Cloud Computing 2021/22 spring

Practice 2 - Working with Docker

In this lab, we will take a look at how to install Docker, use Docker CLI commands, and how to containerize applications. Docker containers allow the packaging of your application (and everything that you need to run it) in a “container image”. Inside a container, you can include all necessary libraries, files and folders, environment variables, volume mount-points, and your application binaries.

Key terminology:

• Docker image
  • Lightweight, stand-alone, executable package that includes everything needed to run piece of software
  • Includes code, a runtime, library, environment variables and config files
• Docker container
  • Runtime instance of an image - what the image become in memory when actually executed.
  • Completely isolated from the host environment.

Build, Ship, and Run Any App, Anywhere

Docker architecture

• Docker is available in two editions: Community Edition (CE) and Enterprise Edition (EE)
• Supported Platform: macOS, Microsoft Windows 10, CentOS, Debian, Fedora, RHEL,Ubuntu and more.

References

Referred documents and web sites contain supportive information for the practice.

Manuals

1. Docker fundamentals: https://docs.docker.com/engine/docker-overview/
2. Docker CLI :https://docs.docker.com/engine/reference/commandline/cli/
3. Building docker image: https://docs.docker.com/engine/reference/builder/

In case of issues check:

1. Pinned messages in the #lab2-docker Slack channel.
   • If you can not see the channel, use the the Add channels -> Browse all channels to find it
2. Possible solutions to common issues section at the end of the guide.
3. Ask in the #lab2-docker Slack channel.

Exercise 2.1. Installation of docker inside OpenStack instance

In this task, you are going to install docker in Ubuntu OS and try to run the basic commands to make you comfortable with docker commands used in the next tasks.

• Create a virtual machine with ubuntu20.04 OS as carried out in Practice1 and connect to the virtual machine remotely using via SSH.
  • NB! DO NOT use your previous lab image/snapshot!
• NB! Extra modifications required to change docker network settings:
  • Create a directory in the virtual machine in the path: /etc/docker
    • sudo mkdir /etc/docker
  • Create a file in the docker directory: sudo nano /etc/docker/daemon.json with the following content:

    {
      "default-address-pools": [{ "base":"172.80.0.0/16","size":24 }]
    }

  • This change is required because otherwise, Docker will use network addresses that collide with the university networks, and you WILL lose access to the instance.
• Update the apt repo sudo apt-get update
• Install packages to allow apt to use a repository over HTTPS:
  • sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
• Add Docker’s official GPG key
  • curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
• Use the following command to set up the stable repository.
  • sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
• Update the apt package index, install Docker
  • sudo apt-get update
  • sudo apt-get install docker-ce

NB! To run a docker commands with non root privileges

• Create a docker group (If it's already created than ignore):sudo groupadd docker
• Add a user to docker group:sudo usermod -aG docker $USER
• Activate the changes:newgrp docker

• Check the installation by displaying docker version:docker --version

Exercise 2.2. Practicing docker commands

This task mainly helps you to learn basic commands used by docker CLI such as run, pull, listing images, attaching data volume, working with exec (like ssh a container), checking ip address and port forwarding. You can have a look into basic docker commands here: Docker commands

The following tasks include: Pulling an image from Docker Hub and running an Ubuntu container' in detached mode https://docs.docker.com/engine/reference/run/#detached-vs-foreground detached mode and assign your name as container-name, further installing HTTP server (use docker exec'' command) and use port forwarding to access container-http traffic via host port 80.

• Create a login account at Docker Hub sign-up page
• Login into your docker account from docker host terminal: docker login
  • Provide input to the following:
    • Username: your docker hub id
    • Password: Docker hub password
• NB! The login part is not mandatory but needed/recommended as recently docker hub limits the number of docker pull from a particular IP. As you are using the university network through VPN, it serves as a single IP for the Docker hub. (Error response from daemon: toomanyrequests: You have reached your pull rate limit. You may increase the limit by authenticating and upgrading: https://www.docker.com/increase-rate-limit)
• Pull an image from docker hub:docker pull ubuntu
• Check the downloaded images in local repository: docker images
• Run a simple ubuntu container, here detachedmode (-d),-it runs interactively (so you get a pseudo-TTY with STDIN) :docker run -dit -p 80:80 --name <<yourname>> ubuntu
  • <<yourname>> = please type your name
• Get the bash shell of container with non detached mode: docker exec -it <container_name> sh
  • Here you could start configuring your container: install packages, modify files, etc.. Alternatively, you can also run commands "outside" of the container using docker exec, as we will do in next steps.
  • Exit from the container:exit
• Connect to container and update the apt repo:docker exec -dit <container_name> apt-get update
• Install http server:docker exec -it <container_name> apt-get install apache2
• Check the status of http server: docker exec -it <container_name> service apache2 status
• If not running, start the http server: docker exec -it <container_name> service apache2 start
• Check the webserver running container host machine :curl localhost:80
• Check the ip address of the container: docker inspect <container_id> | grep -i "IPAddress"
• Commit the docker container changes in to docker image docker commit -m "added apache2 web server" -a "your_name" <container_id> "image_name"
• Check the newly created image using docker images
• Now, stop and delete your container

• Host directory as a data volume: Here you are mounting a host directory in a container and this is useful for testing the applications. For example you store source code in the host directory and mount in the container, the code changed in host directory file can effect the application running in the container.
  • Accessing a host file system on container with read only and read/write modes:
    • Create directory with name test:mkdir test && cd test, Create a file:touch abc.txt
    • Run a container and -v parameter to mount the host directory to the container
      • Read only:docker run -dit -v /home/ubuntu/test/:/home/:ro --name vol1 ubuntu sh
      • Access the file in a container in the path /home and try to create a new file(you should see access denied) from container docker exec -it vol1 sh, cd /home, ls, exit.
      • Read/write:docker run -dit -v /home/ubuntu/test/:/home/:rw --name vol2 ubuntu ,docker exec -it vol2 sh,cd /home, ls,Try to create some text files,exit.You can see the created files in host machine cd /home/ubuntu/test/,ls
  • NB! Take the screenshot heredocker ps
    • Stop and delete the container : docker stop vol1,docker rm vol1
• Data volume containers: A popular practice with Docker data sharing is to create a dedicated container that holds all of your persistent shareable data resources, mounting the data inside of it into other containers once created and setup.
  • Create a data volume container and share data between containers.
    • Create a data volume container docker run -dit -v /data --name data-volume ubuntu ,docker exec -it data-volume sh
    • Go to volume and create some files:cd /data && touch file1.txt && touch file2.txt Exit the container exit
    • Run another container and mount the volume as earlier container:docker run -dit --volumes-from data-volume --name data-shared ubuntu,docker exec -it data-shared sh
    • Go to the data directory in the created container and list the files: cd /data && ls
  • NB! Take the screenshot heredocker ps

Exercise 2.3. Creating Docker Image using Dockerfile

The task is to create your own docker image and try to run the same. More information about Dockerfile (https://docs.docker.com/engine/reference/builder/). A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. Using docker build users can create an automated build that executes several command-line instructions in succession.

Some of Dockerfile commands:

The scenario is to create a docker image and deploy the flask application from Practice Session 1 (Message Board) using the docker container. In this exercise, we are going to perform three tasks:

1. Create docker Image for flask application (Message Board)
2. Deploy flask application container using the host directory as a volume(bind volumes) to store messages in the host directory (data.json in flask application).
3. Deploy a different version of the flask application, linking to PostgreSQL relational database container to store the data, instead of a text-file.

Task 2.3.1: Create docker image for flask application

• First, fetch the source code of the application with git, storing it into the folder "lab2app":
  • git clone https://bitbucket.org/jaks6/cloud-computing-2022-lab-1.git lab2app
• change to lab2app cd lab2app
• Modify your home.html on your own style to display your name.
• Now, let us write a Dockerfile to create a docker image as shown below:
  • Create a Dockerfile (inside the lab2app directory) sudo nano Dockerfile
  • Add the following set docker commands:
    FROM command chooses the base image for the container, here its python:slim-buster
    COPY command will copy the code from host directory to container directory lab2app (Your copying the Messageboard code to container image)
    WORKDIR Set the current working directory when your container starts.
    RUN command will run the specified commands on the shell.
    CMD command will run the flask application at a specified host address and port.
    

    FROM python:slim-buster
    WORKDIR /lab2app
    COPY . .
    RUN pip3 install -r requirements.txt
    ENV FLASK_APP=app.py
    ENV FLASK_RUN_HOST=0.0.0.0
    EXPOSE 5000
    CMD [ "flask", "run"]
    
• Build the container image using the following command docker build as docker build -t <flask_task1_lastname> . inside the lab2app folder.
  • Now, look at the output of the build command where a set of docker commands are executed in the order you written in Dockerfile.
  • After a successful build, you should see your built image in the list of local images when calling docker images
• Now, run the container with the following options:
  • port mapping : host(80) to container(5000)
  • image name: <flask_task1_lastname>
  • Name of container: <task1_your_lastname>
• By now, you should see the application running at http://VM_IP:80
• Stop and delete the container

Task 2.3.2: Deploy Flask app container with a mounted-volume based storage

Deploy flask application container using the host directory as a volume(bind volumes) to store messages in the host directory (data.json in flask application).

• Copy the data.json file (inside the lab2app folder) into the ubuntu user home folder inside the VM in the path (/home/ubuntu/data.json).
• Now run the container with the following options:
  • detached mode (-dit)
  • Container image <flask_task1_lastname>
  • Name of container <task2_your_lastname>
  • port mapping host(80), container(5000)
  • Volume (-v) /home/ubuntu/data.json:/lab2app/data.json
    • This vill mount the file you previously created (inside the host file) into the correct location inside the container.
• By now, you should see the application running at http://VM_IP:80 and add few messages
• Check the content of data.json cat /home/ubuntu/data.json, here you can see the added messages.
• Stop and remove the container
• Run the container again and should see the data of previous container's application in http://VM_IP:80 web page
• NB! Take the screenshot of cat /home/ubuntu/data.json inside the VM and docker exec -it <task2_your_lastname> cat /lab2app/data.json
• Stop and delete the container

Task 2.3.3: Deploy Flask app container with a database container for storage

Deploy flask application with linking to PostgreSQL relational database container to store the data.

• Firstly run the Postgresql database container using following command and set the value of postgresql configuration variable POSTGRES_PASSWORD according to your convenience in docker run -d --name postgres -e POSTGRES_USER=postgres -e POSTGRES_PASSWORD=<your_paasword> -e PGDATA=/var/lib/postgresql/data/pgdata -v /tmp:/var/lib/postgresql/data -p 5432:5432 -it postgres:14.1-alpine
• Now let us clone the modified code to store messages in the postgresql container. You use the clone as git clone https://bitbucket.org/shivupoojar87/task3lab2app.git task3lab2app. In this code, we used SQLAlchemy with Flask framework to interact with Postgresql.
• Change the current directory to task3lab2app and copy the Dockerfile of Task 2 in this directory.
• Modify the home.html to diaply your name and task number
• Rebuild the image with name <flask_task3_lastname>
• Now run the container with following options:
  • detached mode (-dit)
  • Container image: <flask_task3_lastname>
  • Name of container: <task3_your_lastname>
  • port mapping : host(80), container(5000)
  • Set environment variable for linking the postgres database (-e): DATABASE_URL=postgresql://postgres:<your_paasword>@<VM_IP>:5432/postgres
  • The whole command for example should look like: docker run -dit -p 80:5000 --name flask -e DATABASE_URL=postgresql://postgres:4y7sV96vA9wv46VR@172.17.67.119:5432/postgres flask_poojara:latest
    • NB! make sure to change the password and the IP address in this command to match the information of your postgres container. For IP address you can use the IP of the host VM (replacing 172.17.67.119 in the example command)
• By now, you should see the application running at http://VM_IP:80 and add few messages.
• NB!! Take the screenshot of running containers and output of web page
• Stop and remove the postgresql container
• Again create postgresql container and still you can see the previous messages in the flask application. The volumes are important to persistent your data in the host even though the container is deleted or killed.

Exercise 2.4. Shipping a docker image to Docker hub

Docker hub is a hosted repository service provided by Docker for finding and sharing container images with your team. (https://www.docker.com/products/docker-hub)

• Create a login account in docker hub (if you do not have one already) using link https://hub.docker.com/signup .
• Push the docker image to docker hub
  • Initially login into your docker account from docker host terminal: docker login
    • Provide input to the following:
      • Username: your docker hub id
      • Password: Docker hub password
  • Tag your image before pushing into docker hub:docker tag <flask_task3_lastname> your-dockerhub-id/flask1.0
  • Finally push the image to docker hub: docker push your-dockerhub-id/flask1.0
• Scenario 1: Modify the container by creating some directories and save the changes in the image using the docker commit command.
• Scenario 2: Export the container as a tar file by using the command docker export.
  • NB! Take the screenshot of the docker hub account showing your image

Exercise 2.5. Working with docker compose.

Docker Compose is a tool for defining and running multi-container Docker applications. With Compose, you use a YAML file to configure your application’s services. Then, with a single command, you create and start all the services from your configuration. To learn more about all the features of Compose, see the list of features.

The compose has commands for managing the whole lifecycle of your application:

1. Start, stop, and rebuild services
2. View the status of running services
3. Stream the log output of running services

In this exercise, we are going to use docker-compose commands to start/stop/view status multiple services (flask application and Postgresql database service). We have two tasks to perform:

1. Task 1: Working with the docker-compose commands for deploying Message-Board application that stores the data in the directory.
2. Task 2: Working with the docker-compose commands for deploying Message-Board flask application that linked to Postgresql.

Setup the docker-compose service using sudo apt install docker-compose

Task 2.5.1

Working with the docker-compose commands for deploying Message-Board application that stores the data in directory.

• Go to the directory of the data.json -version of the flask application (lab2app directory)
• Create a docker-compose file nano docker-compose.yml to define a new Docker service called flask_app with following options:
  • port mapping host(80), container(5000)
  • Volume (-v) .:/lab2app

version: "3.7"
services:
  flask_app:
    build: .
    ports:
      - "80:5000"
    volumes:
      - .:/lab2app

• Now, run the docker-compose docker-compose up, this will build the image and create the application container in non-detached mode. When you cancel the docker-compose task it automatically deletes the container.
• You can try to run in detached mode using docker-compose up -d and check the running container at http://VM_IP:80 and add a few messages. You can also check the contents of data.json in your host machine.
• Check the list of docker-compose services docker-compose ps
• Stop the services using command docker-compose stop
• Try at least two other commands from this list
• NB! Take the screenshot of the output of the commands that you tried.

Task 2.5.2

Working with the docker-compose commands for deploying Message-Board flask application that linked to Postgresql.

This task is to be carried out by yourself with the knowledge of the previous task and reading docker-compose documentation.

• Create docker-compose.yml with 2 services (flask_app, postgresql).
  • As a starting point, you can use this "skeleton":

  version: "3.7"
  services:
    flask_app:
  
    postgresql:
  
  volumes:
    db:
  

• For flask_app:
  • Build path should be the location of Dockerfile
  • You need to use tag depends_on to link the flask_app application to postgresql service (Example)
  • Set environment variables, here DATABASE_URL=postgresql://postgres:<postgresql_password>@postgresql:5432/postgres (Example)
    • Make sure to change the PASSWORD to match the PostgreSQL password
  • Set port mapping to map host port 80 to container port 5000
• For postgresql:
  • Set image as postgres:14.1-alpine
  • Set environment variables POSTGRES_USER=postgres and POSTGRES_PASSWORD=postgres
  • We do not need to map ports, because the database container does not have to be accessible externally through the host machine ports.
  • Assign a Volume where the database files will be stored db:/var/lib/postgresql/data
• Define which volumes should be created:
  • Define the db volume as a separate entry at the end of the docker-compose.yml file (outside and after the "services:" entry)

    • volumes:
        db:
         name: postgres-db-vol
      

• Create and run the services using docker-compose up (do NOT use -d).
  • As a result, you get 2 service containers running, plus 1 data volume, all from a single command!
• NB! Take the screenshot of docker-compose up command output

Deliverables

• Upload the screenshot taken as mentioned in Exercise 2.2(2 screenshots), Exercise 2.3 (2 screenshots), Exercise 2.4, and Exercise 2.5 (2 screenshots).
• Source code of two flask applications and docker-compose files should be included (You can copy to host machine from VM using scp command and Windows users can use WinSCP tool).
• Pack the screenshots into a single zip file and upload them through the following submission form.
• Your instance must have been terminated!

In case of issues, check these potential solutions to common issues:

1. If you run into an issue about missing requirements.txt when building the Docker file, it is likely because of the location of the Docker file and the folder in which you run the docker build command.
   • I would suggest making sure that:
     • Dockerfile is inside the lab2app folder
     • run the docker build command inside the folder
   • Otherwise the COPY command has to use slightly different relative paths inside the example Docker file.
2. Seems that there is an issue with university VPN after the software was updated. the old guide no longer works.
   • You can use the suggested approach by one student:
     • Log into UT VPN service and download the profile file: https://tunnel.ut.ee/
     • Download and install the official OpenVPN Connect client: https://openvpn.net/download-open-vpn/ and import the profile file.