GH-200 Exam Dumps - Microsoft GitHub Administrator Questions and Answers

GitHub-hosted runners automatically handle patching, meaning they will be kept up to date with the latest security updates and software patches for both the runner environment and the underlying operating system.

GitHub-hosted runners support Linux, Windows, and macOS, giving you flexibility to run workflows on different operating systems without needing to manage your own self-hosted runners.

Deleting artifacts from repositories manually will free up storage space. Artifacts are typically stored for a limited time by default, but manual cleanup can help manage space.

Configuring the artifact and log retention period allows you to control how long artifacts and logs are retained in your repository. By shortening the retention period, you can prevent unnecessary accumulation of data and manage storage more effectively.

Actions stored in private repositories within the organization can be reused across all repositories by referencing them in workflows. This ensures a centralized way of maintaining custom actions.

Encrypted secrets can be accessed across repositories in the same organization, making it easy to store sensitive data (like API keys or tokens) securely while allowing multiple workflows to access them.

Workflow templates allow you to create reusable templates for workflows that can be shared across repositories within the organization. This makes it easier to standardize processes and automate them across multiple projects.

GitHub Actions supports the use of service containers, which allows you to spin up a PostgreSQL database (or any other service) in a Docker container during your workflow. You can pull a PostgreSQL image from Docker Hub, and the container will automatically be available to your workflow job. This method requires no additional infrastructure and is easy to configure and maintain, as you simply define the container in the workflow file.

A Docker container action is ideal for custom actions that require specific environments or dependencies, such as Python. By creating a Docker container, you can define the environment with the necessary Python version and dependencies, and your Python code can run inside that container.

The smallest scope for an environment variable is within a step. Environment variables defined within a step are only accessible to that particular step, which makes it the smallest scope for a variable in a GitHub Actions workflow.

The action.yml file is the metadata file in a custom GitHub Action that defines the main entry point, including information such as the inputs, outputs, description, and the runs key that specifies the main entry point (e.g., a script or a Docker container).

You can define environment variables for the entire workflow by using the env key at the top level of the workflow file. These environment variables will be available to all jobs and steps within the workflow.

Environment variables can also be set within the run attribute of a job step, and these variables will be scoped only to that specific step.

You can set environment variables for specific steps within a job by using jobs..steps[*].env, which allows you to define variables that will only be available to that step.

Dockerfile: The Dockerfile is required for Docker container actions. It defines the environment for the action, specifying the base image, dependencies, and any commands to set up the action’s runtime inside the container.

action.yml: The action.yml file is required for all GitHub Actions, including Docker container actions. It contains metadata about the action, including the inputs, outputs, and the runtime environment (which in this case is Docker, defined under runs.using).

A. Use the actions/setup-docker action

B. Authenticate to the GitHub Container Registry.

C. Build the container image.

D. Push the image to the GitHub Container Registry

E. Pull the image from the GitHub Container Registry.