Using Application Performance Signatures For Characterizing Application Updates

• US 20100094592A1
• Filed: 10/14/2008
• Published: 04/15/2010
• Est. Priority Date: 04/25/2008
• Status: Active Grant

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Mi, Ningfang, Ozonat, Mehmet Kivanc, Symons, Julie A., Cherkasova, Ludmila
• Granted Patent: US 8,224,624 B2
• Time in Patent Office: Days
• US Class Current: 702/182
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 2201/80 Database-specific techniques
• CPC Class Codes: G06F 2201/865 Monitoring of software
• CPC Class Codes: G06F 2201/87 Monitoring of transactions
• CPC Class Codes: G06F 2201/88 Monitoring involving counting

Abstract

One embodiment is a method that determines application performance signatures occurring at an application server in a multi-tier architecture. The method then analyzes the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application.

Claims

1. ) A method, comprising:

calculating a first application performance signature for an application at an application server;

calculating a second application performance signature for the application at the application server after providing an update to the application, wherein the first and second application performance signatures are computed from a service time for transaction requests from a client computer;

comparing the first and second application performance signatures to determine whether a change in transaction performance at the application server results from the update; and

providing results of the change to a user.

2. ) The method of claim 1 further comprising, simultaneously plotting the first and second application performance signatures on a graph to show whether the change in transaction performance at the application server results from the update.

3. ) The method of claim 1 further comprising, plotting the first and second application performance signatures on a graph having one axis as transaction number and a second axis as service time of transactions.

4. ) The method of claim 1 further comprising, measuring transaction latencies for wailing times and service times at both the application server and a database server.

5. ) The method of claim 1 further comprising, wherein the service time is a function of a residence time for a transaction and a throughput of transactions processed at the application server.

6. ) The method of claim 1 further comprising, classifying observed transactions at the application server into Central Processing Unit (CPU) buckets for each of plural different monitoring windows of time.

7. ) The method of claim 1 further comprising, computing transaction latencies at different Central Processing Unit (CPU) utilizations for different types of transactions requested by the client computer.

8. ) A tangible computer readable storage medium having instructions for causing a computer to execute a method, comprising:

determining application performance signatures occurring at an application server in a multi-tier architecture, the application performance signatures being a function of transaction processing time, transaction latency, and server utilization;

analyzing the application performance signatures to determine whether a change in transaction performance at the application server results from a modification to an application; and

outputting analysis of the change.

9. ) The tangible computer readable storage medium of claim 8 further comprising, plotting the application performance signatures to determine whether the change in transaction performance at the application server results from the modification to the application.

10. ) The tangible computer readable storage medium of claim 8 further comprising, removing outliers from the application performance signatures at the application server to remove CPU utilization that is under-represented.

11. ) The tangible computer readable storage medium of claim 8 further comprising, simultaneously comparing on a graph a first application performance signature calculated before the modification to a second application performance signature calculated after the modification.

12. ) The tangible computer readable storage medium of claim 8, wherein the application performance signatures are a function of service time and residence time for transactions at the application server.

13. ) The tangible computer readable storage medium of claim 8 further comprising, plotting on a single graph the application performance signatures occurring at the application server for plural different workload mixes.

14. ) The tangible computer readable storage medium of claim 8 further comprising, determining whether a change in transaction execution time at the application server results from an increase in workload or the modification.

15. ) The tangible computer readable storage medium of claim 8, wherein the transaction processing time (S) is based on the transaction latency (R) and the server utilization (U) as follows:

S=R*(1−

U).

16. ) A computer system, comprising:

a memory for storing an algorithm; and

a processor for executing the algorithm to;

determine application performance signatures occurring at an application server in a multi-tier architecture, the application performance signatures being a function of transaction processing time, transaction latency, and server utilization;

analyze the application performance signatures during a monitoring window to determine whether a change in transaction performance at the application server results from a modification to an application.

17. ) The computer system of claim 16, wherein the processor further executes the algorithm to plot the application performance signatures of the application server to visually show whether the change in the transaction performance results from the update to the application or changes in transaction workload occurring at the application server.

18. ) The computer system of claim 16, wherein the processor further executes the algorithm to compute transaction latencies at different Central Processing Unit (CPU) utilizations for different types of transactions received at the application server from a client computer.

19. ) The computer system of claim 16, wherein the processor further executes the algorithm to remove outliers from the application performance signatures at the application server to remove Central Processing Unit (CPU) utilization that is under-represented.

20. ) The computer system of claim 16, wherein the processor further executes the algorithm to determine whether the change in transaction performance results from an increase in load in the multi-tier architecture.