Cloud-based Apache JMeter Load Test task

Azure DevOps Services

Note

While Azure DevOps cloud-based load testing service is deprecated, Azure Load Testing Preview is available. Azure Load Testing Preview is a fully managed load testing service that enables you to use existing Apache JMeter scripts to generate high-scale load. To learn more, see What is Azure Load Testing Preview?. To learn more about the deprecation of Azure DevOps load testing and other, alternative services see Changes to load test functionality in Visual Studio and cloud load testing in Azure DevOps.

Use this task to run Apache JMeter load tests in the cloud.

Demands

The agent must have the following capability:

  • Azure PowerShell

YAML snippet

# Cloud-based Apache JMeter load test
# Run an Apache JMeter load test in the cloud
- task: ApacheJMeterLoadTest@1
  inputs:
    #connectedServiceName: # Optional
    testDrop: 
    #loadTest: 'jmeter.jmx' 
    #agentCount: '1' # Options: 1, 2, 3, 4, 5
    #runDuration: '60' # Options: 60, 120, 180, 240, 300
    #geoLocation: 'Default' # Optional. Options: default, australia East, australia Southeast, brazil South, central India, central US, east Asia, east US 2, east US, japan East, japan West, north Central US, north Europe, south Central US, south India, southeast Asia, west Europe, west US
    #machineType: '0' # Optional. Options: 0, 2

Arguments

ArgumentDescription
Azure Pipelines Connection(Optional) Select a previously registered service connection to talk to the cloud-based load test service. Choose 'Manage' to register a new connection.
Apache JMeter test files folder(Required) Relative path from repo root where the load test files are available.
Apache JMeter file(Required) The Apache JMeter test filename to be used under the load test folder specified above.
Agent Count(Required) Number of test agents (dual-core) used in the run.
Run Duration (sec)(Required) Load test run duration in seconds.
Run load test using(Optional) undefined

Task control options

Open source

This task is open source on GitHub. Feedback and contributions are welcome.

FAQ