crowd.yml

---
settings:
  artifacts-dir: results/crowd/%Y-%m-%d_%H-%M-%S
  aggregator: consolidator
  verbose: false
  env:
    application_hostname: test_crowd_instance.atlassian.com    # Crowd DC hostname without protocol and port e.g. test-crowd.atlassian.com or localhost
    application_protocol: http      # http or https
    application_port: 80            # 80, 443, 8080, 4990, etc
    secure: True                    # Set False to allow insecure connections, e.g. when using self-signed SSL certificate
    application_postfix:            # e.g. /crowd in case of url like http://localhost:4990/crowd
    admin_login: admin
    admin_password: admin
    application_name: crowd
    application_password: 1111
    load_executor: jmeter            
    concurrency: 1000               # number of concurrent threads to authenticate random users
    test_duration: 45m

    # 1 node scenario parameters
    ramp-up: 20s                    # time to spin all concurrent threads
    total_actions_per_hour: 180000  # number of total JMeter actions per hour

    # 2 nodes scenario parameters
    # ramp-up: 10s                    # time to spin all concurrent threads
    # total_actions_per_hour: 360000  # number of total JMeter actions per hour

    # 4 nodes scenario parameters
    # ramp-up: 5s                     # time to spin all concurrent threads
    # total_actions_per_hour: 720000  # number of total JMeter actions per hour

    JMETER_VERSION: 5.2.1
    LANGUAGE: en_US.utf8
    allow_analytics: Yes            # Allow sending basic run analytics to Atlassian. These analytics help us to understand how the tool is being used and help us to continue to invest in this tooling. For more details please see our README.
services:
  - module: shellexec
    prepare:
      - python util/pre_run/environment_checker.py
      - python util/pre_run/check_for_updates.py
      - python util/data_preparation/crowd_prepare_data.py
      - python util/data_preparation/crowd_sync_check.py
    shutdown:
      - python util/post_run/jmeter_post_check.py
      - python util/jtl_convertor/jtls-to-csv.py kpi.jtl
    post-process:
      - python util/analytics/analytics.py crowd
      - python util/post_run/cleanup_results_dir.py
execution:
  - scenario: ${load_executor}
    executor: ${load_executor}
    concurrency: ${concurrency}
    hold-for: ${test_duration}
    ramp-up: ${ramp-up}
scenarios:
  jmeter:
    script: jmeter/crowd.jmx
    properties:
      application_hostname: ${application_hostname}
      application_protocol: ${application_protocol}
      application_port: ${application_port}
      application_postfix: ${application_postfix}
      application_name: ${application_name}
      application_password: ${application_password}
      # Workload model
      total_actions_per_hr: ${total_actions_per_hour}
modules:
  consolidator:
    rtimes-len: 0 # CONFSRVDEV-7631 reduce sampling
    percentiles: [] # CONFSRVDEV-7631 disable all percentiles due to Taurus's excessive memory usage
  jmeter:
    version: ${JMETER_VERSION}
    detect-plugins: true
    memory-xmx: 8G  # allow JMeter to use up to 8G of memory
    plugins:
      - bzm-parallel=0.4
      - bzm-random-csv=0.6
      - jpgc-casutg=2.5
      - jpgc-dummy=0.2
      - jpgc-ffw=2.0
      - jpgc-fifo=0.2
      - jpgc-functions=2.1
      - jpgc-json=2.6
      - jpgc-perfmon=2.1
      - jpgc-prmctl=0.4
      - jpgc-tst=2.4
      - jpgc-wsc=0.3
      - tilln-sshmon=1.0
      - jpgc-synthesis=2.2
    system-properties:
      server.rmi.ssl.disable: true
      java.rmi.server.hostname: localhost
      httpsampler.ignore_failed_embedded_resources: "true"
reporting:
- data-source: sample-labels
  module: junit-xml