Method and apparatus for automatically discovering of application errors as a predictive metric for the functional health of enterprise applications

• US 20060026467A1
• Filed: 07/29/2005
• Published: 02/02/2006
• Est. Priority Date: 07/30/2004
• Status: Abandoned Application

• Current Assignee: Certagon Ltd.
• Original Assignee: Certagon Ltd.
• Inventors: Cohen, Yoav, Barzilai, David, Nehab, Smadar, Entin, Gadi
• Application Number:
  US11/192,662
• Publication Number:
  US 20060026467A1
• Time in Patent Office: Days
• US Class Current: 714/38
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring

Abstract

A method and apparatus that uses application errors as a predictive metric for overall measuring of applications functional health are disclosed. The automated system intercepts messages exchanged between inter-services of enterprise applications, analyzes the context of those messages, and automatically derives application errors embedded in the message. Thereafter, it is capable of showing deviations from expected behavior for the purposes of predicting failures of the monitored application. Furthermore, the invention displays the user'"'"'s real-time actionable data generated using the application errors.

Claims

1. An automated apparatus for discovering and using application errors as a metric for overall measuring of enterprise applications health comprising:

a plurality of data collectors for capturing cross-application messages;

a context analyzer for deriving application errors from said messages; and

a baseline analyzer for predicting failures in a monitored enterprise application.

2. The apparatus of claim 1, further comprising:

a graphical user interface (GUI) for displaying graphical views related to said application errors.

3. The apparatus of claim 1, further comprising:

a transaction correlator for correlating independent cross-application messages into a transaction instance.

4. The apparatus of claim 3, said context analyzer measuring a plurality of measured values for each of a plurality of types of error.

5. The apparatus of claim 4, wherein each of said plurality of measured values comprises any of:

an error rate, a throughput, a response time, a monetary value, and application availability.

6. The apparatus of claim 4, said context analyzer comprising:

means for deriving said application errors by applying a set of extraction expressions to said cross-application messages.

7. The apparatus of claim 1, said baseline analyzer generating a plurality of norms, wherein each of said plurality of norms determines behavior of a respective error type.

8. The apparatus of claim 7, said baseline analyzer performing failure prediction, wherein said failure prediction is performed by comparing an error rate of a respective error type to said norm.

9. The apparatus system of claim 1, said baseline analyzer further comprising:

a verification engine.

10. The apparatus of claim 9, said verification engine generating alerts if said error rate triggers a predefined rule.

11. The apparatus of claim 1, wherein locations of error fields in said cross-application messages are user designated.

12. The apparatus of claim 11, wherein said designation of error fields is performed as said cross-application messages are captured by said plurality of data collectors.

13. The apparatus of claim 1, wherein said enterprise application comprises a composite application.

14. The apparatus of claim 13, said cross application messages comprising:

messages in a format compliant with and of the following protocols;

a simple object access protocol (SOAP), a hypertext transfer protocol (HTTP), an extensible a markup language (XML), a Microsoft message queuing (MSMQ), a Java message service (JMS), and an IBM Web-Sphere MQ.

29. The method of claim 1, further comprising the step of:

using said application errors as a predictive metric for application failures.

15. A computer implemented method for automatically discovering and using application errors as a metric for overall measuring of enterprise applications health and their functional health, comprising the steps of:

capturing cross-application messages for a monitored enterprise application;

analyzing context of said cross-application messages to derive application errors;

measuring a plurality of values for each of a plurality of types of application errors;

comparing said measured values for a respective error type to a norm; and

generating an action based on the comparison results.

16. The method of claim 15, further comprising the step of:

correlating said cross-application messages into a transaction instance.

17. The method of claim 16, said cross application messages comprising:

messages in a format compliant with at least one of the following protocols;

a simple object access protocol (SOAP), a hypertext transfer protocol (HTTP), an extensible markup language (XML), a Microsoft message queuing (MSMQ), a Java message service (JMS), and an IBM Web-Sphere MQ.

18. The method of claim 15, each of said plurality of measured values comprising of:

an error rate, a throughput, a response time, a monetary value, application and availability.

19. The method of claim 15, said analyzing step further comprising the step of:

applying a set of extraction expressions to said cross-application messages.

20. The method of claim 15, wherein said norm determines behavior of a respective error type.

21. The method of claim 20, said comparing step further comprising the step of:

comparing said measured values to a predefined set of rules.

22. The method of claim 21, said generating step further comprising the step of:

generating alerts if at least one of said predefined set of rules is triggered.

23. The method of claim 20, wherein locations of error fields in said cross-application messages are user designated.

24. The method of claim 23, wherein said designation of error fields is performed as said cross-application messages are captured.

25. The method of claim 15, wherein said enterprise application comprises a composite application.

26. The method of claim 15, wherein actionable data are displayed to a user through at least one graphical user interface (GUI) view.

27. The method of claim 25, further comprising the step of:

automatically discovering application errors using a plurality of performance indicators.

28. The method of claim 27, said discovering step comprising the steps of:

receiving said performance indicators; and

identifying application errors in said performance indicators.

30. A computer software product readable by a machine, tangibly embodying a program of instructions executable by the machine to implement a process for automatically discovering and using application errors as a predictive metric for overall monitoring of enterprise applications and their functional health, the process comprising the steps of:

capturing cross-application messages for a monitored enterprise application;

analyzing context of said cross-application messages derive application errors;

measuring a plurality of values for each for a plurality of types of application errors;

comparing said measured values for a respective error type to a norm; and

generating an action data based on said comparison results.

31. The computer software product of claim 30, said process further comprising the step of:

correlating said cross-application messages into a transaction instance.

32. The computer software product of claim 31, said cross application messages comprising:

messages in a format compliant with at least one of the following protocols;

a simple object access protocol (SOAP), a hypertext transfer protocol (HTTP), an extensible markup language (XML), a Microsoft message queuing (MSMQ), a Java message service (JMS), an IBM Web-Sphere MQ.

33. The computer software product of claim 30, each of said plurality of measured values comprising any of:

an error rate, a throughput, a response time, a monetary value, and application availability.

34. The computer software product of claim 30, said analyzing step further comprising the step of:

applying a set of extraction expressions to said cross-application messages.

35. The computer software product of claim 30, wherein said norm determines behavior of a respective error type.

36. The computer software product of claim 30, said comparing step further comprising the step of:

comparing said measured values to a predefined set of rules.

37. The computer software product of claim 36, said generating step further comprising the step of:

generating alerts if at least one of said predefined set of rules is triggered.

38. The computer software product of claim 35, wherein locations of error fields in said cross-application messages are user designated.

39. The computer software product of claim 38, wherein designation of error fields is performed as said cross-application messages are captured.

40. The computer software product of claim 30, wherein said enterprise application comprises a composite application.

41. The computer software product of claim 30, wherein actionable data are displayed to a user through at least one graphical user interface (GUI) view.

42. The computer software product of claim 30, said method further comprising the step of:

automatically discovering application errors using a plurality of performance indicators.

43. The computer software product of claim 42, said discovering step comprising the steps of:

receiving said performance indicators; and

identifying said application errors in said performance indicators.

44. The computer software product of claim 30, said step for discovering application errors is executed by a network appliance.

45. The computer software product of claim 44, wherein said network appliance comprises any of:

a bridge, a router, a hub, and a gateway.

46. The computer software product of claim 30, further comprising the step of:

performing application messages routing and provisioning.