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migrating-from-azure-pipelines-to-github-actions.md

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title intro redirect_from versions type topics shortTitle
Migrating from Azure Pipelines to GitHub Actions
{% data variables.product.prodname_actions %} and Azure Pipelines share several configuration similarities, which makes migrating to {% data variables.product.prodname_actions %} relatively straightforward.
/actions/learn-github-actions/migrating-from-azure-pipelines-to-github-actions
/actions/migrating-to-github-actions/migrating-from-azure-pipelines-to-github-actions
/actions/migrating-to-github-actions/manual-migrations/migrating-from-azure-pipelines-to-github-actions
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Migrate from Azure Pipelines

{% data reusables.actions.enterprise-github-hosted-runners %}

Introduction

Azure Pipelines and {% data variables.product.prodname_actions %} both allow you to create workflows that automatically build, test, publish, release, and deploy code. Azure Pipelines and {% data variables.product.prodname_actions %} share some similarities in workflow configuration:

  • Workflow configuration files are written in YAML and are stored in the code's repository.
  • Workflows include one or more jobs.
  • Jobs include one or more steps or individual commands.
  • Steps or tasks can be reused and shared with the community.

For more information, see "AUTOTITLE."

Key differences

When migrating from Azure Pipelines, consider the following differences:

  • Azure Pipelines supports a legacy classic editor, which lets you define your CI configuration in a GUI editor instead of creating the pipeline definition in a YAML file. {% data variables.product.prodname_actions %} uses YAML files to define workflows and does not support a graphical editor.
  • Azure Pipelines allows you to omit some structure in job definitions. For example, if you only have a single job, you don't need to define the job and only need to define its steps. {% data variables.product.prodname_actions %} requires explicit configuration, and YAML structure cannot be omitted.
  • Azure Pipelines supports stages defined in the YAML file, which can be used to create deployment workflows. {% data variables.product.prodname_actions %} requires you to separate stages into separate YAML workflow files.
  • On-premises Azure Pipelines build agents can be selected with capabilities. {% data variables.product.prodname_actions %} self-hosted runners can be selected with labels.

Migrating jobs and steps

Jobs and steps in Azure Pipelines are very similar to jobs and steps in {% data variables.product.prodname_actions %}. In both systems, jobs have the following characteristics:

  • Jobs contain a series of steps that run sequentially.
  • Jobs run on separate virtual machines or in separate containers.
  • Jobs run in parallel by default, but can be configured to run sequentially.

Migrating script steps

You can run a script or a shell command as a step in a workflow. In Azure Pipelines, script steps can be specified using the script key, or with the bash, powershell, or pwsh keys. Scripts can also be specified as an input to the Bash task or the PowerShell task.

In {% data variables.product.prodname_actions %}, all scripts are specified using the run key. To select a particular shell, you can specify the shell key when providing the script. For more information, see "AUTOTITLE."

Below is an example of the syntax for each system.

Azure Pipelines syntax for script steps

{% raw %}

jobs:
  - job: scripts
    pool:
      vmImage: 'windows-latest'
    steps:
      - script: echo "This step runs in the default shell"
      - bash: echo "This step runs in bash"
      - pwsh: Write-Host "This step runs in PowerShell Core"
      - task: PowerShell@2
        inputs:
          script: Write-Host "This step runs in PowerShell"

{% endraw %}

{% data variables.product.prodname_actions %} syntax for script steps

{% raw %}

jobs:
  scripts:
    runs-on: windows-latest
    steps:
      - run: echo "This step runs in the default shell"
      - run: echo "This step runs in bash"
        shell: bash
      - run: Write-Host "This step runs in PowerShell Core"
        shell: pwsh
      - run: Write-Host "This step runs in PowerShell"
        shell: powershell

{% endraw %}

Differences in script error handling

In Azure Pipelines, scripts can be configured to error if any output is sent to stderr. {% data variables.product.prodname_actions %} does not support this configuration.

{% data variables.product.prodname_actions %} configures shells to "fail fast" whenever possible, which stops the script immediately if one of the commands in a script exits with an error code. In contrast, Azure Pipelines requires explicit configuration to exit immediately on an error. For more information, see "AUTOTITLE."

Differences in the default shell on Windows

In Azure Pipelines, the default shell for scripts on Windows platforms is the Command shell (cmd.exe). In {% data variables.product.prodname_actions %}, the default shell for scripts on Windows platforms is PowerShell. PowerShell has several differences in built-in commands, variable expansion, and flow control.

If you're running a simple command, you might be able to run a Command shell script in PowerShell without any changes. But in most cases, you will either need to update your script with PowerShell syntax or instruct {% data variables.product.prodname_actions %} to run the script with the Command shell instead of PowerShell. You can do this by specifying shell as cmd.

Below is an example of the syntax for each system.

Azure Pipelines syntax using CMD by default

{% raw %}

jobs:
  - job: run_command
    pool:
      vmImage: 'windows-latest'
    steps:
      - script: echo "This step runs in CMD on Windows by default"

{% endraw %}

{% data variables.product.prodname_actions %} syntax for specifying CMD

{% raw %}

jobs:
  run_command:
    runs-on: windows-latest
    steps:
      - run: echo "This step runs in PowerShell on Windows by default"
      - run: echo "This step runs in CMD on Windows explicitly"
        shell: cmd

{% endraw %}

For more information, see "AUTOTITLE."

Migrating conditionals and expression syntax

Azure Pipelines and {% data variables.product.prodname_actions %} can both run steps conditionally. In Azure Pipelines, conditional expressions are specified using the condition key. In {% data variables.product.prodname_actions %}, conditional expressions are specified using the if key.

Azure Pipelines uses functions within expressions to execute steps conditionally. In contrast, {% data variables.product.prodname_actions %} uses an infix notation. For example, you must replace the eq function in Azure Pipelines with the == operator in {% data variables.product.prodname_actions %}.

Below is an example of the syntax for each system.

Azure Pipelines syntax for conditional expressions

{% raw %}

jobs:
  - job: conditional
    pool:
      vmImage: 'ubuntu-latest'
    steps:
      - script: echo "This step runs with str equals 'ABC' and num equals 123"
        condition: and(eq(variables.str, 'ABC'), eq(variables.num, 123))

{% endraw %}

{% data variables.product.prodname_actions %} syntax for conditional expressions

{% raw %}

jobs:
  conditional:
    runs-on: ubuntu-latest
    steps:
      - run: echo "This step runs with str equals 'ABC' and num equals 123"
        if: ${{ env.str == 'ABC' && env.num == 123 }}

{% endraw %}

For more information, see "AUTOTITLE."

Dependencies between jobs

Both Azure Pipelines and {% data variables.product.prodname_actions %} allow you to set dependencies for a job. In both systems, jobs run in parallel by default, but job dependencies can be specified explicitly. In Azure Pipelines, this is done with the dependsOn key. In {% data variables.product.prodname_actions %}, this is done with the needs key.

Below is an example of the syntax for each system. The workflows start a first job named initial, and when that job completes, two jobs named fanout1 and fanout2 will run. Finally, when those jobs complete, the job fanin will run.

Azure Pipelines syntax for dependencies between jobs

{% raw %}

jobs:
  - job: initial
    pool:
      vmImage: 'ubuntu-latest'
    steps:
      - script: echo "This job will be run first."
  - job: fanout1
    pool:
      vmImage: 'ubuntu-latest'
    dependsOn: initial
    steps:
      - script: echo "This job will run after the initial job, in parallel with fanout2."
  - job: fanout2
    pool:
      vmImage: 'ubuntu-latest'
    dependsOn: initial
    steps:
      - script: echo "This job will run after the initial job, in parallel with fanout1."
  - job: fanin:
    pool:
      vmImage: 'ubuntu-latest'
    dependsOn: [fanout1, fanout2]
    steps:
      - script: echo "This job will run after fanout1 and fanout2 have finished."

{% endraw %}

{% data variables.product.prodname_actions %} syntax for dependencies between jobs

{% raw %}

jobs:
  initial:
    runs-on: ubuntu-latest
    steps:
      - run: echo "This job will be run first."
  fanout1:
    runs-on: ubuntu-latest
    needs: initial
    steps:
      - run: echo "This job will run after the initial job, in parallel with fanout2."
  fanout2:
    runs-on: ubuntu-latest
    needs: initial
    steps:
      - run: echo "This job will run after the initial job, in parallel with fanout1."
  fanin:
    runs-on: ubuntu-latest
    needs: [fanout1, fanout2]
    steps:
      - run: echo "This job will run after fanout1 and fanout2 have finished."

{% endraw %}

For more information, see "AUTOTITLE."

Migrating tasks to actions

Azure Pipelines uses tasks, which are application components that can be re-used in multiple workflows. {% data variables.product.prodname_actions %} uses actions, which can be used to perform tasks and customize your workflow. In both systems, you can specify the name of the task or action to run, along with any required inputs as key/value pairs.

Below is an example of the syntax for each system.

Azure Pipelines syntax for tasks

{% raw %}

jobs:
  - job: run_python
    pool:
      vmImage: 'ubuntu-latest'
    steps:
      - task: UsePythonVersion@0
        inputs:
          versionSpec: '3.7'
          architecture: 'x64'
      - script: python script.py

{% endraw %}

{% data variables.product.prodname_actions %} syntax for actions

jobs:
  run_python:
    runs-on: ubuntu-latest
    steps:
      - uses: {% data reusables.actions.action-setup-python %}
        with:
          python-version: '3.7'
          architecture: 'x64'
      - run: python script.py

You can find actions that you can use in your workflow in {% data variables.product.prodname_marketplace %}, or you can create your own actions. For more information, see "AUTOTITLE."