Method for building enterprise scalability models from production data

• US 20100106478A1
• Filed: 08/05/2009
• Published: 04/29/2010
• Est. Priority Date: 02/01/2006
• Status: Active Grant

• Current Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Original Assignee: CA, Inc. (d/b/a CA Technologies) (Broadcom, Inc.)
• Inventors: Reynolds, James, Clarke, Allan Drew, Barnett, Paul T., Gimarc, Richard, Spellmann, Amy, Wise, Timothy E.
• Granted Patent: US 8,271,643 B2
• Time in Patent Office: Days
• US Class Current: 703/17
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

The invention provides a method for preparing a discrete event simulation model of a production network including a client and a plurality of servers on a plurality of network tiers connected by a network comprising the steps of executing a business function from the client on the production network, gathering resource data from the plurality of servers, normalizing the resource data, calculating a consumption of resources used by the plurality of servers, estimating a transaction cost associated with the consumption of resources and building a discrete event simulation model from the transaction cost.

Claims

1. A computer readable medium containing a computer program product storing a set of computer executable instructions, the set of computer executable instructions operable on a host computer system, including a CPU, that when executed creates a discrete event simulation model of a production network including a client and a plurality of servers on a plurality of network tiers connected by a network, the plurality of servers executing a plurality of applications, and running a business function, by performing the steps of:

executing the business function, including accessing a plurality of applications running on the production network, from the client on the production network;

gathering resource data from the plurality of servers;

normalizing the resource data;

synchronizing the resource data by utilizing a set of timestamp data;

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

estimating a transaction cost associated with the consumption of resources;

building a discrete event simulation model from the transaction cost; and

,

storing the discrete event simulation model on the computer readable medium.

2. The computer readable medium of claim 1 wherein the step of gathering 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 including collecting the set of time stamp data; and

merging the resource data into a single file for analysis.

3. The computer readable medium of claim 2 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.

4. The computer readable medium of claim 2 wherein the step of building a discrete event simulation model further comprises the steps of:

assembling a table containing the transaction costs;

approximating a flow of a transaction associated with the business function;

calculating data throughput on a network interface of the production network; and

assembling the approximated flow of a transaction associated with the business function with the calculated data throughput on a network interface of the production network.

5. The computer readable medium of claim 2 wherein the step of calculating further comprises the step of:

multiplying the calculated consumption of resources by a measurement period.

6. The computer readable medium of claim 5 wherein the step of calculating data throughput further comprises the step of:

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

7. The computer readable medium of claim 1 wherein the step of estimating a transaction cost further comprises the step of:

dividing the calculated consumption of resources by a number of transactions performed during a measurement period.

8. The computer readable medium of claim 1 comprising the further step of:

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

9. The computer readable medium of claim 8 wherein the number of transactions is derived from a transaction log.

10. The computer readable medium of claim 8 wherein the number of transactions is derived from a load test.

11. The computer readable medium of claim 1 wherein the production network is a non-linear production network and the step of building an instruction table further comprises the steps of:

assuming an iteration count between at least two alternate paths on the non-linear production network;

statistically accounting for each of the at least two alternate paths on the non-linear production network; and

allocating the calculated consumption of resources among the at least two alternate paths.

12. A computer readable medium containing a computer program product storing a set of computer executable instructions, the set of computer executable instructions operable on a host computer system, including a CPU, that when executed creates a discrete event simulation model comprising the program steps of:

gathering resource data from a plurality of resource monitors operatively disposed on a plurality of servers resident on a multi-tiered computer system executing a business function;

the business function accessing a plurality of applications running on the multi-tiered computer system;

wherein the resource data includes a reporting interval, a timestamp, a resource utilization, a received packet count and a sent packet count;

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 resource data;

calculating a resource consumption for the plurality of servers;

calculating a transaction cost from the resource data;

approximating a transaction flow for a plurality of transactions related to the business function;

calculating a network throughput between the plurality of servers; and

building a discrete event simulation model from the transaction cost, the transaction flow and the network throughput; and

storing the discrete event simulation model on the computer readable medium.

13. The computer readable medium of claim 12 wherein the step of calculating a network throughput between the plurality of servers further comprises the program steps of:

eliminating duplicate data from the sent packet count; and

eliminating duplicate data from the received packet count.

14. The computer readable medium of claim 12 wherein the program step of approximating a transaction flow comprises the further program steps of:

estimating the transaction flow of a linear multi-tiered system.

15. The computer readable medium of claim 12 wherein the program step of approximating a transaction flow comprises the further program steps of:

estimating the transaction flow of a non-linear multi-tiered system.

16. The computer readable medium of claim 15 wherein the program step of estimating the transaction flow of a non-linear multi-tiered system comprises the further program steps of:

statistically accounting for a set of alternate paths on the multi-tiered system.

17. A system for creating a discrete event simulation model, comprising an analysis computer communicatively connected to a multi-tiered computer system, the multi-tiered computer system executing a business function, the analysis computer programmed to perform the steps of:

gathering a set of resource data from a plurality of resource monitors operatively disposed on a plurality of servers resident on each tier of the multi-tiered computer system;

the business function accessing a plurality of applications running on the multi-tiered computer system;

wherein the set of resource data includes a reporting interval, a timestamp, a resource utilization, a received packet count and a sent packet count;

equalizing at least one reporting interval in the set of resource data;

synchronizing at least one time stamp in the set of resource data;

normalizing at least one set of units in the set of resource data;

calculating a resource consumption for the plurality of servers resident on each tier of the multi-tiered computer system;

calculating a transaction cost from the resource consumption;

approximating a transaction flow for a plurality of transactions related to the business function;

calculating a network throughput between the plurality of servers; and

building a discrete event simulation model from the transaction cost, the transaction flow and the network throughput; and

executing the discrete event simulation model on the analysis computer.

20. The computer system of claim 17 wherein the step of normalizing further comprises aggregating resource data from the plurality of servers, residing on each tier of the multi-tiered computer system, into a single server model.

18. The computer system of 17 wherein the step of calculating the resource consumption for the plurality of servers further comprises extrapolating a value for at least one resource datum of the set of resource data for the at least one reporting interval.

19. The computer system of 17 wherein the step of calculating the resource consumption for the plurality of servers further comprises interpolating a value for at least one resource datum of the set of resource data for the at least one reporting interval.