GitHub Actions: Sharing Data Between Jobs in a Workflow

GitHub Actions: Sharing Data Between Jobs in a Workflow

Welcome back, GitHub fans! We continue our exploration into GitHub Actions, this time focusing on how to share data between jobs in a workflow. This is a critical concept to master when orchestrating complex workflows where the output of one job is required as an input to another.

Understanding the Challenge

By design, each job in a GitHub Actions workflow runs in a fresh instance of the virtual environment. Therefore, data isn’t persistently stored across jobs, ensuring that each job is isolated and independent. But what if you need to share data, such as a file or an environment variable, across jobs?

Using Artifacts to Share Data

To share data between jobs, we can use artifacts. Artifacts allow you to persist data after a job has completed, allowing it to be used in other jobs later in the workflow.

An artifact is simply a file (or a collection of files) that is associated with a workflow run. These can be log files, test result files, build outputs, or any other files you want to retain.

To use artifacts, we need two GitHub Actions:

  1. actions/upload-artifact: To upload artifacts.
  2. actions/download-artifact: To download artifacts.

Uploading Artifacts

Let’s look at a job that creates an artifact:

In this example, we first create a file named my_file.txt. We then use the upload-artifact action to upload this file as an artifact named my-artifact.

Downloading Artifacts

Once the artifact has been uploaded, it can be downloaded in a subsequent job:

In the use_artifact job, we first download the artifact using the download-artifact action. We then display the content of the file using the cat command.

Note: The needs keyword indicates that the use_artifact job depends on the completion of the build job. This ensures that the artifact is available before we attempt to download it.


Sharing data between jobs in a GitHub Actions workflow is a bit tricky due to the isolated nature of jobs, but artifacts provide a simple and efficient way to overcome this limitation. By mastering the use of artifacts, you can create complex workflows with dependencies between jobs.

Stay tuned for more insights into mastering GitHub Actions. Happy coding!