Method for building enterprise scalability models from load test and trace test data

• US 20060224375A1
• Filed: 03/13/2006
• Published: 10/05/2006
• Est. Priority Date: 03/11/2005
• Status: Active Grant

• Current Assignee: HyPerformix, Inc. (Broadcom, Inc.)
• Original Assignee: HyPerformix, Inc. (Broadcom, Inc.)
• Inventors: Reynolds, James, Clarke, Allan Drew, Barnett, Paul T., Gimarc, Richard, Wise, Timothy E.
• Granted Patent: US 7,818,150 B2
• Time in Patent Office: Days
• US Class Current: 703/22
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3447 Performance evaluation by modeling
• CPC Class Codes: G06F 11/3461 Trace driven simulation
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/835 Timestamp
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2201/87 Monitoring of transactions
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: G06F 2201/88 Monitoring involving counting

Abstract

A method is disclosed that preparing a discrete event simulation model of a production network is provided including a client and a plurality of servers connected by a network comprising the steps of initiating a single business function trace test on the production network; gathering network from trace data from the network; deriving a transaction summary from the network flow trace data; initiating a single business function load test on the production network; gathering resource data from the plurality of servers; normalizing the resource data; gathering web log data from at least one server from the plurality of servers; calculating a number of business functions running on the production network; calculating a consumption of resources used by the plurality of servers; calculating a business function cost associated with the consumption of resources; creating a business function profile from the transaction summary and the business function cost; and building a discrete event simulation model from the business function profile.

Claims

1. A method of preparing a discrete event simulation model of a production network including a client and a plurality of servers connected by a network comprising the steps of:

initiating a single business function trace test on the production network;

gathering network from trace data from the network;

deriving a transaction summary from the network flow trace data;

initiating a single business function load test on the production network;

gathering resource data from the plurality of servers;

normalizing the resource data;

gathering web log data from at least one server from the plurality of servers;

calculating a number of business functions running on the production network;

calculating a consumption of resources used by the plurality of servers;

calculating a business function cost associated with the consumption of resources;

creating a business function profile from the transaction summary and the business function cost; and

building a discrete event simulation model from the business function profile.

2. The method of claim 1 wherein the step of creating a business function profile further comprises the steps of:

deriving a transaction visit count from the transaction summary; and

calculating a transaction resource usage by dividing a business function resource usage by the transaction visit count.

3. The method of claim 1 wherein the step of gathering resource data further comprises the steps of:

deploying one of a plurality of resource monitors on each server resident on the production network;

collecting the resource data from the plurality of resource monitors; and

merging the resource data into a single file for analysis.

4. The method of claim 1 wherein the step of normalizing further comprises the steps of:

equalizing a reporting interval in the resource data;

aggregating servers on at least one tier of the production network; and

synchronizing at least 2 timestamps present in the resource data.

5. The method of claim 1 wherein the step of calculating a consumption of resources further comprises the step of:

multiplying the calculated consumption of resources by a measurement period.

6. The method of claim 5 wherein the step of calculating a consumption of resources further comprises the step of:

repeating the step of multiplying and accumulating a running total of consumption of resources.

7. The method of claim 1 wherein the step of calculating a consumption of resources further comprises counting a number of unique URL occurrences in the web log data.

8. The method of claim 1 comprising the further step of:

running the discrete event simulation model on a discrete event simulation modeler.

9. A computer program product adaptable for storage on a computer readable medium and operable for creating a discrete event simulation model of a business function comprising the program steps of:

gathering resource data from a function load test on a plurality of servers deployed on a network;

wherein the resource data includes a reporting interval, a plurality of timestamps, and a plurality of resource utilization indicators;

equalizing at least one reporting interval in the resource data;

synchronizing at least one time stamp in the resource data;

normalizing at least one set of units in the plurality of resource utilization indicators;

gathering network data from a functional trace test;

deriving a transaction summary from the network data;

deriving web log data from the function load test;

calculating a number of business functions from the transaction summary;

calculating a resource consumption for the plurality of servers;

deriving a business function profile from the resource data and the number of business functions;

adopting a transaction flow from the transaction summary; and

building a discrete event simulation model from the business function profile and the transaction flow.

10. The computer program product of claim 9 wherein the program step of calculating a resource consumption for the plurality of servers further comprises the program step of:

multiplying the resource utilization during the reporting interval by the length of the reporting interval.

11. The computer program product of claim 9 wherein the program step of deriving a business function profile further comprises the program step of:

dividing the resource consumption by the number of business functions.

12. The computer program product of claim 9 wherein the step of calculating a number of business functions for the transaction summary further comprises:

identifying a business function search entity form an HTTP map; and

searching a web log for the business function search entity.

13. The computer program product of claim 12 wherein the business functions search entity is one of the group of text and regular expression.

14. The computer program product of claim 9 wherein the step of deriving a business function profile further comprises the step of:

deriving the business function cost for each of a plurality of transactions related to the business function.

21. The method of claim 13 wherein the step of creating a business function profile further comprises the step of identifying a visit count.

22. The method of claim 13 wherein the step of calculating a business function profile further comprises searching a web log with a search technique to locate the number of occurrences of the business function.

23. The method of claim 22 wherein the search technique is one of the group of pattern matching and text matching.

15. A method of preparing an instruction table of a business function for a discrete event simulation modeler comprising the steps of:

measuring network flow trace data on a network;

analyzing the network flow trace data to derive a transaction summary;

gathering resource data from a plurality of servers on the network;

gathering web log data from at least one server on the network;

calculating a number of business functions from the network flow trace data;

calculating a resource consumption from the resource data;

calculating a business function cost;

creating a business function profile from the business function cost; and

building an instruction table from the transaction summary and the business function profile.

16. The method of claim 15 wherein the step of gathering resource data further comprises collecting the resource data and merging the resource data.

17. The method of claim 15 further comprising the step of normalizing resource data after the step of gathering resource data.

18. The method of claim 17 wherein the step of normalizing resource data further comprises the steps of:

equalizing a reporting interval;

synchronizing a timestamp; and

normalizing units of the resource data.

19. The method of claim 15 wherein the step of calculating a business function cost further comprises the step of:

dividing a measured resource usage by the number of business functions.

20. The method of claim 15 wherein the step of creating a business function profile further comprises dividing a business function resource usage by a transaction visit count derived from the network flow trace data.