Book Image

Docker Deep Dive

By : Nigel Poulton
Book Image

Docker Deep Dive

By: Nigel Poulton

Overview of this book

Most applications, even the funky cloud-native microservices ones, need high-performance, production-grade infrastructure to run on. Having impeccable knowledge of Docker will help you to thrive in the modern cloud-first world. With this book, you’ll gain the skills you need to work with Docker and its containers. The book begins with an introduction to containers and explains its functionality and application in the real world. You’ll then get an overview of VMware, Kubernetes, and Docker and learn to install Docker on Windows, Mac, and Linux. Once you’ve understood the Ops and Dev perspective of Docker, you’ll be able to see the big picture and understand what Docker exactly does. The book then turns its attention to the more technical aspects, guiding your through practical exercises covering Docker engine, Docker images, and Docker containers. You’ll learn techniques for containerizing an app, deploying apps with Docker Compose, and managing cloud-native applications with Swarm. You’ll also build Docker networks and Docker overlay networks and handle applications that write persistent data. Finally, you’ll deploy apps with Docker stacks and secure your Docker environment. By the end of this book, you’ll be well-versed in Docker and containers and have developed the skills to create, deploy, and run applications on the cloud.
Table of Contents (3 chapters)

4: The big picture

The aim of this chapter is to paint a quick big-picture of what Docker is all about before we dive in deeper in later chapters.

We’ll break this chapter into two:

  • The Ops perspective
  • The Dev perspective

In the Ops Perspective section, we’ll download an image, start a new container, log in to the new container, run a command inside of it, and then destroy it.

In the Dev Perspective section, we’ll focus more on the app. We’ll clone some app-code from GitHub, inspect a Dockerfile, containerize the app, run it as a container.

These two sections will give you a good idea of what Docker is all about and how the major components fit together. It’s recommended that you read both sections to get the dev and the ops perspectives. DevOps anyone?

Don’t worry if some of the stuff we do here is totally new to you. We’re not trying to make you an expert in this chapter. This is about giving you a feel of things — setting you up so that when we get into the details in later chapters, you have an idea of how the pieces fit together.

If you want to follow along, all you need is a single Docker host with an internet connection. I recommend Docker Desktop for your Mac or Windows PC. However, the examples will work anywhere that you have Docker installed. We’ll be showing examples using Linux containers and Windows containers.

If you can’t install software and don’t have access to a public cloud, another great way to get Docker is Play With Docker (PWD). This is a web-based Docker playground that you can use for free. Just point your web browser to and you’re ready to go (you’ll need a Docker Hub or GitHub account to be able to login).

As we progress through the chapter, we may use the terms “Docker host” and “Docker node” interchangeably. Both refer to the system that you are running Docker on.

The Ops Perspective

When you install Docker, you get two major components:

  • the Docker client
  • the Docker daemon (sometimes called the “Docker engine”)

The daemon implements the runtime, API and everything else required to run Docker.

In a default Linux installation, the client talks to the daemon via a local IPC/Unix socket at /var/run/docker.sock. On Windows this happens via a named pipe at npipe:////./pipe/docker_engine. Once installed, you can use the docker version command to test that the client and daemon (server) are running and talking to each other.

> docker version
Client: Docker Engine - Community
 Version:       19.03.8
 API version:   1.40
 Go version:    go1.12.17
 Git commit:    afacb8b
 Built: Wed Mar 11 01:23:10 2020
 OS/Arch:       linux/amd64
 Experimental:  false

  Version:          19.03.8
  API version:      1.40 (minimum version 1.12)
  Go version:       go1.12.17
  Git commit:       afacb8b
  Built:            Wed Mar 11 01:29:16 2020
  OS/Arch:          linux/amd64
  Experimental:     false
  Version:          v1.2.13

If you get a response back from the Client and Server, you’re good to go.

If you are using Linux and get an error response from the Server component, make sure that Docker is up and running. Also, try the command again with sudo in front of it: sudo docker version. If it works with sudo you will need to add your user account to the local docker group, or prefix the remainder of the commands in the book with sudo.


It’s useful to think of a Docker image as an object that contains an OS filesystem, an application, and all application dependencies. If you work in operations, it’s like a virtual machine template. A virtual machine template is essentially a stopped virtual machine. In the Docker world, an image is effectively a stopped container. If you’re a developer, you can think of an image as a class.

Run the docker image ls command on your Docker host.

$ docker image ls

If you are working from a freshly installed Docker host, or Play With Docker, you will have no images and it will look like the previous output.

Getting images onto your Docker host is called “pulling”. If you are following along with Linux, pull the ubuntu:latest image. If you are following along on Windows, pull the image.

$ docker image pull ubuntu:latest
latest: Pulling from library/ubuntu
50aff78429b1: Pull complete
f6d82e297bce: Pull complete
275abb2c8a6f: Pull complete
9f15a39356d6: Pull complete
fc0342a94c89: Pull complete
Digest: sha256:fbaf303...c0ea5d1212
Status: Downloaded newer image for ubuntu:latest

Windows images can be large and take a long time to pull.

Run the docker image ls command again to see the image you just pulled.

$ docker images
ubuntu          latest   1d622ef86b13    16 hours ago    73.9MB

We’ll get into the details of where the image is stored and what’s inside of it in later chapters. For now, it’s enough to know that an image contains enough of an operating system (OS), as well as all the code and dependencies to run whatever application it’s designed for. The ubuntu image that we’ve pulled has a stripped-down version of the Ubuntu Linux filesystem, including a few of the common Ubuntu utilities. The image contains a Windows Server Core OS plus PowerShell.

If you pull an application container such as nginx or, you will get an image that contains some OS, as well as the code to run either NGINX or IIS.

It’s also worth noting that each image gets its own unique ID. When referencing images, you can refer to them using either IDs or names. If you’re working with image ID’s, it’s usually enough to type the first few characters of the ID — as long as it’s unique, Docker will know which image you mean.


Now that we have an image pulled locally, we can use the docker container run command to launch a container from it.

For Linux:

$ docker container run -it ubuntu:latest /bin/bash

For Windows:

> docker container run -it pwsh.exe

PowerShell 7.0.0
Copyright (C) Microsoft Corporation. All rights reserved.
PS C:\>

Look closely at the output from the previous commands. You should notice that the shell prompt has changed in each instance. This is because the -it flags switch your shell into the terminal of the container — you are literally inside of the new container!

Let’s examine that docker container run command.

docker container run tells the Docker daemon to start a new container. The -it flags tell Docker to make the container interactive and to attach the current shell to the container’s terminal (we’ll get more specific about this in the chapter on containers). Next, the command tells Docker that we want the container to be based on the ubuntu:latest image (or the image if you’re following along with Windows). Finally, we tell Docker which process we want to run inside of the container. For the Linux example we’re running a Bash shell, for the Windows container we’re running PowerShell.

Run a ps command from inside of the container to list all running processes.

Linux example:

root@6dc20d508db0:/# ps -elf
4 S root     1     0    0 -  4560 -      13:38 pts/0    00:00:00 /bin/bash
0 R root     9     1    0 -  8606 -      13:38 pts/0    00:00:00 ps -elf

Windows example:

PS C:\> ps

NPM(K)    PM(M)      WS(M)     CPU(s)      Id  SI ProcessName
 ------    -----      -----     ------      --  -- -----------
      5     0.90       3.78       0.00    1068   1 CExecSvc
      6     0.97       4.12       0.03    1184   1 conhost
      6     0.87       2.16       0.00     972   1 csrss
      0     0.06       0.01       0.00       0   0 Idle
     18     4.38      12.32       0.00     272   1 lsass
     54    34.82      65.09       1.27    1212   1 pwsh
      9     1.61       4.99       0.00    1020   1 services
      4     0.49       1.18       0.00     948   0 smss
     14     1.98       6.61       0.00     628   1 svchost
     12     2.95      10.02       0.00     752   1 svchost
      8     1.83       6.02       0.00     788   1 svchost
      7     1.42       4.70       0.00    1040   1 svchost
     16     6.12      11.41       0.00    1120   1 svchost
     24     3.73      10.38       0.00    1168   1 svchost
     15     9.60      18.96       0.00    1376   1 svchost
      0     0.16       0.14       0.00       4   0 System
      8     1.16       4.12       0.00    1004   1 wininit

The Linux container only has two processes:

  • PID 1. This is the /bin/bash process that we told the container to run with the docker container run command.
  • PID 9. This is the ps -elf command/process that we ran to list the running processes.

The presence of the ps -elf process in the Linux output can be a bit misleading as it is a short-lived process that dies as soon as the ps command completes. This means the only long-running process inside of the container is the /bin/bash process.

The Windows container has a lot more going on. This is an artefact of the way the Windows Operating System works. However, even though the Windows container has a lot more processes than the Linux container, it is still a lot less than a regular Windows Server.

Press Ctrl-PQ to exit the container without terminating it. This will land your shell back at the terminal of your Docker host. You can verify this by looking at your shell prompt.

Now that you are back at the shell prompt of your Docker host, run the ps command again.

Notice how many more processes are running on your Docker host compared to the container you just ran. Windows containers run far fewer processes than Windows hosts, and Linux containers run far less than Linux hosts.

In a previous step, you pressed Ctrl-PQ to exit from the container. Doing this from inside of a container will exit you from the container without killing it. You can see all running containers on your system using the docker container ls command.

$ docker container ls
6dc20d508db0   ubuntu:latest  "/bin/bash"   7 mins   Up 7 min  vigilant_borg

The output above shows a single running container. This is the container that you created earlier. The presence of the container in this output proves that it’s still running. You can also see that it was created 7 minutes ago and has been running for 7 minutes.

Attaching to running containers

You can attach your shell to the terminal of a running container with the docker container exec command. As the container from the previous steps is still running, let’s make a new connection to it.

Linux example:

This example references a container called “vigilant_borg”. The name of your container will be different, so remember to substitute “vigilant_borg” with the name or ID of the container running on your Docker host.

$ docker container exec -it vigilant_borg bash

Windows example:

This example references a container called “pensive_hamilton”. The name of your container will be different, so remember to substitute “pensive_hamilton” with the name or ID of the container running on your Docker host.

> docker container exec -it pensive_hamilton pwsh.exe

PowerShell 7.0.0
Copyright (C) Microsoft Corporation. All rights reserved.
PS C:\>

Notice that your shell prompt has changed again. You are logged into the container again.

The format of the docker container exec command is: docker container exec <options> <container-name or container-id> <command/app>. In our examples, we used the -it options to attach our shell to the container’s shell. We referenced the container by name, and told it to run the bash shell (PowerShell in the Windows example). We could easily have referenced the container by its hex ID.

Exit the container again by pressing Ctrl-PQ.

Your shell prompt should be back to your Docker host.

Run the docker container ls command again to verify that your container is still running.

$ docker container ls
6dc20d508db0   ubuntu:latest  "/bin/bash"   9 mins   Up 9 min  vigilant_borg

Stop the container and kill it using the docker container stop and docker container rm commands. Remember to substitute the names/IDs of your own containers.

$ docker container stop vigilant_borg

$ docker container rm vigilant_borg

Verify that the container was successfully deleted by running the docker container ls command with the -a flag. Adding -a tells Docker to list all containers, even those in the stopped state.

$ docker container ls -a

You’ve just pulled a Docker image, started a container from it, attached to it, executed a command inside it, stopped it, and deleted it.

The Dev Perspective

Containers are all about the apps.

In this section, we’ll clone an app from a Git repo, inspect its Dockerfile, containerize it, and run it as a container.

The Linux app can be cloned from:

The Windows app can be cloned from:

The rest of this section will focus on the Linux NGINX example. However, both examples are containerizing simple web apps, so the process is the same. Where there are differences in the Windows example we will highlight them to help you follow along.

Run all of the following commands from a terminal on your Docker host.

Clone the repo locally. This will pull the application code to your local Docker host ready for you to containerize it.

Be sure to substitute the following repo with the Windows repo if you are following along with the Windows example.

$ git clone
Cloning into 'psweb'...
remote: Counting objects: 15, done.
remote: Compressing objects: 100% (11/11), done.
remote: Total 15 (delta 2), reused 15 (delta 2), pack-reused 0
Unpacking objects: 100% (15/15), done.
Checking connectivity... done.

Change directory into the cloned repo’s directory and list its contents.

$ cd psweb
$ ls -l
total 40
-rw-r--r--@ 1 ubuntu ubuntu  338 24 Apr 19:29 Dockerfile
-rw-r--r--@ 1 ubuntu ubuntu  396 24 Apr 19:32
-rw-r--r--@ 1 ubuntu ubuntu  341 24 Apr 19:29 app.js
-rw-r--r--  1 ubuntu ubuntu  216 24 Apr 19:29 circle.yml
-rw-r--r--@ 1 ubuntu ubuntu  377 24 Apr 19:36 package.json
drwxr-xr-x  4 ubuntu ubuntu  128 24 Apr 19:29 test
drwxr-xr-x  3 ubuntu ubuntu   96 24 Apr 19:29 views

The Linux example is a simple nodejs web app. The Windows example is an IIS server running some static HTML.

Both Git repos contain a file called Dockerfile. This is a plain-text document that tells Docker how to build an app and dependencies into a Docker image.

List the contents of the Dockerfile.

$ cat Dockerfile

FROM alpine
LABEL maintainer="[email protected]"
RUN apk add --update nodejs nodejs-npm
COPY . /src
RUN  npm install
ENTRYPOINT ["node", "./app.js"]

The contents of the Dockerfile in the Windows example are different. However, this isn’t important at this stage. For now, it’s enough to understand that each line represents an instruction that Docker uses to build an image.

At this point we have pulled some application code from a remote Git repo. We also have a Dockerfile containing instructions on how to build the app into a Docker image.

Use the docker image build command to create a new image using the instructions in the Dockerfile. This example creates a new Docker image called test:latest.

The command is the same for the Linux and Windows examples, and be sure to run it from within the directory containing the app code and Dockerfile.

$ docker image build -t test:latest .

Sending build context to Docker daemon  74.75kB
Step 1/8 : FROM alpine
latest: Pulling from library/alpine
88286f41530e: Pull complete
Digest: sha256:f006ecbb824...0c103f4820a417d
Status: Downloaded newer image for alpine:latest
 ---> 76da55c8019d
Successfully built f154cb3ddbd4
Successfully tagged test:latest

Note: It may take a long time for the build to finish in the Windows example. This is because of the image being pulled is several gigabytes in size.

Once the build is complete, check to make sure that the new test:latest image exists on your host.

$ docker image ls
REPO     TAG      IMAGE ID        CREATED         SIZE
test     latest   f154cb3ddbd4    1 minute ago    81.5MB

You have a newly-built Docker image with the app and dependencies inside.

Run a container from the image and test the app.

Linux example:

$ docker container run -d \
  --name web1 \
  --publish 8080:8080 \

Open a web browser and navigate to the DNS name or IP address of the Docker host that you are running the container from, and point it to port 8080. You will see the following web page.

If you are following along with Docker for Windows or Docker for Mac, you will be able to use localhost:8080 or If you’re following along on Play With Docker, you will be able to click the 8080 hyperlink above the terminal screen.

Figure 4.1
Figure 4.1

Windows example:

> docker container run -d \
  --name web1 \
  --publish 8080:80 \

Open a web browser and navigate to the DNS name or IP address of the Docker host that you are running the container from, and point it to port 8080. You will see the following web page.

The same rules apply if you’re following along with Docker Desktop or Play With Docker.

Figure 4.2
Figure 4.2

Well done. You’ve taken some application code from a remote Git repo and built it into a Docker image. You then ran a container from it. We call this “containerizing an app”.

Chapter Summary

In the Ops section of the chapter you downloaded a Docker image, launched a container from it, logged into the container, executed a command inside of it, and then stopped and deleted the container.

In the Dev section, you containerized a simple application by pulling some source code from GitHub and building it into an image using instructions in a Dockerfile. You then ran the containerized app.

This big picture view should help you with the up-coming chapters where we will dig deeper into images and containers.