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new.pngCollaborative Lifecycle Management performance report: Rational Quality Manager 6.0.4 release

Authors: Hongyan Huo
Last updated: May 20, 2017
Build basis: Rational Quality Manager 6.0.4

Introduction

This report compares the performance of Rational Quality Manager (RQM) version 6.0.4 to the previous 6.0.3 release, using a large repository that contains 10 million test artifacts in total. The goal of the test was the verify that the performance of the 6.0.4 operations were the same or better than their 6.0.3 equivalents.

The test methodology involves these steps:

  • Collect the standard one-hour performance test data using 1,000 concurrent users from RQM 6.0.3 (repeat 2 times)
  • Repeat the same standard one-hour performance test load against RQM 6.0.4 using 1,000 concurrent users (repeat 2 times)
  • Compare the 4 runs

Disclaimer

The information in this document is distributed AS IS. The use of this information or the implementation of any of these techniques is a customer responsibility and depends on the customer’s ability to evaluate and integrate them into the customer’s operational environment. While each item may have been reviewed by IBM for accuracy in a specific situation, there is no guarantee that the same or similar results will be obtained elsewhere. Customers attempting to adapt these techniques to their own environments do so at their own risk. Any pointers in this publication to external Web sites are provided for convenience only and do not in any manner serve as an endorsement of these Web sites. Any performance data contained in this document was determined in a controlled environment, and therefore, the results that may be obtained in other operating environments may vary significantly. Users of this document should verify the applicable data for their specific environment.

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multi-programming in the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

This testing was done as a way to compare and characterize the differences in performance between different versions of the product. The results shown here should thus be looked at as a comparison of the contrasting performance between different versions, and not as an absolute benchmark of performance.

Summary of performance results

We applied the standard performance load using a large QM repository containing 10 million artifacts against RQM 6.0.3 and 6.0.4 respectively (refer to section Data volume and shape for details). Test results showed the general performance of 6.0.4 is better than the 6.0.3 equivalents. Most of the pages under test were observed to be faster, comparing 6.0.4 to 6.0.3, which resulted in an overall 25% decrease in average page response time by all pages, as seen in the chart below.

There are a certain number of significant performance improvements made into 604, including viewing a test suite containing large number of test cases, selecting test scripts to add to a test case, and viewing test schedules for a test plan. Below is a chart showing the top pages that have been improved greatly

For more details on the 1000 user workload, see this section: User roles, test cases and workload characterization .

For the detailed performance results for each use case, see this section: Detailed performance results.

Summary of OS resource utilization

Comparing system resource data for both 6.0.4 release and 6.0.3, 6.0.4 has
  • Reduced CPU utilization on both DB server WAS application server than 6.0.3
  • Reduced network I/O than 6.0.3
  • Slightly reduced disk utilization on both DB server WAS application server than 6.0.3
  • Similar memory consumption for QM DB on the DB server with 6.0.3

The details are provided in section Resource utilization

Appendix A: Topology

The topology under test is based on Standard Topology (E1) Enterprise - Distributed / Linux / DB2.

ServerOverview.png

The specifications of machines under test are listed in the table below. Server tuning details listed in Appendix D: Key configuration parameters

Function Number of Machines Machine Type CPU / Machine Total # of CPU vCores/Machine Memory/Machine Disk Disk capacity Network interface OS and Version
Proxy Server (IBM HTTP Server and WebSphere Plugin) 1 IBM System x3250 M4 1 x Intel Xeon E3-1240 3.4GHz (quad-core) 8 16GB RAID 1 -- SAS Disk x 2 299GB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.5
JTS Server 1 IBM System x3550 M4 2 x Intel Xeon E5-2640 2.5GHz (six-core) 24 32GB RAID 5 -- SAS Disk x 2 897GB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.5
QM Server 1 IBM System x3550 M4 2 x Intel Xeon E5-2640 2.5GHz (six-core) 24 32GB RAID 5 -- SAS Disk x 2 897GB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.5
Database Server 1 IBM System x3650 M4 2 x Intel Xeon E5-2640 2.5GHz (six-core) 24 64GB RAID 5 -- SAS Disk x 2 2.4TB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.1
RPT workbench 1 IBM System x3550 M4 2 x Intel Xeon E5-2640 2.5GHz (six-core) 24 32GB RAID 5 -- SAS Disk x 2 897GB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.4
RPT Agents 6 VM image 4 x Intel Xeon X5650 CPU (1-Core 2.67GHz) 1 2GB N/A 30GB Gigabit Ethernet Red Hat Enterprise Linux Server release 6.5
Network switches N/A Cisco 2960G-24TC-L N/A N/A N/A N/A N/A Gigabit Ethernet 24 Ethernet 10/100/1000 ports

N/A: Not applicable. vCores = Cores with hyperthreading

Network connectivity

All server machines and test clients are located on the same subnet. The LAN has 1000 Mbps of maximum bandwidth and less than 0.3 ms latency in ping.

Data volume and shape

The artifacts were migrated from 6.0.3GA repository which contains a total of 10.7M artifacts in one large project.

The repository contained the following data:

  • 1667 test plans
  • 1,000,000 test scripts
  • 1,000,000 test cases
  • 4,000,000 test case execution records
  • 4,000,000 test case results
  • 100,000 test suites
  • 5,000 work items(defects)
  • 6667 test environments
  • 20,000 test phases
  • 200 build definitions
  • 47,470 execution sequences
  • 100,000 test suite execution records
  • 500,000 test suite execution results
  • 33,333 build records

  • QM Database size = 310 GB
  • QM full text index size = 15 GB

The artifact maintains the following associations:

  • each test plan is linked to 600 unique test cases, and 600 unique test scripts
  • each test suite contains 500 test cases

In this test environment, the Configuration Management is not enabled.

Appendix B: Methodology

Rational Performance Tester(RPT) was used to simulate the workload created using the web client. Each user completed a random use case from a set of available use cases. A Rational Performance Tester script is created for each use case. The scripts are organized by pages and each page represents a user action.

The work load is role based as each of the areas defined under sequence of actions which are separated into individual user groups within an RPT schedule. The settings of the RPT schedule is shown below:

User roles, test cases and workload characterization

User Roles
Use role % of Total Related Actions
QE Manager 8 Test plan create, Browse test plan and test case, Browse test script, Simple test plan copy, Defect search, View dashboard
Test Lead 19 Edit Test Environments, Edit test plan, Create test case, Bulk edit of test cases, Full text search, Browse test script, Test Execution, Defect search
Tester 68 Defect create, Defect modify, Defect search, Edit test case, Create test script, Edit test script, Test Execution, Browse test execution record
Dashboard Viewer 5 View dashboard(with login and logout)

Test Cases

Use Role Percentage of the user role Sequence of Operations
QE Manager 1 Test plan create:user creates test plan, then adds description, business objectives, test objectives, 2 test schedules, test estimate quality objectives and entry and exit criteria.
26 Browse test plans and test cases: user browses assets by: View Test Plans, then configure View Builder for name search; open test plan found, review various sections, then close. Search for test case by name, opens test case found, review various sections, then close.
26 Browse test script: user search for test script by name, open it, reviews it, then closes.
1 Simple test plan copy: user search test plan by name, then select one, then make a copy.
23 Defect search: user searches for specific defect by number, user reviews the defect (pause), then closes.
20 View Dashboard: user views dashboard
Test Lead 8 Edit Test Environment: user lists all test environments, and then selects one of the environments and modifies it.
15 Edit test plan: list all test plans; from query result, open a test plan for editing, add a test case to the test plan, a few other sections of the test plan are edited and then the test plan is saved.
4 Create test case: user create test case by: opening the Create Test Case page, enters data for a new test case, and then saves the test case.
1 Bulk edit of test cases: user searches for test cases with root name and edits all found with owner change.
3 Full text search: user does a full text search of all assets in repository using root name, then opens one of found items.
32 Browse test script: user search for test script by name, open it, reviews it, then closes.
26 Test Execution: selects “View Test Execution Records”, by name, starts execution, enters pass/fail verdict, reviews results, sets points then saves.
11 Defect search: user searches for specific defect by number, user reviews the defect (pause), then closes.
Tester 8 Defect create: user creates defect by: opening the Create Defect page, enters data for a new defect, and then saves the defect.
5 Defect modify: user searches for specific defect by number, modifies it then saves it.
14 Defect search: user searches for specific defect by number, user reviews the defect (pause), then closes.
6 Edit test case: user searches Test Case by name, the test case is then opened in the editor, then a test script is added to the test case (user clicks next a few times (server size paging feature) before selecting test script), The test case is then saved.
4 Create test script: user creates test case by: selecting Create Test Script page, enters data for a new test script, and then saves the test script.
8 Edit test script: user selects Test Script by name. test script then opened for editing, modified and then saved.
42 Test Execution: selects “View Test Execution Records”, by name, starts execution, enters pass/fail verdict, reviews results, sets points then saves.
7 Browse test execution record: user browses TERs by: name, then selects the TER and opens the most recent results.
Dashboard Viewer 100 View dashboard(with login and logout): user logs in, views dashboard, then logs out. This user provides some login/logout behavior to the workload

Response time comparison

The page performance is measured as mean value (or average) of its response time in the result data. For the majority of the pages under tests, there is little variation between runs, and the mean values are close to median in the sample for the load.

Appendix C: Detailed performance results

Average page response time comparison breakdown

For all usecase comparison charts, the unit is millisecond, and for the data, smaller is better.

Create Defect

Back to Test Cases & workload characterization

Create Test Plan

Back to Test Cases & workload characterization

Create Test Case

Back to Test Cases & workload characterization

Create Test Script

Back to Test Cases & workload characterization

Browse Test Plans & Test Cases

Back to Test Cases & workload characterization

Browse Test Scripts

Back to Test Cases & workload characterization

Bulk Edit of Test Cases

Back to Test Cases & workload characterization

Defect Search

Back to Test Cases & workload characterization

Defect Modify

Back to Test Cases & workload characterization

Edit Test Case

Back to Test Cases & workload characterization

Edit Test Environment

Back to Test Cases & workload characterization

Edit Test Plan

Back to Test Cases & workload characterization

Edit Test Script

Back to Test Cases & workload characterization

Full Text Search

Back to Test Cases & workload characterization

Simple Test Plan Copy

Back to Test Cases & workload characterization

Test Execution For 4 Steps

Back to Test Cases & workload characterization

Test Execution Record Browsing

Back to Test Cases & workload characterization

View Dashboard

Back to Test Cases & workload characterization

View Dashboard with Login

Back to Test Cases & workload characterization

RPT network transfer comparison

RPT script execution composition

The script execution breakdown is similar to the scalability test: RPT script executions breakdown in scalability test of 6.0.3

Resource utilization

OS resource utilization 6.0.4 vs 6.0.3 - overview
6.0.4 vs 6.0.3
CPU
Disk
Memory
Network

QM server resource utilization 6.0.4 vs 6.0.3
6.0.4 6.0.3
CPU
Disk
Memory
Network

DB server resource utilization 6.0.4 vs 6.0.3
6.0.4 6.0.3
CPU
Disk
Memory
Network

Garbage collection - JVM GC Chart

For JVM parameter please refer to Appendix D: Key configuration parameters

Verbose garbage collection is enabled to log the GC activities. These GC logs showed very little variation between runs. There is also no discernible difference between versions. Below is one example of the output from the GC log for each application.

WAS JVM Garbage Collection Charts 6.0.4 vs 6.0.3
6.0.4 6.0.3
QM
JTS

Appendix D - Key configuration parameters

Product
 Version Highlights for configurations under test
IBM HTTP Server for WebSphere Application Server 8.5.5.9 IBM HTTP Server functions as a reverse proxy server implemented via Web server plug-in for WebSphere Application Server.

Configuration details can be found from the CLM infocenter.

HTTP server (httpd.conf):

OS Configuration:

  • max user processes = unlimited
IBM WebSphere Application Server Network Deployment 8.5.5.9 JVM settings:

  • GC policy and arguments, max and init heap sizes: 

 -Xgcpolicy:gencon -Xmx8g -Xms8g -Xmn2g -Xss786K -Xcompressedrefs -Xgc:preferredHeapBase=0x100000000
 -verbose:gc -Xverbosegclog:gc.log -XX:MaxDirectMemorySize=1G

SDK version:

  • IBM WebSphere SDK for Java Technology Edition Version 7.1.3.40

Thread pools:

  • Maximum WebContainer = Minimum WebContainer = 500

OS Configuration:

System wide resources for the app server process owner:

  • max user processes = unlimited
  • open files = 65536

DB2 ESE 10.1.0.5
LDAP server
License server N/A
RPT workbench 8.3.0.3 Defaults
RPT agents 8.3.0.3 Defaults
Network Shared subnet within test lab

About the authors:

HongyanHuo is a performance engineer focusing on the scalability of products in the Collaborative Lifecycle Management family.

Related topics: Collaborative Lifecycle Management performance and scalability report: Rational Quality Manager 6.0.3 release

Questions and comments:
  • What other performance information would you like to see here?
  • Do you have performance scenarios to share?
  • Do you have scenarios that are not addressed in documentation?
  • Where are you having problems in performance?

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