Multidimensional repositories for problem discovery and capacity planning of database applications

• US 6,804,714 B1
• Filed: 04/14/2000
• Issued: 10/12/2004
• Est. Priority Date: 04/16/1999
• Status: Expired due to Term

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Tummalapalli, Venkat Ranga Reddy
• Primary Examiner(s): Cardone, Jason D.
• Application Number:
  US09/549,824
• Time in Patent Office: 1,642 Days
• Field of Search: 709/224, 709/228, 707/3, 707/102, 707/103.R, 345/736
• US Class Current: 709/224
• CPC Class Codes: H04L 41/06 Management of faults, events, alarms or notifications
• CPC Class Codes: H04L 41/5009 Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

A distributed decision support system is described for use in the area of problem discovery and capacity planning for database applications. The use of data navigation, particularly drill down, roll up, and pivot for application management tasks are described. The system presents data collected from components of an application server system by various cartridges to users in a way that facilitates the identification of problems in the application server system and provides for an efficient way to do capacity planning of such systems.

Claims

1. A method for monitoring performance of an application server system, the method comprising the steps of:

collecting performance data from components of said application server system,

wherein the performance data includes at least one measure that reflects performance of said components;

storing said performance data as multidimensional data organized according to a plurality of dimensions within one or more database systems;

wherein one dimension of said plurality of dimensions is a hierarchical time dimension;

wherein another dimension of said plurality of dimensions is a component dimension;

presenting an interface for accessing and navigating through said multidimensional data within at least one of said one or more database systems; and

performing drill down operations into one or more hierarchical dimensions of said plurality of dimensions in response to user input received through said interface.

2. The method of claim 1 wherein:

the component dimension is a hierarchical dimension that includes a first level that corresponds to concurrent processing servers and a second level that corresponds to concurrent managers that correspond to said concurrent processing servers; and

the step of performing drill down includes performing drill down operations into the component dimension.

3. The method of claim 1 further comprising the step of performing pivot operations in response to user input received through said user interface.

4. The method of claim 1 further comprising the step of performing roll up operations on one or more hierarchical dimensions of said plurality of dimensions in response to user input received through said interface.

5. The method of claim 1 wherein the step of presenting an interface includes transmitting HTML code over a network to a browser.

6. The method of claim 1 wherein the step of presenting an interface includes presenting an interface that provides a view of said multidimensional data.

7. The method of claim 6 further comprising the step of selecting said view from a plurality of views based on identity of a user to which said interface is presented.

8. The method of claim 1 wherein:

the step of storing said performance data as multidimensional data organized according to a plurality of dimensions includes storing a series of snapshots of said performance data;

the method further includes the steps of establishing a particular snapshot in said series of snapshots as a baseline snapshot; and

comparing one or more snapshots that are subsequent to said baseline snapshot against said baseline snapshot to identify possible performance problems in said application server system.

9. The method of claim 1 wherein the step of collecting performance data includes collecting performance data from a plurality of concurrent processing servers.

10. The method of claim 1 wherein the step of collecting performance data includes collecting performance data from a database that hosts applications associated with the application server system.

11. The method of claim 1 wherein the step of collecting performance data includes collecting memory and CPU utilization information for a plurality of runtime instances of a forms application.

12. The method of claim 1 wherein the step of collecting performance data includes collecting performance data from an operating system on a node that is hosting an applications instance associated with the application server system.

13. A system comprising:

an application server system that includes application server components;

data collection components operatively coupled to a monitored set of application server components;

data storage components;

said data collection components being configured to collect performance data from said monitored set of application server components, said performance data including at least one measure that reflects performance of said application server components; and

to store said performance data as multidimensional data in said data storage components, said multidimensional data including a hierarchical time dimension;

data access components operatively coupled to said data storage components for retrieving and navigating through said multidimensional data, wherein at least one of said data access components includes controls for performing drill down operations in said hierarchical time dimension.

14. A computer-readable medium carrying one or more sequences of instructions for monitoring performance of an application server system, which instructions, when executed by one or more processors, cause the one or more processors to carry out the steps of:

collecting performance data from components of said application server system, wherein the performance data includes at least one measure that reflects performance of said components;

storing said performance data as multidimensional data organized according to a plurality of dimensions within one or more database systems,

wherein one dimension of said plurality of dimensions is a hierarchical time dimension; and

wherein another dimension of said plurality of dimensions is a component dimension;

presenting an interface for accessing and navigating through said multidimensional data within at least one of said one or more database systems; and

performing drill down operations into one or more hierarchical dimensions of said plurality of dimensions in response to user input received through said interface.

15. A computer-readable medium as recited in claim 14 wherein the step of presenting an interface includes presenting an interface that provides a view of said multidimensional data.

16. A computer-readable medium as recited in claim 15 further comprising instructions to cause the one or more processors to carry out the step of selecting said view from a plurality of views based on identity of a user to which said interface is presented.

17. A computer-readable medium as recited in claim 14 further comprising instructions to cause the one or more processors to carry out the step of performing a roll up operation on one or more hierarchical dimensions of said plurality of dimensions in response to user input received through said interface.

18. A computer-readable medium as recited in claim 14 wherein the step of presenting an interface includes transmitting HTML code over a network to a browser.

19. A computer-readable medium as recited in claim 14 wherein:

the component dimension is a hierarchical dimension that includes a first level that corresponds to concurrent processing servers and a second level that corresponds to concurrent managers that correspond to said concurrent processing servers; and

wherein the step of performing drill down includes performing drill down operations into the component dimension.

20. A computer-readable medium as recited in claim 14 further comprising instructions to cause the one or more processors to carry out the step of performing a pivot operation in response to input received through said user interface.

21. A computer-readable medium as recited in claim 14 wherein:

the step of storing said performance data as multidimensional data organized according to a plurality of dimensions includes storing a series of snapshots of said performance data; and

wherein the computer readable storage medium further comprises instructions to cause the one or more processors to carry out the steps of;

establishing a particular snapshot in said series of snapshots as a baseline snapshot; and

comparing one or more snapshots that are subsequent to said baseline snapshot against said baseline snapshot to identify possible performance problems in said application server system.

22. A computer-readable medium as recited in claim 14 wherein the step of collecting performance data includes collecting performance data from a plurality of concurrent processing servers.

23. A computer-readable medium as recited in claim 14 wherein the step of collecting performance data includes collecting performance data from a database that hosts applications associated with the application server system.

24. A computer-readable medium as recited in claim 14 wherein the step of collecting performance data includes collecting memory and CPU utilization information for a plurality of runtime instances of a forms application.

25. A computer-readable medium as recited in claim 14 wherein the step of collecting performance data includes collecting performance data from an operating system on a node that is hosting an applications instance associated with the application server system.