Pearson GH-200 New Attempt

The repository_dispatch event allows you to trigger a workflow in response to external activity. It is commonly used when you need to trigger a workflow from outside GitHub, such as from another system or service, by sending a request to the GitHub API. This event provides flexibility to integrate with various external systems and trigger workflows in a GitHub repository.

Job outputs are used to pass data from one job to another in a workflow. A job can produce output values (like variables or files), which can be referenced by subsequent jobs using the needs keyword and ${{ steps.step_id.outputs.output_name }} syntax.

Artifact storage allows data (such as files or results) to be saved by a job and then retrieved by another job in a later step. This is commonly used for passing large amounts of data or files between jobs.

The key is required because it uniquely identifies the cache. It is used to store and retrieve cached data. When creating or restoring a cache, you need to define a key that will be used to identify the cache.

The path is the file path on the runner that you want to cache. This is where the cached files or dependencies are located and should be specified to tell GitHub where to store or retrieve the cache from.

The correct native GitHub Actions method for passing files between jobs in the same workflow is artifact storage. Workflow artifacts are designed to persist files produced by one job so they can be downloaded and used by another job later in the workflow. Job outputs are better suited for passing small values, strings, IDs, flags, or metadata between jobs, not full files. Caching is intended to speed up repeated workflow runs by reusing dependencies or build outputs; it is not the proper mechanism for transferring job-produced files. An external blob store can work architecturally, but it is not the native GitHub Actions method. Therefore, artifact storage is the best and most exam-aligned answer for passing files between jobs.