What is GitHub Actions?

GitHub Actions is a built-in tool on GitHub that lets you automatically run tasks (called “workflows”) whenever something happens in your code repository, like when you push new code or open a pull request. It helps you test, build, and deploy software without doing those steps by hand.

Let's break it down

  • GitHub: a website where people store and share code.
  • Actions: small pieces of code that do a specific job, such as running tests or copying files.
  • Workflow: a list of actions that run one after another, triggered by an event.
  • Trigger: the event that starts the workflow, like a code push or a scheduled time.
  • Run automatically: the computer does the work for you, no manual clicks needed.

Why does it matter?

It saves developers time and reduces mistakes by handling repetitive tasks automatically, so they can focus on writing code. It also ensures that every change is checked (tested, built, or deployed) in the same reliable way.

Where is it used?

  • A team runs tests and builds a Docker image every time a developer pushes code, catching bugs early.
  • An open-source project automatically publishes a new release to the package registry when a version tag is created.
  • A company deploys a web app to a cloud service after a pull request is merged, keeping production up-to-date without manual steps.
  • A documentation site is regenerated and published nightly to keep content fresh.

Good things about it

  • Integrated directly into GitHub, no extra services needed.
  • Free tier available for public repositories and generous limits for private ones.
  • Supports many programming languages and can run on Linux, Windows, and macOS runners.
  • Easy to share and reuse community-made actions from the marketplace.
  • Scales automatically; you can run many jobs in parallel.

Not-so-good things

  • Complex workflows can become hard to read and maintain.
  • Limited control over the underlying runner environment compared to self-hosted CI tools.
  • Large or long-running jobs may quickly consume free minutes, leading to extra costs.
  • Debugging failed steps can be tricky without detailed logs or local testing.