Understanding Container Scenarios and Overview of Docker

17 min read

Docker is one of the recent most successful open source project which provides packaging, shipping, and running any application as light weight containers. We can actually compare Docker containers as shipping containers that provides standard consistent way of shipping any application. Docker is fairly a new project and with help of this article it will be easy to troubleshoot some of the common problems which Docker users face while installing and using Dockers containers.

In this article by Rajdeep Dua, Vaibhav Kohli, and John Wooten authors of the book Troubleshooting Docker, the emphasis will be on the following topics;

  • Decoding containers
  • Diving into Docker
  • Advantages of Docker containers
  • Docker lifecycle
  • Docker design patterns
  • Unikernels

(For more resources related to this topic, see here.)

Decoding containers

Containerization are an alternative to virtual machine which involves encapsulation of applications and providing it with its own operating environment. The basic foundation for containers is Linux containers (LXC) which is user space interface for Linux Kernel containment features. With help of powerful API and simple tools it lets Linux users create and manage application containers. LXC containers are in-between of chroot and full-fledged virtual machine. Another key difference with containerization from traditional hypervisor’s is that containers share the Linux Kernel used by operating system running the host machine, thus multiple containers running in the same machine uses the same Linux Kernel. It gives the advantage of being fast with almost zero performance overhead compared to VMs.

Major use cases of containers are listed in the further sections.

OS container

OS containers can be easily imagined as a Virtual Machine (VM) but unlike a VM they share the Kernel of the host operating system but provide user space isolation. Similar to a VM dedicated resources can be assigned to containers and we can install, configure and run different application, libraries, and so on. Just as you would run on any VM. OS containers are helpful in case of scalability testing where fleet of containers can be deployed easily with different flavors of distros, which is very less expensive compared to deployment of VM’s. Container are created from templates or images that determine the structure and contents of the container. It allows to create a container with identical environment, same package version, and configuration across all containers mostly used in case of dev environment setups.

There are various container technologies like LXC, OpenVZ , Docker, and BSD jails which are suitable for OS containers.

Troubleshooting Docker

Figure 1: OS based container

Application containers

Application containers are designed to run a single service in the package, while OS containers which are explained previously can support multiple processes. Application containers are getting lot of attraction after launch of Docker and Rocket.

Whenever container is launched it runs a single process. This process runs an application process but in case of OS containers it runs multiple services on the same OS. Containers usually have a layered approach as in case of Docker container which helps in reduced duplication and increased re-use. Container can be started with base image common for all components and then we can go on adding layers in the file system that are specific to the component. Layered file system helps to rollback changes as we can simple switch to old layers if required. The run command which is specified in Dockerfile adds a new layer for the container.

The main purpose of application containers is to package different component of the application in separate container. The different component of the application which are packaged separately in container then interact with help of API’s and services. The distributed multi-component system deployment is the basic implementation of micro-service architecture. In the preceding approach developer gets the freedom to package the application as per his requirement and IT team gets the privilege to deploy the container on multiple platforms in order to scale the system both horizontally as well as vertically.

Hypervisor is virtual machine monitor (VMM), used to allow multiple operation system to run and share the hardware resources from the host. Each virtual machine is termed as guest machine.

The following simple example explains the difference between application container and OS containers:

Troubleshooting Docker

Figure 2: Docker layers

Let’s consider the example of web three-tier architecture we have a database tier such as MySQL, Nginx for load balancer and application tier as Node.js:

Troubleshooting Docker

Figure 3: OS container

In case of OS container we can pick up by default Ubuntu as the base container and install services MySQL, Nginx, Node.js using Dockerfile. This type of packaging is good for testing or for development setup where all the services are packaged together and can be shipped and shared across developer’s. But deploying this architecture for production cannot be done with OS containers as there is no consideration of data scalability and isolation. Application containers helps to meet this use case as we can scale the required component by deploying more application specific containers and it also helps to meet load-balancing and recovery use-case. For the preceding three-tier architecture each of the services will be packaged into separate containers in order to fulfill the architecture deployment use-case.

Troubleshooting Docker

Figure 4: Application containers scaled up

Main difference between OS and application containers are:

OS container

Application container

Meant to run multiple services on same OS container

Meant to run single service

Natively, No layered filesystem

Layered filesystem

Example: LXC, OpenVZ, BSD Jails

Example: Docker, Rocket

Diving into Docker

Docker is a container implementation that has gathered enormous interest in recent years. It neatly bundles various Linux Kernel features and services like namespaces, cgroups, SELinux, and AppArmor profiles and so on with Union files systems like AUFS, BTRFS to make modular images. These images provides highly configurable virtualized environment for applications and follows write-once-run-anywhere principle. Application can be as simple as running a process to a highly scalable and distributed processes working together.

Docker is getting a lot of traction in industry, because of its performance savvy, and universal replicability architecture, meanwhile providing the following four cornerstones of modern application development:

  • Autonomy
  • Decentralization
  • Parallelism
  • Isolation

Furthermore, wide-scale adaptation of Thoughtworks’s micro services architecture or Lots of Small Applications (LOSA) is further bringing potential in Docker technology. As a result, big companies like Google, VMware, and Microsoft have already ported Docker to their infrastructure, and the momentum is continued by the launch of myriad of Docker startups namely Tutum, Flocker, Giantswarm and so on.

Since Docker containers replicate their behavior anywhere, be it your development machine, a bare-metal server, virtual machine, or datacenter, application designers can focus their attention on development, while operational semantics are left with Devops. This makes team workflow modular, efficient and productive. Docker is not to be confused with VM, even though they are both virtualization technologies. Where Docker shares an OS, meanwhile providing sufficient level of isolation and security to applications running in containers, later completely abstracts out OS and gives strong isolation and security guarantees. But Docker resource footprint is minuscule in comparison to VM, and hence preferred for economy and performance. However, it still cannot completely replace VM, and hence is complementary to VM technology:

Troubleshooting Docker

Figure 5: VM and Docker architecture

Advantages of Docker containers

Following listed are some of the advantages of using Docker containers in Micro-service architecture:

  • Rapid application deployment: With minimal runtime containers can be deployed quickly because of the reduced size as only application is packaged.
  • Portability: An application with its operating environment (dependencies) can be bundled together into a single Docker container that is independent from the OS version or deployment model. The Docker containers can be easily transferred to another machine that runs Docker container and executed without any compatibility issues. As well Windows support is also going to be part of future Docker releases.
  • Easily sharable: Pre-built container images can be easily shared with help of public repositories as well as hosted private repositories for internal use.
  • Lightweight footprint: Even the Docker images are very small and have minimal footprint to deploy new application with help of containers.
  • Reusability: Successive versions of Docker containers can be easily built as well as roll-backed to previous versions easily whenever required. It makes them noticeably lightweight as components from the pre-existing layers can be reused.

Docker lifecycle

These are some of the basic steps involved in the lifecycle of Docker container:

  1. Build the Docker image with help of Dockerfile which contains all the commands required to be packaged. It can run in the following way:

    Docker build
  2. Tag name can be added in following way:

    Docker build -t username/my-imagename
  3. If Dockerfile exists at different path then the Docker build command can be executed by providing –f flag:

    Docker build -t username/my-imagename -f /path/Dockerfile
  4. After the image creation, in order to deploy the container Docker run can be used. The running containers can be checked with help of Docker pscommand, which list the currently active containers.

    There are two more commands to be discussed;

    • Docker pause: This command used cgroups freezer to suspend all the process running in container, internally it uses SIGSTOP signal. Using this command process can be easily suspended and resumed whenever required.
    • Docker start: This command is used to either start the paused or stopped container.
  5. After the usage of container is done it can either be stopped or killed; Docker stop: command will gracefully stop the running container by sending SIGTERM and then SIGKILL command. In this case container can still be listed by using Docker ps –a command.

  6. Docker kill will kill the running container by sending SIGKILL to main process running inside the container.

  7. If there are some changes made to the container while it is running, which are likely to be preserved, container can be converted back to image by using the Docker commit after container has been stopped.

Troubleshooting Docker

Figure 6: Docker lifecycle

Docker design patterns

Following listed are some of the Docker design patterns with examples. Dockerfile is the base structure from which we define a Docker image it contains all the commands to assemble an image. Using Docker build command we can create automated build that executes all the previously mentioned command-line instructions to create an image:

$ Docker build
Sending build context to Docker daemon  6.51 MB

Design patterns listed further can help in creating Docker images that persist in volumes and provides various other flexibility so that they can be re-created or replaced easily at any time.

The base image sharing

For creating a web-based application or blog we can create a base image which can be shared and help to deploy the application with ease. This patterns helps out as it tries to package all the required services on top of one base image, so that this web application blog image can be re-used anywhere:

FROM debian:wheezy
    RUN apt-get update
    RUN apt-get -y install ruby ruby-dev build-essential git
    # For debugging
    RUN apt-get install -y gdb strace
    # Set up my user
    RUN useradd vkohli -u 1000 -s /bin/bash --no-create-home
    RUN gem install -n /usr/bin bundler
    RUN gem install -n /usr/bin rake
    WORKDIR /home/vkohli/
    ENV HOME /home/vkohli
    VOLUME ["/home"]
    USER vkohli
    EXPOSE 8080

The preceding Dockerfile shows the standard way of creating an application-based image.

Docker image is a zipped file which is a snapshot of all the configuration parameters as well as the changes made in the base image (Kernel of the OS).

It installs some specific tools (Ruby tools rake and bundler) on top of Debian base image. It creates a new user adds it to the container image and specifies the working directory by mounting /home directory from the host which is explained in detail in next section.

Shared volume

Sharing the volume at host level allows other containers to pick up the shared content required by them. This helps in faster rebuilding of Docker image or add/modify/remove dependencies. Example if we are creating the homepage deployment of the previously mentioned blog only directory required to be shared is /home/vkohli/src/repos/homepage directory with this web app container through the Dockerfile in the following way:

FROM vkohli/devbase
          WORKDIR /home/vkohli/src/repos/homepage
          ENTRYPOINT bin/homepage web

For creating the dev version of the blog we can share the folder /home/vkohli/src/repos/blog where all the related developer files can reside. And for creating the dev-version image we can take the base image from pre-created devbase:

FROM vkohli/devbase
USER root
# For Graphivz integration
RUN apt-get update
RUN apt-get -y install graphviz xsltproc imagemagick
       USER vkohli
         WORKDIR /home/vkohli/src/repos/blog
         ENTRYPOINT bundle exec rackup -p 8080

Dev-tools container

For development purpose we have separate dependencies in dev and production environment which easily gets co-mingled at some point. Containers can be helpful in differentiating the dependencies by packaging them separately. As shown in the following example we can derive the dev tools container image from the base image and install development dependencies on top of it even allowing ssh connection so that we to work upon the code:

FROM vkohli/devbase
RUN apt-get update
RUN apt-get -y install openssh-server emacs23-nox htop screen

# For debugging
RUN apt-get -y install sudo wget curl telnet tcpdump
# For 32-bit experiments
RUN apt-get -y install gcc-multilib 
# Man pages and "most" viewer:
RUN apt-get install -y man most
RUN mkdir /var/run/sshd
ENTRYPOINT /usr/sbin/sshd -D
VOLUME ["/home"]

As can be seen previously basic tools such as wget, curl, tcpdump are installed which are required during development. Even SSHD service is installed which allows to ssh connection into the dev container.

Test environment container

Testing the code in different environment always eases the process and helps to find more bugs in isolation. We can create a ruby environment in separate container to spawn a new ruby shell and use it to test the code base:

FROM vkohli/devbase
RUN apt-get update
RUN apt-get -y install ruby1.8 git ruby1.8-dev

In the preceding Dockerfile we are using the base image as devbase and with help of just one command Docker run can easily create a new environment by using the image created from this Dockerfile to test the code.

The build container

We have built steps involved in the application that are sometimes expensive. In order to overcome this we can create a separate a build container which can use the dependencies needed during build process. Following Dockerfile can be used to run a separate build process:

FROM sampleapp
RUN apt-get update
RUN apt-get install -y build-essential [assorted dev packages for libraries]
VOLUME ["/build"]
WORKDIR /build
CMD ["bundler", "install","--path","vendor","--standalone"]

/build directory is the shared directory that can be used to provide the compiled binaries also we can mount the /build/source directory in the container to provide updated dependencies. Thus by using build container we can decouple the build process and final packaging part in separate containers. It still encapsulates both the process and dependencies by breaking the previous process in separate containers.

The installation container

The purpose of this container is to package the installation steps in separate container. Basically, in order to provide deployment of container in production environment.

Sample Dockerfile to package the installation script inside Docker image as follows:

ADD installer /installer
CMD /installer.sh

The installer.sh can contain the specific installation command to deploy container in production environment and also to provide the proxy setup with DNS entry in order to have the cohesive environment deployed.

Service-in-a-box container

In order to deploy the complete application in a container we can bundle multiple services to provide the complete deployment container. In this case we bundle web app, API service and database together in one container. It helps to ease the pain of inter-linking various separate containers:

    git_url: [email protected]:vkohli/sampleapp.git
    git_branch: test   
    command: rackup -p 3000               
    build_command: rake db:migrate        
    deploy_command: rake db:migrate       
    log_folder: /usr/src/app/log          
    ports: ["3000:80:443", "4000"]        
    volumes: ["/tmp:/tmp/mnt_folder"]     
    health: default
    image: quay.io/john/node              
    command: node test.js                 
    ports: ["1337:8080"]                  
    requires: ["web"]                     
  - "mysql"                               
  - "redis"

Infrastructure container

As we have talked about the container usage in development environment, there is one big category missing the usage of container for infrastructure services such as proxy setup which provides a cohesive environment in order to provide the access to application. In the following mentioned Dockerfile example we can see that haproxy is installed and links to its configuration file is provided:

FROM debian:wheezy
ADD wheezy-backports.list /etc/apt/sources.list.d/
RUN apt-get update
RUN apt-get -y install haproxy
ADD haproxy.cfg /etc/haproxy/haproxy.cfg
CMD ["haproxy", "-db", "-f", "/etc/haproxy/haproxy.cfg"]

Haproxy.cfg is the configuration file responsible for authenticating a user:

backend test
    acl authok http_auth(adminusers)
    http-request auth realm vkohli if !authok
    server s1


Unikernels compiles source code into a custom operating system that includes only the functionality required by the application logic producing a specialized single address space machine image, eliminating unnecessary code. Unikernels is built using library operating system, which has the following benefits compared to traditional OS:

  • Fast Boot time: Unikernels make provisioning highly dynamic and can boot in less than second.
  • Small Footprint: Unikernel code base is smaller than the traditional OS equivalents and pretty much easy to manage.
  • Improved security: As unnecessary code is not deployed, the attack surface is drastically reduced.
  • Fine-grained optimization: Unikernels are constructed using compile tool chain and are optimized for device drivers and application logic to be used.

Unikernels matches very well with the micro-services architecture as both source code and generated binaries can be easily version-controlled and are compact enough to be rebuild. Whereas on other side modifying VM’s is not permitted and changes can be only made to source code which is time-consuming and hectic. For example, if the application doesn’t require disk access and display facility. Unikernels can help to remove this unnecessary device drivers and display functionality from the Kernel. Thus production system becomes minimalistic only packaging the application code, runtime environment and OS facilities which is the basic concept of immutable application deployment where new image is constructed if any application change is required in production servers:

Troubleshooting Docker

Figure 7: Transition from traditional container to Unikernel based containers

Container and Unikernels are best fit for each other. Recently, Unikernel system has become part of Docker and the collaboration of both this technology will be seen sooner in the next Docker release. As it is explained in the preceding diagram the first one shows the traditional way of packaging one VM supporting multiple Docker containers. The next step shows 1:1 map (one container per VM) which allows each application to be self-contained and gives better resource usage but creating a separate VM for each container adds an overhead. In the last step we can see the collaboration of Unikernels with the current existing Docker tools and eco-system, where container will get the Kernel low-library environment specific to its need.

Adoption of Unikernels in Docker toolchain will accelerate the progress of Unikernels and it will be widely used and will be understood as packaging model and runtime framework making Unikernels as another type of container. After the Unikernels abstraction for Docker developers, we will be able to choose either to use traditional Docker container or use the Unikernel container in order to create the production environment.


In this article we studied about the basic containerization concept with help of application and OS-based containers. And the differences between them explained in this article will clearly help the developers to choose the containerization approach which fits perfectly for their system. We have thrown some light around the Docker technology, its advantages and lifecycle of Docker container. The eight Docker design patterns explained in this article clearly shows the way to implement Docker containers in production environment.

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