Event chain visualization of performance data
View Patent ↗An event chain visualization of performance data may show the execution of monitored elements as bars on a timeline, with connections or other relationships connecting the various bars into a sequential view of an application. The visualization may include color, shading, or other highlighting to show resource utilization or performance metrics. The visualization may be generated by monitoring many events processed by an application, where each bar on a timeline may reflect multiple instances of a monitored element and, in some case, the aggregated performance.
1. A method performed by at least one computer processor, said method comprising:
receiving trace data gathered from an application, said application comprising monitored elements, said trace data comprising performance observations from said monitored elements;
identifying a first monitored element and a second monitored element within said trace data, said first monitored element having a relationship with said second monitored element;
creating a first geometric shape representing a first monitored element, said first geometric shape having a first dimension;
determining a first value for said first dimension from an aggregation of a plurality of said performance observations, said first value representing a first observation of said plurality of said performance observations;
creating a second geometric shape representing a second monitored element, said second geometric shape having said first dimension;
determining a second value for said first dimension from an aggregation of a second plurality of said performance observations, said second value representing a second of said second plurality of said performance observations;
creating a graphical connector connecting said first geometric shape and said second geometric shape; and
rendering said first geometric shape, said second geometric shape, and said graphical connector.
2. The method of claim 1 further comprising:
determining a curve representing said first plurality of performance observations in said first dimension; and
rendering said curve within said first geometric shape.
3. The method of claim 2 , said curve being a line graph.
4. The method of claim 2 , said curve being variable shading within said first geometric shape.
5. The method of claim 1 , said first dimension representing time.
6. The method of claim 1 , said first dimension representing resource utilization.
7. The method of claim 6 , said resource utilization being one of a group composed of:
memory resource utilization;
processor resource utilization; and
network resource utilization.
8. The method of claim 1 , said first geometric shape being a rectangle.
9. The method of claim 8 , said first dimension being a horizontal length of said rectangle.
10. The method of claim 8 , said first dimension being a vertical length of said rectangle.
11. The method of claim 1 , said first observation being a maximum observation of said plurality of said performance observations.
12. The method of claim 1 , said first observation being one of a group composed of:
minimum observation;
average observation; and
median observation.
13. The method of claim 1 , said relationship being a sequential relationship between said first monitored element and said second monitored element.
14. The method of claim 1 , said relationship being a dependency relationship between said first monitored element and said second monitored element.
15. The method of claim 1 , said relationship being a shared memory object relationship between said first monitored element and said second monitored element.
16. A system comprising:
a processor;
a rendering engine executing on said processor, said rendering engine that:
receives trace data gathered from an application, said application comprising monitored elements, said trace data comprising performance observations from said monitored elements;
identifies a first monitored element and a second monitored element within said trace data, said first monitored element having a relationship with said second monitored element;
creates a first geometric shape representing a first monitored element, said first geometric shape having a first dimension;
determines a first value for said first dimension from an aggregation of a plurality of said performance observations, said first value representing a first observation of said plurality of said performance observations;
creates a second geometric shape representing a second monitored element, said second geometric shape having said first dimension;
determines a second value for said first dimension from an aggregation of a second plurality of said performance observations, said second value representing a second of said second plurality of said performance observations;
creates a graphical connector connecting said first geometric shape and said second geometric shape; and
renders said first geometric shape, said second geometric shape, and said graphical connector.
17. The system of claim 16 , said rendering engine that further:
determines a curve representing said first plurality of performance observations in said first dimension; and
displays said curve within said first geometric shape.
18. The system of claim 17 , said curve being a line graph.
19. The system of claim 17 , said curve being variable shading within said first geometric shape.
20. The system of claim 16 , said first dimension representing time.
21. The system of claim 16 , said first dimension representing resource utilization.
22. The system of claim 21 , said resource utilization being one of a group composed of:
memory resource utilization;
processor resource utilization; and
network resource utilization.
23. The system of claim 16 , said first geometric shape being a rectangle.
24. The system of claim 23 , said first dimension being a horizontal length of said rectangle.
25. The system of claim 23 , said first dimension being a vertical length of said rectangle.
26. The system of claim 16 , said first observation being a maximum observation of said plurality of said performance observations.
27. The system of claim 16 , said first observation being one of a group composed of:
minimum observation;
average observation; and
median observation.
28. The system of claim 16 , said relationship being a sequential relationship between said first monitored element and said second monitored element.
29. The system of claim 16 , said relationship being a dependency relationship between said first monitored element and said second monitored element.
30. The system of claim 16 , said relationship being a shared memory object relationship between said first monitored element and said second monitored element.