of the potential problem includes generating a range, based on the reference operations data, for at least one analysis variable of the aggregate operations data, and determining whether the at least one variable of the aggregate operations data falls outside of the range.

17. The method of claim 1, including generating an alert including information pertaining to the potential problem if the potential problem is detected.

18. The method of claim 1, including automatically initiating an action to correct the potential problem, responsive to the detection thereof.

19. The method of claim 1, wherein the operations data is at least one of transaction, event and heartbeat data.

20. A machine-readable medium storing a sequence of instructions that, when executed by a machine, cause the machine to perform the method of claim 1.

21. A system to detect potential problems within a heterogeneous and diverse application environment, the system including:

a summary module configured to receive operations data from a plurality of application servers within the application environment, the operations data pertaining to operations performed at the plurality of application servers, and to aggregate the operations data pertaining to the operations performed at the plurality of application servers over a predetermined time interval; and

a comparison module configured to compare the aggregated operations data to reference operations data, and to detect a potential problem within the application environment if the aggregated operations data deviates from the reference operations data in a predetermined manner.

22. The system of claim 21, wherein the received operations data conforms to a common syntax.

23. The system of claim 22, wherein the common syntax defines at least one dimension variable and one analysis variable.

24. The system of claim 23, wherein the at least one dimension variable is a transaction type variable identifying an associated transaction as being one of a predetermined set of transaction types.

25. The system of claim 23, wherein the at least one dimension variable is a message class variable identifying a message class, of a predetermined set of a message classes, to which a message embodying at least a portion of operations data of a message belongs.

26. The system of claim 21, wherein the summary module is configured to generate a multidimensional data structure into which the operations data, pertaining to the transactions performed at the plurality of application servers over the predetermined time interval, is aggregated.

27. The system of claim 26, wherein the multidimensional data structure is a multidimensional OLAP data structure.

28. The system of claim 21, wherein the comparison module is configured to generate the reference operations data based on historical operations data pertaining to the application environment.

29. The system of claim 28, wherein the comparison module is configured to generate the reference operations data by selecting the historical operations data based on the predetermined time interval.

30. The system of claim 29, wherein the historical operations data is selected as pertaining to a past time interval corresponding to the predetermined time interval.

31. The system of claim 30, wherein the past time interval corresponds to the predetermined time interval on at least one of a previous day, week and month.

32. The system of claim 30, wherein the past time interval corresponds to the predetermined time interval according to the time of day.

33. The system of claim 21, wherein the comparison module is configured to compare the aggregated operations data to the reference operations data by performing comparisons on multiple dimensions common to the aggregated operations data and the reference operations data.

34. The system of claim 33, wherein the comparison module is configured to generate a dimensional hierarchy common to the aggregated operational data and the reference operations data, and to perform comparisons at a plurality of levels of the dimensional hierarchy.

35. The system of claim 21, wherein the comparison module is configured to generate at least one threshold based on the reference operations data, and to determine whether the aggregated operations data transgresses the at least one threshold.

36. The system of claim 21, wherein the comparison module is configured to generate a range, based on the reference operations data, for at least one analysis variable of the aggregate operations data, and to determine whether the at least one variable of the aggregate operations data falls outside of the range.

37. The system of claim 21, wherein the comparison module is configured to generate an alert including information pertaining to the potential problem if the potential problem is detected.

38. The system of claim 21, wherein the comparison module is configured automatically to initiate an action to correct the potential problem, responsive to the detection thereof.

39. A system to detect potential problems within a heterogeneous and diverse application environment, the system including:

summary means for receiving operations data from a plurality of application servers within the application environment, the operations data pertaining to operations performed at the plurality of application servers, and for aggregating the operations data pertaining to the operations performed at the plurality of application servers over a predetermined time interval; and

comparison means for comparing the aggregated operations data to reference operations data, and to detect a potential problem within the application environment if the aggregated operations data deviates from the reference operations data in a predetermined manner.