Hello ! I’m Xavier Jouvenot and in this small post, we are going to see how to configure some optional steps in Azure Pipelines.
Self promotion: You can find other articles on my website 😉
Problematic
When creating a CI/CD pipeline, you may want to trigger some scripts only if some conditions are met. Indeed, depending on the operating system, or on some inputs, you may want to have a pipeline able to adapt itself and run the right scripts to achieve your processes/tests.
I covered the operating system part of it in another blog post, but we are going to dive a little bit deeper in this article.
Solution
In your Azure Pipeline configuration file, there is a very convenient keyword to do just that : condition
. By using this keyword, we will be able to specify… well, some conditions, in which the step, or job targeted will be executed.
For example, if we want a script to only be executed if the operating system is a Mac environnement, the step will look like that:
- script: |
echo "Hello World from OSX"
displayName: OSX Job
condition: and(succeededOrFailed(), eq(variables['Agent.OS'], 'Darwin'))
With eq(variables['Agent.OS'], 'Darwin')
, we check the current operating system, and with succeededOrFailed()
, we make sure that this step
will run even if a previous dependency has failed, unless the run was canceled.
If you want to trigger a step of you pipeline depending on the parameters of a template, for example, you can do it like that
- script: |
echo "Hello World"
displayName: If parameter is release
condition: eq('${{ parameters.configuration }}', 'Release')
With configuration
being one of your parameters. In that case, this job will only be triggered if the configuration
parameter is set to the value Release
.
Finally, let see another use case, where you want a job to be executed or not, depending of the final state of another job:
- job: Bar
dependsOn: Foo
condition: failed()
// Rest of the pipeline
In this example, the job Bar
will only be run if the job Foo
ended up with a failure.
These are some example of the use case I commonly encountered, so I hope that it will help you in your own pipelines. I also encourage you to look into the Azure Pipeline documentation, where you will find a more complete description on all the possibilities available to you 😉
Thank you all for reading this article, And until my next article, have a splendid day 🙂
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