Collaborative Lifecycle Management performance report: RRC 4.0.6 release

Introduction

This report compares the performance of an unclustered Rational Requirements Composer version 4.0.6 deployment to the previous 4.0.5 release. The test objective is achieved in three steps:

• Run version 4.0.5 with standard 1.5 -hour test using 400 concurrent users.
• Run version 4.0.6 with standard 1.5 -hour test using 400 concurrent users.
• The test is run three times for each version and the resulting six tests are compared with each other. Three tests per version is used to get a more accurate picture since there are variations expected between 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.

What our tests measure

We use predominantly automated tooling such as Rational Performance Tester (RPT) to simulate a workload normally generated by client software such as the Eclipse client or web browsers. All response times listed are those measured by our automated tooling and not a client.

The diagram below describes at a very high level which aspects of the entire end-to-end experience (human end-user to server and back again) that our performance tests simulate. The tests described in this article simulate a large part of the end-to-end transaction as indicated. Performance tests include some simulation of browser rendering and network latency between the simulated browser client and the application server stack.

Findings

Performance goals

• Verify that there are no performance regressions between current release and prior release with 400 concurrent users using the workload described below.
  • The challenge we experience is that there is a high variance of execution time within a single run. Depending on the load that the server is under in any given moment the execution time will vary considerably. This could be avoided by testing the performance in a single user environment but the purpose of this test is to ensure performance is acceptable also when the server is under heavy load. Using the median rather than the average when calculating the execution times within each test run will lessen the impact of a few slow running performance numbers.
  • When comparing the three old runs with the three new runs we use the average of the three runs. Because of the difference in execution times of pages between runs, as can be observed in the charts below, a margin of error of 10% is generally tolerated although faster running pages typically have a higher margin of errors (larger variation between runs).

Findings

• The RPT report shows similar response times for 4.0.6 and 4.0.5.
• Comparing nmon data for both 4.0.6 and 4.0.5 show similar CPU, memory and disk utilization on application servers and database server.

Topology

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

The specifications of machines under test are listed in the table below. Server tuning details listed in Appendix A

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 0.3ms latency in ping.

Data volume and shape

The artifacts were distributed between 10 projects for a total of 240,659 artifacts.

The repository contained the following data:

• 219 modules
• 218,632 module artifacts
• 22,027 requirement artifacts
• 11,715 folders
• 150 collections
• 704 reviews
• 114,258 comments
• 3000 public tags
• 500 private tags
• 2,374 terms
• 75,941 links
• 2000 views

• Database size on disk = 20 GB
• JTS index size on disk = 11.5 GB

The large project contained the following data:

• 22 modules
• 1,170 folders
• 2,171 requirement artifacts
• 20,600 module artifacts
• 15 collections
• 62 reviews
• 11,350 comments
• 300 public tags
• 50 private tags
• 132 terms
• 7,676 links

Methodology

Rational Performance Tester 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.

Based on real customer use, the test scenario provides a ratio of 70% reads and 30% writes. The users completed use cases at a rate of 30 pages per hour per user. Each performance test runs for 90 minutes after all of the users are activated in the system.

Test cases and workload characterization

Response time comparison

The median response time provided more even results than the average response time. The nature of the high variance between tests where some tasks at time takes a longer time to run, such as when the server is under heavy load, makes the average response time less predictive. Both the median and average values are included in the following tables and charts for comparison.

In the repository that contained 240,000 artifacts with 400 concurrent users, no obvious regression was shown when comparing response times between runs.

The numbers in the following charts include all of the pages for all of the scripts that ran.

Results

Observation

Garbage collection

Verbose garbage collection is enable to create the GC logs. The GC logs shows 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.

RM

• Observation: The graph looks the same in 4.0.5 and 4.0.6.

JTS

• Observation: The graph looks the same in 4.0.5 and 4.0.6. The high frequency of collections is normal behavior for JTS.

Create a collection

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Filter a query

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Open nested folders

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Manage folders

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Query by ID

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View collections

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Check suspect links

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Add comments to an artifact

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Open the project dashboard

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Create a multi-value artifact

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Create an artifact

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Show artifacts in a Tree view

• Observation: There is a performance degradation when opening the tree view as can be seen in this graph. RRC defect 84312 was created for this issue and a patch exists that will restore the performance.

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Open graphical artifacts

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Create and edit a storyboard

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Display the hover information for a collection

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Query by string

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Create review

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Create a PDF report

• Observation: An improvement is enabling the saving action to perform faster as can be seen in the last step of the creation of a PDF report

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Create a Microsoft Word report

• Observation: An improvement is enabling the saving action to perform faster as can be seen in the last step of the creation of a Word report

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Browse project folder

• Observation: A performance improvement is observed when browse artifacts menu option is used

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Open collection and display first page

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Create artifact in large module

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Display module history

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Create traceability report using 50 artifact

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Open large module

• Observation: An improvement is seen when browse modules menu option is used

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Scroll through a large module

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Switch between modules

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Edit a module artifact

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Save a module

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Create a large module report

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Uploading 4 MB file in new artifact

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Review using a large module

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Switch view

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Hover over linked artifact

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Appendix A

-XX:MaxDirectMemorySize=1g -Xgcpolicy:gencon -Xmx8g -Xms8g -Xmn512m -Xcompressedrefs -Xgc:preferredHeapBase=0x100000000

For more information

• Collaborative Lifecycle Management 2012 Sizing Report (Standard Topology E1)

About the authors

GustafSvensson

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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