Performance Center and Jenkins

This section describes the Jenkins plugin, and how it enables you to use continuous performance testing in production. It enables you to run performance tests using Performance Center and to view Performance Center Trend reports.

Continuous integration with Jenkins overview

As more software companies utilize continuous integration practices, you may also need to integrate performance tests into your testing process. This integration helps developers insure that new builds did not introduce regressions.

The Micro Focus Application Automation Tools plugin for the Jenkins continuous integration server provides a mechanism for executing performance tests as part of a build script. This plugin allows you to trigger a Performance Center test as a build step and present the results in the Jenkin's user interface.

You can integrate performance tests which have service level agreements (SLAs). This allows you to quickly determine whether the test passed or failed and if performance was affected.

Back to top

Set up a Jenkins server and install the plugin

  1. Install the Jenkins server.

    For the supported server versions, see the Integration with non-Micro Focus products section of the System Requirements.

  2. Install the Micro Focus Application Automation Tools plugin.

    For details on downloading and installing this plugin, see the Application Automation Tools wiki page.

    Note: The Jenkins plugin requires an administrator account.

Set up a Jenkins job to run tests in Performance Center

  1. Go to the Jenkins Server home page.

  2. Click the New Job link or select an existing job.

  3. Enter a Job name (for a new job).

  4. Select Build a free-style software project and click OK.

  5. In the Project Configuration section scroll down to the Build section.

  6. Perform the following according to the plugin you are using:

    Micro Focus Application Automation Tools

    Expand the Add build step drop-down, and select Execute tests using Performance Center.

    Micro Focus Performance Center integration with Git

    Expand the Add build step drop-down and select Run Performance Test Using Performance Center.

  7. (Optional) Enter a description of the build step.

  8. Enter the hostname or IP address of a Performance Center server.

    Example: If the Performance Center server URL is http://MY_SERVER/loadtest, enter MY_SERVER.

  9. If you are running the Jenkins job over a secured Performance Center server, select the Use HTTPS protocol option.

  10. Enter the server credentials, project, and domain.

  11. Perform the following according to the plugin you are using:

    Micro Focus Application Automation Tools Enter the Test ID. You can get the ID from My Performance Center > Test Management > Test Lab > Performance Test Set view. If the column is not visible, you can select it by clicking the Select Columns button.
    Micro Focus Performance Center integration with Git

    In the Run Test section, you can either select to:

    • Run an existing test. If you run an existing test, you can provide a Test ID. You can get the ID from Performance Center > Test Management > Test Lab > Performance Test Set view. If the column is not visible, you can select it by clicking the Select Columns button.

    • Create a new test. If you create a new test, you can provide in the Test To Create field a text in YAML syntax representing a Performance Center test, or provide a path to a YAML file relative to the workspace. The parameters to be used in each case are different. See Create a Performance Center test from YAML input.

  12. Select an option for adding the Test Instance ID:

    Automatically select existing or create new if none exists (Performance Center 12.55 or later) If you select this option, Performance Center creates a test instance or locates the existing test instance.
    Manual selection

    Enter the Test Instance ID (available from Performance Center > Test Management > Test Lab > Performance Test Set view).

  13. Choose whether to use a Local Proxy.

  14. Choose a Post Run Action (Collate Results, Collate and Analyze, or Do Not Collate).

  15. Select a trend report option:

    Do Not Trend No trend report is created.
    Use trend report associated with the test (Performance Center 12.55 or later)

    If Auto Trending is selected in the Load Test, select this option to automatically publish trend results.

    Add run to trend report with ID If you select this option, enter the trend report ID (supported for version 12.53 or later).
  16. Enter a duration for the Ad-Hoc timeslot. The minimum time is 30 minutes.

  17. Choose whether to use VUDs licenses.

  18. Choose whether to consider the SLA status for determining the build-step status. If you do not enable the Set step status according to SLA option, the build-step will be labeled as Passed as long as no failures occurred.

Back to top

Run the job

Run or schedule the job as you would with any standard Jenkins job.

Back to top

Configure Trending Report Charts on Jenkins

To view Performance Center Trend reports:

  1. Install the plot plugin from https://wiki.jenkins.io/display/JENKINS/Plot+Plugin.

  2. Open your job configuration, and add a new post build action: Plot build data.

  3. Click Add Plot.

  4. Configure the following settings and leave the other settings blank or unselected (see the Data Series files table below for setting details):

    Name Description
    Plot group Enter a meaningful name for the group. For example, Performance Trending.
    Plot title Enter a name that is related to the measurement. For example, Average Transaction Response Time.
    Number of builds to include Enter the number of builds to include. We recommend no more than 10 builds.
    Plot y-axis label Enter the appropriate measurement unit. For example, Seconds. See the recommended unit for each measurement in the table below.
    Plot style Select the plot style. Line or Line 3D are the most suitable for trending.
    Data series file

    Enter one of the measurement types listed in the table below.

    Tip: We recommend using the bolded measurements for trending because they compare like-for-like measurements to provide an indication of the application’s performance and workload.

    Load data from csv file Select this check box.
    Include all columns Make sure this is selected.
    Display original csv above plot Select this check box.
  5. Repeat steps 1-4 to add more plots.

  6. Save the configuration.

Data Series files

Type Data Series File Comment Unit
TRT (Transaction Response Time) pct_minimum_trt.csv Minimum transaction response time Seconds
pct_maximum_trt.csv Maximum transaction response time Seconds
pct_average_trt.csv Average transaction response time Seconds
pct_median_trt.csv Median transaction response time Seconds
pct_percentile_90_trt.csv 90th 90th percentile of transaction response time Seconds
pct_stddeviation_trt.csv Standard deviation transaction response time Seconds
pct_count1_trt.csv Number of occurrences of the transaction Count
TPS (Transaction per seconds) pct_minimum_tps.csv Minimum transaction per second Count
pct_maximum_tps.csv Maximum transactions per second Count
pct_average_tps.csv Average transactions per second Count
pct_median_tps.csv Median transactions per second Count
pct_sum1_tps.csv Total amount of transaction per second for a given transaction Count
TRS (Transaction Summary) pct_count1_trs.csv Total amount of occurrences for a given transaction Count
UDP (User defined data point) pct_minimum_udp.csv Minimum value for a user defined data point Unit
pct_maximum_udp.csv Maximum value for a user defined data point Unit
pct_average_udp.csv Average value for a user defined data point Unit
pct_median_udp.csv Median value for a user defined data point Unit
pct_stddeviation_udp.csv Standard deviation value for user defined data point Unit
pct_count1_udp.csv Number of occurrences for a given user defined data point Count
pct_sum1_udp.csv Sum of the values reported in a given user defined data point Unit
VU (Running Vusers) pct_maximum_vu.csv Maximum number of running Vusers in the scenario Count
pct_average_vu.csv Average number of running Vusers in the scenario Count
WEB pct_minimum_web.csv Minimum value of web statistics (# of connections, throughput, hits per second, etc.) Unit
pct_maximum_web.csv Maximum value of web statistics Unit
pct_average_web.csv Average value of web statistics Unit
pct_median_web.csv Median value of web statistics Unit
pct_sum1_web.csv Total value of web statistics Unit

Note: If you get a file does not exist error (“<file_name.csv> doesn’t match anything”), you can ignore this because the file will be created during the job execution.

Back to top

Configure the Performance Center-Octane integration

You can bring performance test run results into ALM Octane using ALM Octane pipelines, and include them in the overall analysis of your product.

For details on configuring the integration, see Automated testing flow in the Octane Help Center.

Back to top

See also: