About workflows

About workflows

A workflow is a configurable automated process that will run one or more jobs. Workflows are defined by a YAML file checked in to your repository and will run when triggered by an event in your repository, or they can be triggered manually, or at a defined schedule.

Workflows are defined in the .github/workflows directory in a repository, and a repository can have multiple workflows, each of which can perform a different set of tasks. For example, you can have one workflow to build and test pull requests, another workflow to deploy your application every time a release is created, and still another workflow that adds a label every time someone opens a new issue.

Workflow basics

A workflow must contain the following basic components:

1. One or more events that will trigger the workflow.
2. One or more jobs, each of which will execute on a runner machine and run a series of one or more steps.
3. Each step can either run a script that you define or run an action, which is a reusable extension that can simplify your workflow.

For more information on these basic components, see "Understanding GitHub Actions."

Triggering a workflow

Workflow triggers are events that cause a workflow to run. These events can be:

• Events that occur in your workflow's repository
• Events that occur outside of GitHub Enterprise Server and trigger a repository_dispatch event on GitHub Enterprise Server
• Scheduled times
• Manual

For example, you can configure your workflow to run when a push is made to the default branch of your repository, when a release is created, or when an issue is opened.

For more information, see "Triggering a workflow", and for a full list of events, see "Events that trigger workflows."

Workflow syntax

Workflow are defined using YAML. For the full reference of the YAML syntax for authoring workflows, see "Workflow syntax for GitHub Actions."

Create an example workflow

GitHub Actions uses YAML syntax to define the workflow. Each workflow is stored as a separate YAML file in your code repository, in a directory named .github/workflows.

You can create an example workflow in your repository that automatically triggers a series of commands whenever code is pushed. In this workflow, GitHub Actions checks out the pushed code, installs the bats testing framework, and runs a basic command to output the bats version: bats -v.

1. In your repository, create the .github/workflows/ directory to store your workflow files.

2. In the .github/workflows/ directory, create a new file called learn-github-actions.yml and add the following code.

   YAML

   name: learn-github-actions
   on: [push]
   jobs:
     check-bats-version:
       runs-on: ubuntu-latest
       steps:
         - uses: actions/checkout@v2
         - uses: actions/setup-node@v2
           with:
             node-version: '14'
         - run: npm install -g bats
         - run: bats -v

3. Commit these changes and push them to your GitHub repository.

Your new GitHub Actions workflow file is now installed in your repository and will run automatically each time someone pushes a change to the repository. To see the details about a workflow's execution history, see "Viewing the activity for a workflow run."

Understanding the workflow file

To help you understand how YAML syntax is used to create a workflow file, this section explains each line of the introduction's example:

name: learn-github-actions

on: [push]

jobs:

check-bats-version:

  runs-on: ubuntu-latest

  steps:

    - uses: actions/checkout@v2

    - uses: actions/setup-node@v2
      with:
        node-version: '14'

    - run: npm install -g bats

    - run: bats -v

Visualizing the workflow file

In this diagram, you can see the workflow file you just created and how the GitHub Actions components are organized in a hierarchy. Each step executes a single action or shell script. Steps 1 and 2 run actions, while steps 3 and 4 run shell scripts. To find more prebuilt actions for your workflows, see "Finding and customizing actions."

Viewing the activity for a workflow run

When your workflow is triggered, a workflow run is created that executes the workflow. After a workflow run has started, you can see a visualization graph of the run's progress and view each step's activity on GitHub.

1. On your GitHub Enterprise Server instance, navigate to the main page of the repository.

2. Under your repository name, click Actions.

   

3. In the left sidebar, click the workflow you want to see.

   

4. Under "Workflow runs", click the name of the run you want to see.

   

5. Under Jobs or in the visualization graph, click the job you want to see.

   

6. View the results of each step.

   

For more on managing workflow runs, such as re-running, cancelling, or deleting a workflow run, see "Managing workflow runs."

Using starter workflows

GitHub provides preconfigured starter workflows that you can customize to create your own continuous integration workflow. GitHub Enterprise Server analyzes your code and shows you CI starter workflows that might be useful for your repository. For example, if your repository contains Node.js code, you'll see suggestions for Node.js projects. You can use starter workflows as a starting place to build your custom workflow or use them as-is.

You can browse the full list of starter workflows in the actions/starter-workflows repository on your GitHub Enterprise Server instance.

For more information on using and creating starter workflows, see "Using starter workflows" and "Creating starter workflows for your organization."

Advanced workflow features

This section briefly describes some of the advanced features of GitHub Actions that help you create more complex workflows.

Storing secrets

If your workflows use sensitive data, such as passwords or certificates, you can save these in GitHub as secrets and then use them in your workflows as environment variables. This means that you will be able to create and share workflows without having to embed sensitive values directly in the workflow's YAML source.

This example job demonstrates how to reference an existing secret as an environment variable, and send it as a parameter to an example command.

jobs:
  example-job:
    runs-on: ubuntu-latest
    steps:
      - name: Retrieve secret
        env:
          super_secret: ${{ secrets.SUPERSECRET }}
        run: |
          example-command "$super_secret"

For more information, see "Encrypted secrets."

Creating dependent jobs

By default, the jobs in your workflow all run in parallel at the same time. If you have a job that must only run after another job has completed, you can use the needs keyword to create this dependency. If one of the jobs fails, all dependent jobs are skipped; however, if you need the jobs to continue, you can define this using the if conditional statement.

In this example, the setup, build, and test jobs run in series, with build and test being dependent on the successful completion of the job that precedes them:

jobs:
  setup:
    runs-on: ubuntu-latest
    steps:
      - run: ./setup_server.sh
  build:
    needs: setup
    runs-on: ubuntu-latest
    steps:
      - run: ./build_server.sh
  test:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - run: ./test_server.sh

For more information, see "Defining prerequisite jobs."

Using a matrix

A matrix strategy lets you use variables in a single job definition to automatically create multiple job runs that are based on the combinations of the variables. For example, you can use a matrix strategy to test your code in multiple versions of a language or on multiple operating systems. The matrix is created using the strategy keyword, which receives the build options as an array. For example, this matrix will run the job multiple times, using different versions of Node.js:

jobs:
  build:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        node: [12, 14, 16]
    steps:
      - uses: actions/setup-node@v2
        with:
          node-version: ${{ matrix.node }}

For more information, see "Using a matrix for your jobs."

Using databases and service containers

If your job requires a database or cache service, you can use the services keyword to create an ephemeral container to host the service; the resulting container is then available to all steps in that job and is removed when the job has completed. This example demonstrates how a job can use services to create a postgres container, and then use node to connect to the service.

jobs:
  container-job:
    runs-on: ubuntu-latest
    container: node:10.18-jessie
    services:
      postgres:
        image: postgres
    steps:
      - name: Check out repository code
        uses: actions/checkout@v2
      - name: Install dependencies
        run: npm ci
      - name: Connect to PostgreSQL
        run: node client.js
        env:
          POSTGRES_HOST: postgres
          POSTGRES_PORT: 5432

For more information, see "Using containerized services."

Using labels to route workflows

If you want to be sure that a particular type of runner will process your job, you can use labels to control where jobs are executed. You can assign labels to a self-hosted runner in addition to their default label of self-hosted. Then, you can refer to these labels in your YAML workflow, ensuring that the job is routed in a predictable way. GitHub-hosted runners have predefined labels assigned.

This example shows how a workflow can use labels to specify the required runner:

jobs:
  example-job:
    runs-on: [self-hosted, linux, x64, gpu]

A workflow will only run on a runner that has all the labels in the runs-on array. The job will preferentially go to an idle self-hosted runner with the specified labels.

To learn more about self-hosted runner labels, see "Using labels with self-hosted runners."

Using environments

You can configure environments with protection rules and secrets to control the execution of jobs in a workflow. Each job in a workflow can reference a single environment. Any protection rules configured for the environment must pass before a job referencing the environment is sent to a runner. For more information, see "Using environments for deployment."