System and method for automated analysis of load testing results

• US 20030074161A1
• Filed: 08/06/2002
• Published: 04/17/2003
• Est. Priority Date: 08/06/2001
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: Mercury Interactive Corp. (HP Inc.)
• Inventors: Landan, Gideon, Smocha, Itzhak
• Granted Patent: US 6,694,288 B2
• Time in Patent Office: Days
• US Class Current: 702/186
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3433 for load management allocation of a server based on load conditions G06F9/505; load rebalancing G06F9/5083; redistributing the load in a network by a load balancer H04L67/1029
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 11/3457 Performance evaluation by simulation
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/81 Threshold
• CPC Class Codes: G06F 2201/815 Virtual
• 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 2201/885 Monitoring specific for caches

Abstract

A system for monitoring and evaluating the performance of a network accessible application comprises one or more load servers, each of which is capable of simulating the load imposed upon the application server by one or more clients. The load servers are configured to execute a particular sequence of server requests in order to evaluate the operation of the server under the specified load. Various performance metrics associated with the operation of the network and the application server are measured during the testing of the server, and these metrics are stored for later access by an analysis module. The analysis module identifies those portions of the test data which are statistically significant and groups these significant parameters to suggest possible relationships between the conditions of the load test and the observed performance results.

Claims

1. A method for load testing a server, the method comprising the computer-implemented steps of:

making a series of requests of a server from a client in accordance with a testing profile;

measuring the values of at a least two performance metrics associated with the server while the series of requests are made;

storing data representing the measured values of the performance metrics and a time index indicating when each value was measured;

identifying at least one significant portion of the stored data for each performance metric;

for each pair of performance metrics, determining a degree of correlation between the significant portions of the at least two performance metrics; and

presenting a representation of the correlation between the at least two performance metrics.

2. The method of claim 1 wherein the server comprises a web server which receives requests from the client and sends a reply to the client via a hypertext transport protocol.

3. The method of claim 1 wherein the client comprises a virtual client running on a load server.

4. The method of claim 3 wherein the load server comprises a plurality of virtual clients, each of which is configured to make a series of requests of the server in accordance with a testing profile.

5. The method of claim 1 wherein the testing profile is sent to the client from a control console.

6. The method of claim 1 wherein the step of measuring the values of at least two performance metrics further comprises measuring the value of a performance metric associated with the client while the series of requests are made.

7. The method of claim 1 wherein the step of presenting a representation of the correlation comprises presenting a graphical representation of the measured values of the at least two performance metrics.

8. A method for analyzing the load on a server, the method comprising:

providing at least one client configured to send a series of requests to a server;

measuring a plurality of parameters of the server over the period of time during which the server receives requests from the at least one client;

storing a series of values representing these measured parameters;

associating a time at which each value was measured with each stored value;

identifying correlations between the measured parameters based upon the stored values for the parameters; and

selecting parameters which may be related to one another based upon the correlation between the measured values of the parameters.

9. The method of claim 8 wherein the series of requests the at least one client is configured to send simulates the behavior of a user connecting to the server.

10. The method of claim 8 wherein the at least one client comprises a load server configured to simultaneously simulate the operation of a plurality of clients.

11. The method of claim 8 wherein the step of identifying correlations comprises performing a sampling analysis on each series of values in order to identify the significant portion of each series.

12. The method of claim 11 wherein the step of identifying correlations further comprises comparing the significant portion of a first series of values to the significant portion of a second series in order to determine a correlation between the first series and the second series.

13. The method of claim 8 wherein the step of identifying correlations further comprises calculating a correlation coefficient between the series of values for one parameter and the series of values for another parameter.

14. The method of claim 13 wherein the step of selecting parameters which may be related comprises comparing the correlation coefficient associated with a pair of parameters to a lower threshold value and selecting the pair of parameters if the correlation coefficient is greater than the lower threshold value.

15. The method of claim 13 wherein the step of selecting parameters which may be related comprises comparing the correlation coefficient associated with a pair of parameters to an upper threshold value and selecting the pair of parameters if the correlation coefficient is less than the upper threshold value.

16. A load testing analysis system for identifying correlations between performance parameters of a server, the system comprising:

a server to be load tested;

a communications medium through which requests may be sent to the server and through which replies may be sent by the server;

at least one client process which sends a plurality of requests to the server via the communications medium;

a control console which receives performance data from the server, the performance data corresponding to a plurality of performance metrics associated with the operation of the server; and

an analysis module configured to correlate the plurality of performance metrics in order to determine any relationship between any pair of the plurality of performance metrics.