• Introduction
• Images
• Container
  • Containerize a single-container app
  • Deploying Apps with Docker Compose
  • Docker Swarm
• Docker Networking
• Docker Volume
  • Spring boot mongo app
• Docker installation guide

• Enables consistent environment
• Easy to use and maintain
• Efficient use of the system resources
• Increase in the rate of software delivery
• Increases operational efficiency
• Increases developer productivity

The Docker Engine is the infrastructure plumbing software that runs and orchestrates containers.

When you install Docker, you get two major components:

• Docker Client
  
• Docker Daemon (sometimes called “server” or “engine”)
  
  

Docker Client:

Docker client is the key component in the Docker system which is used by users to interact with Docker, it provides a command-line interface (CLI). When we run the docker commands, the client sends these commands to the daemon ‘dockerd, to issue build, run, and stop the application.

Docker Daemon:

The Docker daemon (dockerd) listens for Docker API requests and manages Docker objects such as images, containers, networks, and volumes. A daemon can also communicate with other daemons to manage Docker services.

Docker Registry:

A Docker registry stores Docker images. Docker Hub is a public registry that anyone can use, and Docker looks for images on Docker Hub by default. You can even run your own private registry.

You can use the docker versioncommand to test that the client and daemon (server) are running and talking to each other.

 docker version ## to check docker version

Docker Images are made up of multiple layers of read-only filesystems, these filesystems are called a Docker file, they are just text file with a set of pre-written commands. For every text written or instructions given in docker file a layer is created and is placed on top of another layer forming a docker image, which is future used to create docker container.
Run the docker image ls command on your Docker host.

 docker image ls or docker images
 docker search python:3.7
 docker search registry

To filter out and see only few columns

 docker search --filter "is-official=true" registry
 docker search alpine --filter "is-automated=true"
 docker search --format "{{.Name}}\t{{.Description}}\t{{.IsOfficial}}" registry

To list out all the present images in the node:

 docker images  
 docker images ls
 docker images nginx

To pull an Image

 docker image pull nginx:latest
 docker image pull nginx:alpine
 docker image pull --all-tags nginx

Clean up

 docker images
 docker image rm nginx:l-alpine-perl
 docker rmi 38049a7d921n293423
 docker rmi 3849a7sdf9sdf923f9 --force

A container is an isolated application, it is built from one or more images, and acts as an entire package system which includes all the libraries and dependencies required for an application to run. Docker containers come without OS, they use the Host OS for functionality, hence it is a more portable, efficient and lightweight system that comes with a guarantee that the software will run in any environment.

The most common way of starting containers is using the Docker CLI. The following docker container run command will start a simple new container.

 docker container create -it --name cc_busybox_A busybox:latest  
 docker container run -itd --rm --name cc_busybox_B busybox:latest
 docker ps -a
 docker container start cc_busybox_A
 docker container stop cc_busybox_B
 docker container restart --time 5 cc_busybox_A
 docker container rename cc_busybox_A my_busybox
 docker container run -d --name webserver -p 80:80 nginx

To execute any command

 docker exec -it my_busybox pwd 
 docker exec -it ubuntu1 bash
 docker attach ubuntu1
 docker container run --name ubuntu -it ubuntu:latest /bin/bash
 docker container run --name neversaydie -it --restart always alpine sh
 docker container run -d --name always \
  --restart always \
  alpine sleep 1d
 docker container run -d --name unless-stopped \
  --restart unless-stopped \
  alpine sleep 1d

Port Mapping

 docker container run -itd --name nginx -p 8080:80 /tcp nginx:latest
 docker container run -itd --name nginx_A -p nginx:latest

Remove Containers

 docker ps-a   ## list all the contianers
 docker container rm 672fc9dasd83h3j393
 docker container rm my_busybox --force
 docker container prune
 docker rm $( docker ps -aq)

Containers are all about apps! In particular, they’re about making apps simple to build, ship, and run.
The process of containerizing an app looks like this:

1. Start with your application code.
   
2. Create a Dockerfile that describes your app, its dependencies, and how to run it.
   
3. Feed this Dockerfile into the docker image build command.
   

The process of containerizing a simple single-container Node.js web app

Getting the application code

$ git clone https://github.com/nigelpoulton/psweb.git

Inspecting the Dockerfile

$ cat Dockerfile

The Dockerfile has two main purposes:

1. To describe the application
   
2. To tell Docker how to containerize the application (create an image with the app inside)

Containerize the app/build the image

 docker image build -t web:latest .

Run the app

 docker container run -d --name c1 \
  -p 80:8080 \
  web:latest

Create Dockerfile

$ vi Dockerfile

FROM tomcat:8.0-alpine
LABEL maintainer="[email protected]"

ADD sample.war /usr/local/tomcat/webapps/

EXPOSE 8080
CMD ["catalina.sh", "run"]

Paste the above mentioned code in Dockerfile

And build the image using command docker build -t mywebapp .

Run a container using the image $docker run -p 8080:8080 mywebapp

Instead of gluing everything together with scripts and long docker commands, Docker Compose lets you describe an entire app in a single declarative configuration file. You then deploy it with a single command.
Once the app is deployed, you can manage its entire lifecycle with a simple set of commands. You can even store and manage the configuration file in a version control system!

 docker-compose --version

Deploying an app with Compose We'll use the following 4 files from https://github.com/maveric-coder/dockerCompose-Counter-App.git:
• Dockerfile
• app.py
• requirements.txt
• docker-compose.yml
Clone the Git repo locally.

git clone https://github.com/maveric-coder/dockerCompose-Counter-App.git
cd dockerCompose-Counter-App
ls

Let’s quickly describe each file:
• app.py is the application code (a Python Flask app)
• docker-compose.yml is the Docker Compose file that describes how Docker should deploy the app
• Dockerfile describes how to build the image for the web-fe service
• requirements.txt lists the Python packages required for the app

Compose to bring the app up.

 docker-compose up &
 docker-compose -f prod-equus-bass.yml up

At a high level Swarm has two major components:
• A secure cluster
• An orchestration engine

Each of the nodes needs Docker installed and needs to be able to communicate with the rest of the swarm. It’ also beneficial if name resolution is configured — it makes it easier to identify nodes in command outputs and helps when troubleshooting.

Initializing a brand new swarm Docker nodes that are not part of a swarm are said to be in single-engine mode. Once they’re added to a swarm they’re switched into swarm mode.
The following steps will put mgr1 into swarm mode and initialize a new swarm. It will then join wrk1, wrk2, and wrk3 as worker nodes — automatically putting them into swarm mode. Finally, it will add mgr2 and mgr3 as additional managers and switch them into swarm mode.

1. Log on to mgr1 and initialize a new swarm

 docker swarm init \
  --advertise-addr 10.0.0.1:2377 \
  --listen-addr 10.0.0.1:2377
  
 docker swarm join-token worker
 docker swarm join-token manager
  

To join:

docker swarm join \
 --token SWMTKN-1-0uahebax...ue4hv6ps3p \  
 10.0.0.1:2377 \
 --advertise-addr 10.0.0.2:2377 \
 --listen-addr 10.0.0.1:2377

List the nodes in the swarm by running docker node ls from any of the manager nodes in the swarm.

 docker node ls

Swarm services docker service create to tell Docker we are declaring a new service, and we used the --name flag to name it web-fe. We told Docker to map port 8080 on every node in the swarm to 8080 inside of each service replica. Next, we used the -- replicas flag to tell Docker that there should always be 5 replicas of this service.

 docker service create --name web-fe \
  -p 8080:8080 \
  --replicas 5 \
  nigelpoulton/pluralsight-docker-ci

Viewing and inspecting services

 docker service ls
 docker service ps web-fe
 docker service inspect --pretty web-fe

Scaling a service

 docker service scale web-fe=10
 docker service scale web-fe=5

Removing a service

 docker service rm web-fe

Be careful using the docker service rm command, as it deletes all service replicas without asking for confirmation.

Rolling updates

This creates a new overlay network called “uber-net” that we’ll be able to leverage with the service we’re about to create. An overlay network creates a new layer 2 network that we can place containers on, and all containers on it will be able to communicate. This works even if the Docker hosts the containers are running on are on different underlying networks. Basically, the overlay network creates a new layer 2 container network on top of potentially multiple different underlying networks.

 docker network create -d overlay uber-net
 docker network ls

 docker service create --name uber-svc \
  --network uber-net \
  -p 80:80 --replicas 12 \
  nigelpoulton/tu-demo:v1
  
 docker service ls
 docker service ps uber-svc

 docker service update \
  --image nigelpoulton/tu-demo:v2 \
  --update-parallelism 2 \
  --update-delay 20s uber-svc
  
docker service ps uber-svc
  

Docker runs applications inside of containers, and these need to communicate over lots of different networks. This means Docker needs strong networking capabilities. Docker networking is based on an open-source pluggable architecture called the Container Network Model (CNM). Different types of Networks are:

• bridge
• host
• overlay
• IPvLAN
• macvlan

docker network ls
docker network inspect bridge

ip link show docker0

The default “bridge” network, on all Linux-based Docker hosts, maps to an underly- ing Linux bridge in the kernel called “docker0”.

docker network inspect bridge | grep bridge.name

docker network create -d bridge localnet
docker container run -d --name c1 \
  --network localnet \
  alpine sleep 1d
  
docker network inspect localnet --format '{{json .Containers}}'

docker container run -it --name c2 \
  --network localnet \
  alpine sh

From within the “c2” container, ping the “c1” container by name.

ping c1

Port mappings let you map a container port to a port on the Docker host. Any traffic hitting the Docker host on the configured port will be directed to the container. This is mapped to port 5000 on the host’s 10.0.0.15 interface. The end result is all traffic hitting the host on 10.0.0.15:5000 being redirected to the container on port 80. An example of mapping port 80 on a container running a web server, to port 5000 on the Docker host.

 docker container run -d --name web \
  --network localnet \
  --publish 5000:80 \
  

localhost or 127.0.0.1. nginx

To attach a running container to a network

 docker network connect <network_name> <container_ID>
 docker network disconnect <network_name> <container_ID>

The recommended way to persist data in containers is with volumes. At a high-level, you create a volume, then you create a container, and you mount the volume into it. The volume gets mounted to a directory in the container’s filesystem, and anything written to that directory is written to the volume. If you then delete the container, the volume and its data will still exist.

Use the following command to create a new volume called myvol.

 docker volume create myvol
 docker volume inspect myvol

By default, Docker creates new volumes with the built-in local driver. As the name suggests, local volumes are only available to containers on the node they’re created on. Use the -d flag to specify a different driver.

There are two ways to detele docker volumes i.e. docker volume prune and docker volume rm To attach the created Volume to a container, we willl execute below commands.

 docker container run -dit --name voltainer \ --mount source=myvol,target=/vol \ alpine
 docker run --name MyJenkins1 -v myvol1:/var/jenkins_home -p 8080:8080 -p 50000:50000 jenkins

To understand better how making the data persistent actually works. Let's see through a live application deployment. Clone the repository to the server with docker, the same server should have maven installed as well (to build the application)

git clone https://github.com/maveric-coder/spring-boot-mongo-docker.git
cd spring-boot-mongo-docker
mvn clean package

By executing the above commands, in the target folder .jar file will be available as the artifact ready to be deployed. The Dockerfile present in the folder contains info and commands to build the image to run the created artifact.Below mentioned command will build an image.

 docker build -t anand2909/spring-boot-mongo .

To check the build image run docker images and inspect the image by running $docker image inspect anand2909/spring-boot-mongo. Create an App container by

 docker run -d --name springmongoapp -p 8080:8080 anand2909/spring-boot-mongo

Let's create a Mongo container to enter and process the entered data.

 docker run -d --name mongo mongo

Now if we will open the webpage for the application we will still not be able to connect as we did not do the needed configuration. Delete the existing app container and recreate by mentioned commands

 docker rm -f <container_id>
 docker run -d --name springmongoapp -p 8080:8080 anand2909/spring-boot-mongo
java -Dspring.data.mongodb.uri=mongodb://<Mongo_container_IP>:27017/spring-mongo -Djava.security.egd=file:/dev/./urandom -jar ./spring-boot-mongo.jar

The date being entered will be stored now but it will be only till the Mongo DB is present in the server. Once the Mongo container is deleted the saved data will be flushed out. Docker volume will make the date persistent and can be attached to other containers. Delete the existing mongo container and create a new Mongo container with a new volume.

 docker volume create mongobckp
 docker run -d --name mongo -v mongobckp:/data/db mongo

There are two types of volumes:

• Local volume
• Network volume

To use the network volume, REX-RAY can be used

 docker plugin install rexray/ebs   EBS_ACCESSKEY=AKIA2NNCZ7U3DFCHL7N4   EBS_SECRETKEY=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
 docker volume create --driver rexray/ebs --name ebsvol
 docker run -d --name mongo -v rexray/ebs:/data/db mongo

In earlier step, private IP address was entered to connect with Mongo DB container. But if both the containers will be in same network then they can communicate by container names. Steps to create and configure containers in the same network are below:

 docker network create -d bridge appnet
 docker network connect appnet mongo
 docker network connect appnet springmongoapp

ARG (build time):

Variables defined through ARG are also known as build-time variables. They are only available from the moment they are ‘announced’ in the Dockerfile with an ARG instruction in the Dockerfile.

Running containers can’t access the values of ARG variables. So anything you run via CMD and ENTRYPOINT instructions won’t see those values by default.

The benefit of ARG is, that Docker will expect to get values for those variables. At least, if you don’t specify a default value. If those values are not provided when running the build command, there will be an error message. Here is an example where Docker fill complain during build:

# no default value is specified!
ARG some_value

Even though ARG values are not available to the container, they can easily be inspected through the Docker CLI after an image is built. For example by running docker history on an image. ARG and ENV are a poor choice for sensitive data if untrusted users have access to your images.

ENV (build time and run time):

ENV variables are available both during the build and to the future running container. In the Dockerfile, they are usable as soon as you introduce them with an ENV instruction.

Unlike ARG, ENV values are accessible by containers started from the final image. ENV values can be overridden when starting a container, more on that below.

Syntax

docker container cp
docker cp

Copy files/folders between a container and the local filesystem.

Copy a local file into container

docker cp ./some_file CONTAINER:/work

Copy files from container to local path

docker cp CONTAINER:/var/logs/ /tmp/app_logs

Copy a file from container to stdout. Please note cp command produces a tar stream

docker cp CONTAINER:/var/logs/app.log - | tar x -O | grep "ERROR"

Example:

docker cp styles.css web1:/usr/share/nginx/html/