**Course Title:** Continuous Integration and Continuous Deployment (CI/CD) **Section Title:** Containerization and Orchestration **Topic:** Dockerize a sample application and integrate it into the CI/CD pipeline.(Lab topic) **Overview:** In this lab, you'll learn how to containerize a sample application using Docker and integrate it into your CI/CD pipeline. You'll explore the benefits of using Docker in the CI/CD process and gain hands-on experience with Dockerizing an application, creating a Docker image, and deploying it to a container. **Prerequisites:** * Familiarity with Docker and containerization concepts (covered in previous topics) * Basic knowledge of a programming language (e.g., Python, Node.js) * Familiarity with a CI/CD tool (e.g., Jenkins, GitHub Actions) **Lab Objectives:** 1. Create a Dockerfile for a sample application 2. Build a Docker image for the application 3. Create a Docker container for the application 4. Integrate the Dockerized application into a CI/CD pipeline 5. Deploy the application to a container using a CI/CD tool **Step 1: Create a Dockerfile for the Sample Application** A Dockerfile is a text file that contains instructions for building a Docker image. For this lab, we'll use a simple Python application as our sample application. Create a new directory for your project and add a file named `Dockerfile`. Open the `Dockerfile` and add the following contents: ```dockerfile FROM python:3.9-slim # Set the working directory to /app WORKDIR /app # Copy the requirements file COPY requirements.txt . # Install the dependencies RUN pip install -r requirements.txt # Copy the application code COPY . . # Expose the port EXPOSE 8000 # Run the command to start the application CMD ["python", "app.py"] ``` This Dockerfile uses the official Python 3.9 image, sets the working directory to `/app`, copies the `requirements.txt` file, installs the dependencies, copies the application code, exposes port 8000, and runs the command to start the application. **Step 2: Build the Docker Image** Run the following command to build the Docker image: ```bash docker build -t my-python-app . ``` This command builds the Docker image using the instructions in the `Dockerfile`. The `-t` option specifies the name of the image. **Step 3: Create a Docker Container for the Application** Run the following command to create a Docker container for the application: ```bash docker run -p 8000:8000 my-python-app ``` This command creates a new container from the `my-python-app` image and maps port 8000 on the host machine to port 8000 in the container. **Step 4: Integrate the Dockerized Application into a CI/CD Pipeline** For this lab, we'll use GitHub Actions as our CI/CD tool. Create a new file named `.github/workflows/docker.yml` and add the following contents: ```yml name: Docker on: push: branches: - main jobs: build-and-deploy: runs-on: ubuntu-latest steps: - name: Checkout code uses: actions/checkout@v2 - name: Login to Docker Hub uses: docker/login-action@v1 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - name: Build and push image run: | docker build -t my-python-app . docker tag my-python-app ${{ secrets.DOCKER_USERNAME }}/my-python-app docker push ${{ secrets.DOCKER_USERNAME }}/my-python-app - name: Deploy to Docker container run: | docker run -p 8000:8000 ${{ secrets.DOCKER_USERNAME }}/my-python-app ``` This workflow file uses the `docker/login-action` to log in to Docker Hub, builds and pushes the Docker image, and deploys the application to a Docker container. **Conclusion:** In this lab, you learned how to containerize a sample application using Docker and integrate it into a CI/CD pipeline using GitHub Actions. You created a Dockerfile, built a Docker image, created a Docker container, and deployed the application to a container using a CI/CD tool. **External Resources:** * Docker Documentation: <https://docs.docker.com/> * Docker Hub: <https://hub.docker.com/> * GitHub Actions Documentation: <https://docs.github.com/en/actions> **What's Next:** In the next topic, we'll cover the importance of monitoring in CI/CD. You'll learn about the key metrics to monitor, how to set up monitoring tools, and how to use monitoring data to improve your CI/CD pipeline. **Leave a Comment or Ask for Help:** If you have any questions or need help with this lab, please leave a comment below.