Docker Project for DevOps Engineers

DockerFile

• A Dockerfile is a text file used to define the instructions for building a Docker image. It provides a set of steps that Docker follows to create an image, which can then be used to run containers.

• In a Dockerfile, you specify the base image, add additional dependencies and files, set environment variables, and define the commands to run when starting a container from the image. The Dockerfile acts as a recipe for building a Docker image with all the necessary components and configurations.

Here are some key reasons to use Dockerfiles:

1. Reproducibility and Consistency: Dockerfiles ensure reproducibility by capturing the exact steps and configurations needed to build an image by defining the precise versions of software packages, libraries, and dependencies required by your application.

2. Automation: Dockerfiles allow for automated image builds. By defining the build steps in a Dockerfile, you can automate the image creation process, reducing manual effort and the risk of human error.

3. Customization and Configuration: Dockerfiles provide flexibility in configuring the application environment. You can define specific settings, environment variables, and file placements within the image.

4. Scalability and Deployment: Dockerfiles facilitate the scaling and deployment of containerized applications. By defining the build process in a Dockerfile, you can easily create multiple instances of the same image, allowing for horizontal scaling of your application.

Task: Deploying Projects

Project 1: React_Django_App

React Django Application Repository

1. Cloning the react django application from git and removing the existing Dockerfile.

    mkdir proj1
    cd proj1
    git clone https://github.com/Abhisek773/react_django_demo_app.git
    cd react_django_demo_app
    rm Dockerfile
   

   

2. Create a new Dockerfile to write the set of instructions for execution

    vim Dockerfile
   
    # Dockerfile contains
    FROM python:3.9
    COPY . .
    RUN pip install -r requirements.txt 
    EXPOSE 8001
    CMD ["python","manage.py","runserver","0.0.0.0:8001"]
   
    # RUN is intermediate steps executed for creating an image to but CMD is entry point inside in your image 
   
    # NOTE
    # To optimise and small the docker image we use python:3.9-alpine
   

   

3. Now we have to build the application by providing the image & tag name

    docker build . -t react_django_app:latest
    # -t is used for tagging 
    # we use . as Dockerfile is same dir. But if it is in different dir we have to pass the absolute path  of Dockerfile
   
    # To create a Docker file and from the Dockerfile we create an image
    # From the image we can create a container
   
    # succssfully tagged message should come atlast
   

   

   

4. Create a container from the built application/image

    docker run -p 8001:8001 -d react_django_app:latest
   

   

5. Check the container is up & running in port 8001

    docker ps
   

   

6. Now we have to map our URL in the EC2 instance so that app can run on a Public IPv4 port.

    # Follow the steps:
    # EC2 -> Security -> Security Groups -> Inbounds Rules-> Edit -> Add a rule
   
    Type: Custom TCP
    Port Range : 8001
    Source Tyep : Anywhere-IPv4
   
    Now save the Rule
   

   

7. Now copy the public ipv4 address and pass the port number to view the application.

   Public_IPv4_URL:<Port_number>

   

Project 2: Node Todo App

Node Todo App Repository

1. Cloning the Node Todo application from git and removing the existing Dockerfile.

    mkdir proj2
    cd proj2
    git clone https://github.com/Abhisek773/node-todo-cicd.git
    cd node-todo-cicd
    rm Dockerfile
   

   

2. Create a new Dockerfile to write the set of instructions for execution

    vim Dockerfile
   
    #
    FROM node:12.2.0-alpine
    COPY . .
    RUN npm install
    EXPOSE 8000
    CMD ["node","app.js"]
   

   

3. Create a container from the built application/image

    docker build . -t node_todo_app:latest
   

   

4. Checking the images

    docker images
   

   

5. Create a container from the built application/image

    docker run -p 8000:8000 -d node_todo_app:latest
   

   

6. Now edit the inbound rule for mapping the port number 8000 so that it will be shown using public IPv4.

    # Follow the steps:
    # EC2 -> Security -> Security Groups -> Inbounds Rules-> Edit -> Add a rule
   
    Type: Custom TCP
    Port Range : 8001
    Source Tyep : Anywhere-IPv4
   
    Now save the Rule
   

   

7. Now copy the public ipv4 address and pass the port number to view the application.

   Public_IPv4_URL:<Port_number>

   

8. Now we can see the containers up & running in port 8000

    docker ps
   

   

Push the image to a public or private repository (e.g. Docker Hub )

1. Create an account on Docker Hub

   DockerHub

   

2. Choose the free plan

   

3. Log in to the Docker hub

    sudo docker login
    # User name & password should provided
   

   

4. Creating the new image name for the existing container

   

    # Checking the image name
    docker ps
   
    # Giving new image name to the existing one
    sudo docker image tag react_django_app:latest abhisek6/react_django_app:latest
   

5. Push the image from local to remote

   

    sudo docker push abhisek6/react_django_app:latest
   

6. Now from the DockerHub dashboard, we can view our deployed image.

   

Thank You,

I want to express my deepest gratitude to each and every one of you who has taken the time to read, engage, and support my journey as a becoming DevOps Engineer.

Feel free to reach out to me if any corrections or add-ons are required on blogs. Your feedback is always welcome & appreciated.

~ Abhisek Moharana 😊