Use of execution flow shape to allow aggregate data reporting with full context in an application manager

• US 20070143743A1
• Filed: 12/15/2005
• Published: 06/21/2007
• Est. Priority Date: 12/15/2005
• Status: Active Grant

• Current Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Original Assignee: Wily Technology, Inc. (Broadcom, Inc.)
• Inventors: Puryear, Daryl, Vanrenen, Gabriel, Cobb, Jeffrey
• Granted Patent: US 8,341,605 B2
• Time in Patent Office: Days
• US Class Current: 717/127
• CPC Class Codes: G06F 11/3447 Performance evaluation by modeling
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/87 Monitoring of transactions
• CPC Class Codes: G06F 2201/88 Monitoring involving counting
• CPC Class Codes: H04L 65/75 Media network packet handling

Abstract

Data relating to execution flows at a computer system is aggregated across multiple execution flows by categorizing each execution flow into an execution flow shape. The execution flows may represent sequences of software components that are invoked or other computer system resources that are consumed. The execution flow shapes are developed by observing and recording the execution flows at the computer system and applying lossy compression rules. Execution flows are categorized into an execution flow shape which is a closest match. The execution flow data may be aggregated by an agent at the computer system, and communicated to a manager for subsequent use. The aggregation combines the information from all execution flows into a small enough data set that can be reported without consuming unduly large processing overhead while still preserving as many of the interesting aspects of the execution flows as possible.

Claims

1. A computer-implemented method for monitoring execution flows, comprising:

obtaining data from a plurality of respective execution flows at one or more computer systems; and

aggregating the data by categorizing each respective execution flow into a corresponding execution flow shape selected from a plurality of execution flow shapes.

2. The computer-implemented method of claim 1, wherein:

each of the execution flow shapes represents a respective sequence of software components; and

the categorizing comprises, for each respective execution flow, determining which respective sequence of software components represented by the execution flow shapes is closest to an observed sequence in which software components are invoked.

3. The computer-implemented method of claim 1, wherein:

each of the execution flow shapes represents a respective sequence in which resources are consumed; and

the categorizing comprises, for each respective execution flow, determining which respective sequence in which resources are consumed is closest to an observed sequence in which resources are consumed.

4. The computer-implemented method of claim 1, wherein:

the plurality of respective execution flows are associated with multiple computer systems;

the aggregating data comprises aggregating data associated with each of the multiple computer systems separately; and

the method further comprises communicating the aggregated data from the multiple computer systems to a central manager.

5. The computer-implemented method of claim 1, wherein:

the categorizing comprises categorizing different execution flows into a single execution flow shape.

6. The computer-implemented method of claim 1, wherein:

the categorizing comprises, for each respective execution flow, performing lossy compression to provide a respective compressed execution flow, and determining which execution flow shape is closest to the respective compressed execution flow.

7. The computer-implemented method of claim 1, further comprising:

providing data indicative of a quantity of the execution flows which were categorized into each of the execution flow shapes.

8. The computer-implemented method of claim 1, further comprising:

providing aggregated performance data associated with each of the execution flow shapes.

9. The computer-implemented method of claim 1, wherein:

at least one of the respective execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

10. The computer-implemented method of claim 1, wherein:

the aggregating is performed after the obtaining.

11. The computer-implemented method of claim 1, wherein:

the data from at least one of the respective execution flows is obtained and aggregated before data from all of the execution flows has been obtained.

12. A computer-implemented method for monitoring execution flows, comprising:

observing a plurality of execution flows at one or more computer systems; and

defining a plurality of execution flow shapes based on the observing.

13. The computer-implemented method of claim 12, further comprising:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the defined plurality of execution flow shapes.

14. The computer-implemented method of claim 13, wherein:

the categorizing comprises categorizing different execution flows into a single execution flow shape.

15. The computer-implemented method of claim 12, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

16. The computer-implemented method of claim 12, wherein:

the observing comprises observing respective sequences in which resources are consumed for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

17. The computer-implemented method of claim 12, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

18. The computer-implemented method of claim 12, wherein:

the defining comprises compressing data representing the execution flows using lossy compression to provide respective compressed execution flows.

19. A computer-implemented method for monitoring execution flows, comprising:

receiving aggregated data from one or more computer systems, the aggregated data representing respective execution flows which were categorized into a corresponding execution flow shape selected from a plurality of available execution flow shapes; and

storing the aggregated data for subsequent use.

20. The computer-implemented method of claim 19, wherein:

the received aggregated data includes performance data associated with each of the execution flow shapes.

21. The computer-implemented method of claim 19, wherein:

each of the available execution flow shapes represents a respective sequence of software components which are invoked.

22. The computer-implemented method of claim 19, wherein:

each of the available execution flow shapes represents a respective sequence in which resources are consumed.

23. The computer-implemented method of claim 19, wherein:

the respective execution flows are associated with multiple computer systems.

24. The computer-implemented method of claim 19, wherein:

the aggregated data represents multiple execution flows which were categorized into a single execution flow shape.

25. The computer-implemented method of claim 19, wherein:

the received aggregated data indicates a quantity of the execution flows which were categorized into each of the execution flow shapes.

26. The computer-implemented method of claim 19, wherein:

at least one of the respective execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

27. An apparatus for monitoring execution flows, comprising:

at least one storage device; and

at least one processor in communication with the at least one storage device, the at least one processor performing a method comprising;

observing a plurality of execution flows at one or more computer systems; and

defining a plurality of execution flow shapes based on the observing.

28. The apparatus of claim 27, wherein the method performed by the at least one processor further comprises:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the defined plurality of execution flow shapes.

29. The apparatus of claim 28, wherein:

the categorizing comprises categorizing different execution flows into a single execution flow shape.

30. The apparatus of claim 27, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

31. The apparatus of claim 27, wherein:

the observing comprises observing respective sequences in which resources are consumed for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

32. The apparatus of claim 27, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

33. The apparatus of claim 27, wherein:

the defining comprises compressing data representing the execution flows using lossy compression to provide respective compressed execution flows.

34. At least one processor readable storage device having processor readable code embodied thereon for programming at least one processor to perform a method for monitoring execution flows, the method comprising:

observing a plurality of execution flows at one or more computer systems; and

defining a plurality of execution flow shapes based on the observing.

35. The at least one processor readable storage device of claim 34, wherein the method performed by the at least one processor further comprises:

aggregating data from the plurality of execution flows by categorizing each of the execution flows into a corresponding execution flow shape selected from the defined plurality of execution flow shapes.

36. The at least one processor readable storage device of claim 35, wherein:

the categorizing comprises categorizing different execution flows into a single execution flow shape.

37. The at least one processor readable storage device of claim 34, wherein:

the observing comprises observing respective sequences of software components which are invoked for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

38. The at least one processor readable storage device of claim 34, wherein:

the observing comprises observing respective sequences in which resources are consumed for the respective execution flows; and

the defining comprises grouping analogous observed sequences.

39. The at least one processor readable storage device of claim 34, wherein:

at least one of the execution flows spans at least one of;

(a) one or more threads and (b) one or more processes.

40. The at least one processor readable storage device of claim 34, wherein:

the defining comprises compressing data representing the execution flows using lossy compression to provide respective compressed execution flows.