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Docker Essentials: Containers and Artifact Registry

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Docker Essentials: Containers and Artifact Registry

Lab 30 Minuten universal_currency_alt 1 Guthabenpunkt show_chart Einsteiger
info Dieses Lab kann KI-Tools enthalten, die den Lernprozess unterstützen.
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gem-docker-basics

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Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

  1. Click Activate Cloud Shell Activate Cloud Shell icon at the top of the Google Cloud console.

When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. The output contains a line that declares the PROJECT_ID for this session:

Your Cloud Platform project in this session is set to YOUR_PROJECT_ID

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

  1. (Optional) You can list the active account name with this command:
gcloud auth list
  1. Click Authorize.

  2. Your output should now look like this:

Output:

ACTIVE: * ACCOUNT: student-01-xxxxxxxxxxxx@qwiklabs.net To set the active account, run: $ gcloud config set account `ACCOUNT`
  1. (Optional) You can list the project ID with this command:
gcloud config list project

Output:

[core] project = <project_ID>

Example output:

[core] project = qwiklabs-gcp-44776a13dea667a6 Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Overview

This lab provides a hands-on introduction to essential Docker operations, including building, running, managing, and publishing Docker containers. You will learn how to containerize a simple application, interact with the container, and push the resulting image to Google Artifact Registry. This lab assumes familiarity with basic Linux commands and Docker concepts.

Task 1. Setting up your environment and Artifact Registry

In this task, you'll configure your environment, enable the necessary services, and create an Artifact Registry repository to store your Docker images.

  1. Set your Project ID:
gcloud config set project {{{ project_0.project_id | "PROJECT_ID" }}} Note:
This configures the gcloud CLI to use your project.
  1. Enable Artifact Registry API
gcloud services enable artifactregistry.googleapis.com Note:
This command enables the Artifact Registry API for your project, allowing you to create and manage repositories.
  1. Create an Artifact Registry Repository in region:
gcloud artifacts repositories create my-docker-repo \ --repository-format=docker \ --location={{{ project_0.default_region | "REGION" }}} \ --description="My Docker image repository" Note:
Creates a Docker repository in Artifact Registry named `my-docker-repo`.
  1. Configure Docker to authenticate with Artifact Registry:
gcloud auth configure-docker {{{ project_0.default_region | "REGION" }}}-docker.pkg.dev Note:
Authenticates Docker with Artifact Registry for the specified region. This allows you to push and pull images.

Task 2. Building a Docker Image

Here, you will create a simple 'Hello World' application and build a Docker image for it using a Dockerfile.

  1. Create a directory for your application:
mkdir myapp && cd $_ Note:
Creates a new directory named `myapp` and navigates into it.
  1. Create a simple app.py file:
cat > app.py <<EOF from flask import Flask app = Flask(__name__) @app.route("/") def hello(): return "Hello, Docker!\n" if __name__ == "__main__": app.run(debug=True, host='0.0.0.0', port=8080) EOF Note:
Creates a simple Flask application that returns 'Hello, Docker!'. This will be our application.
  1. Create a requirements.txt file:
cat > requirements.txt <<EOF Flask EOF Note:
Specifies the dependencies for your application (Flask).
  1. Create a Dockerfile:
FROM python:3.9-slim-buster WORKDIR /app COPY requirements.txt . RUN pip install --no-cache-dir -r requirements.txt COPY . . EXPOSE 8080 CMD ["python", "app.py"] Note:
Defines the steps to build your Docker image. It uses a Python base image, installs dependencies, copies the application code, and specifies the command to run the application.
  1. Build the Docker image. Replace and
docker build -t {{{ project_0.default_region | "REGION" }}}-docker.pkg.dev/{{{ project_0.project_id | "PROJECT_ID" }}}/my-docker-repo/hello-docker:latest . Note:
Builds the Docker image using the `Dockerfile` in the current directory. It tags the image with the Artifact Registry repository URL.

Task 3. Running and Testing the Docker Container

In this task, you will run the Docker image you built and test it to ensure it's working correctly.

  1. Run the Docker container:
docker run -d -p 8080:8080 {{{ project_0.default_region | "REGION" }}}-docker.pkg.dev/{{{ project_0.project_id | "PROJECT_ID" }}}/my-docker-repo/hello-docker:latest Note:
Runs the Docker image in detached mode (`-d`) and maps port 8080 on the host to port 8080 in the container. You may need to configure firewall rules to allow external traffic on port 8080.
  1. Check if the container is running:
docker ps Note:
Lists the currently running Docker containers.
  1. Test the application. Replace
curl http://localhost:8080 Note:
Sends an HTTP request to the application running in the container. You should see 'Hello, Docker!' in the output.
  1. Stop the Docker container:
docker stop $(docker ps -q) Note:
Stops all running Docker containers. `docker ps -q` returns only the container IDs.

Task 4. Pushing the Image to Artifact Registry

Now that you have a working image, you will push it to your Artifact Registry repository.

  1. Push the Docker image. Replace and
docker push {{{ project_0.default_region | "REGION" }}}-docker.pkg.dev/{{{ project_0.project_id | "PROJECT_ID" }}}/my-docker-repo/hello-docker:latest Note:
Pushes the Docker image to the Artifact Registry repository. This makes the image available for others to use.

Task 5. Cleaning Up

Remove local artifacts to ensure a clean environment.

  1. Remove the application directory:
cd .. && rm -rf myapp Note:
Removes the `myapp` directory and all its contents.

Congratulations!

Congratulations! You have successfully built, run, and pushed a Docker image to Artifact Registry. You learned the basic Docker operations necessary for developing and deploying containerized applications. This lab provides a foundation for more advanced Docker concepts and workflows.

Additional Resources

Manual Last Updated Jun 24, 2025

Lab Last Tested Jun 24, 2025

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