Following the article about stages in Azure DevOps in this article we will examine jobs, which are units of tasks grouped together.
In more detail we will check the dependsOn along with the condition keyword in order to create dependencies between various jobs and indicate which should run first and if it will be executed.
Main scenario
We have a stage which contains multiple jobs. This stage could be a larger unit of actions like the deployment to production environment. A procedure like a deployment could be very complex with many different components working together for the outcome. In the stage1 there are 4 jobs with the names job1..4. Job1 needs to run first and the job2 depends on the job1 as a result it needs to wait the execution. Job2 will execute successful or fail based on the input that the user provides. Then job3 and job4 will be executed with a condition. The job3 will be executed if all the previous jobs have succeeded and job4 will be executed if one of the previous jobs had a failure and the pipeline stopped.
Example 1
We execute the pipeline with parameter equal to 1 in order to have the job2 failed. Then we will see that only job4 runs and job3 will be skipped because of the conditions.
Code
trigger:
- none
parameters:
- name: state
displayName: select 1 for failure and 0 for success
type: number
values:
- 0
- 1
pool:
vmImage: ubuntu-latest
stages:
- stage: stage1
displayName: stage1
jobs:
- job: job1
timeoutInMinutes: 60
displayName: job1
steps:
- script: echo running task1
displayName: task1
- job: job2
dependsOn: job1
displayName: job2
continueOnError: true
steps:
- script: exit ${{ parameters.state }}
displayName: task will succeed or fail based on user input
- job: job3
dependsOn: job2
condition: succeeded()
displayName: job3
steps:
- script: echo task to be executed on success
displayName: execute on success
- job: job4
condition: failed()
dependsOn: job2
displayName: job4
steps:
- script: echo task to be executed on failure
displayName: execute on failure
Then we execute the pipeline with parameter equal to 0 in order to have the job2 run. As a result job3 will run and job4 will be skipped.
Example 2
We will now execute the same jobs but we will also use the continueOnError keyword on job2. This will allow subsequent tasks to run and skip the failure of the pipeline. By looking at the execution we will now see that job3 seems to be executed in comparison with the run that did not have the continueOnError. This is done because job2 is handled as partially failed and the next steps will continue. The job4 was skipped because pipeline did not recognize a failure.
If we execute again the pipeline with continueOnError and 0 as the parameter we will get the same result as with run-2.
Microsoft Docs:
https://learn.microsoft.com/en-us/azure/devops/pipelines/process/phases?view=azure-devops&tabs=yaml
Youtube video:
