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

A system for optimizing and scaling a production network, the production network comprising a plurality of servers which operates a set of business functions, where each business function is a user task having a sequence of transactions between a client computer and the plurality of servers, a collection of network sniffers deployed on the production network, an analysis computer connected to the production network and the collection of network sniffers, the analysis computer programmed to carry out the steps of:

• loading a discrete event simulation tool;
• gathering resource data from a business function load test on the plurality of servers;
• wherein the resource data includes a reporting interval, a plurality of timestamps, and a plurality of resource utilization indicators for a single business function in the set of business functions;
• merging the resource data into a single table;
• equalizing at least one reporting interval in the resource data to a standard measurement interval by extrapolating a set of utilization data within the resource data;
• synchronizing at least one time stamp in the resource data;
• converting at least one set of units in the plurality of resource utilization indicators to a set of consistent units;
• aggregating a set of servers, from the plurality of servers, into a mega server;
• gathering a set of network data from a functional trace test carried out by the collection of network sniffers;
• deriving a transaction summary from the set of network data wherein the transaction summary comprises a tabular listing of the sequence of transactions for each business function in the set of business functions, the tabular listing including information related to resource usage within the plurality of servers;
• deriving a set of 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;
• calculating a business function cost for the single business function by dividing the resource consumption by a measured number of executions of the single business function;
• deriving a single business function profile for the single business function from the resource data, the business function cost for the single business function and the number of business functions in the set of business functions;
• adopting a transaction flow from the transaction summary;
• building a discrete event simulation model from the single business function profile and the transaction flow;
• and,
• performing a simulation of the production network with the discrete event simulation model in the discrete event simulation tool and producing a report displayed on the analysis computer which optimizes and scales the production network.