https://faun.pub/reduce-your-build-time-using-caching-in-azure-pipelines-7a7bd0201cee
Resources
Trigger
Pipeline -> Stage(Implicit) -> Jobs -> Steps [Task, Script, Checkout]
jobs:
- job: Job_1
displayName: Agent job 1
pool:
vmImage: ubuntu-latest
steps:
-script: echo "Hello World"
pool:
name: Default
demands: SpecialSoftware # Check if SpecialSoftware capability exists
stages:
- stage: A
jobs:
- job: A1
- job: A2
- stage: B
jobs:
- job: B1
- job: B2
stages:
- stage: A
# stage B runs if A fails
- stage: B
condition: failed()
# stage C runs if B succeeds
- stage: C
dependsOn:
- A
- B
condition: succeeded('B')
If you choose to specify a pool at the stage level, then all jobs defined in that stage will use that pool unless otherwise specified at the job-level.
stages:
- stage: A
pool: StageAPool
jobs:
- job: A1 # will run on "StageAPool" pool based on the pool defined on the stage
- job: A2 # will run on "JobPool" pool
pool: JobPool
jobs:
- job: Foo
steps:
- script: echo Hello!
condition: always() # this step will always run, even if the pipeline is canceled
- job: Bar
dependsOn: Foo
condition: failed() # this job will only run if Foo fails
jobs:
- job: Debug
steps:
- script: echo hello from the Debug build
- job: Release
dependsOn: Debug
steps:
- script: echo hello from the Release build
You can organize pipeline jobs into stages. Stages are the major divisions in a pipeline: "build this app", "run these tests", and "deploy to pre-production" are good examples of stages. They are logical boundaries in your pipeline where you can pause the pipeline and perform various checks.
Pipeline > Stages >Stage>Steps>Step
jobs:
- job: A
steps:
- bash: echo "A"
- job: B
steps:
- bash: echo "B"
If you organize your pipeline into multiple stages, you use the stages keyword.
If you choose to specify a pool at the stage level, then all jobs defined in that stage will use that pool unless otherwise specified at the job-level
stages:
- stage: A
jobs:
- job: A1
- job: A2
- stage: B
jobs:
- job: B1
- job: B2
When you define multiple stages in a pipeline, by default, they run sequentially in the order in which you define them in the YAML file. The exception to this is when you add dependencies. With dependencies, stages run in the order of the dependsOn requirements
stages:
- stage: string
dependsOn: string
condition: string
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You can organize your pipeline into jobs. Every pipeline has at least one job. A job is a series of steps that run sequentially as a unit. In other words, a job is the smallest unit of work that can be scheduled to run.
In the simplest case, a pipeline has a single job. In that case, you do not have to explicitly use the job keyword
jobs:
- job: myJob
timeoutInMinutes: 10
pool:
vmImage: 'ubuntu-16.04'
steps:
- bash: echo "Hello world"
/usr/lib/jvm/adoptopenjdk-11-hotspot-amd64
# update-alternatives --config java
update-alternatives --list java
echo ls /etc/alternatives
ls /etc/alternatives
