Using Docker to Simplify Devops and Application Deployment


As cloud environments are maturing and growing more complex, developers are increasingly embracing distributed microservice architecture for fast software development and delivery. DevOps engineers now prefer containers to simplify and automate the continuous deployment of their applications to the cloud.   

Container technology is gaining momentum in the software industry. This is due to the increasing virtualization, decreasing reliance on operating systems in the cloud, and the establishment of Linux.

Containerization helps software applications to run reliably when moving between different computing environments. This could be from the developer’s laptop, staging servers on-premise to virtual machines and server less environments in the cloud. This makes applications to function identically in every environment.

Docker is the most popular, open-source container that automates and streamlines the deployment of cloud applications in software containers. This allows engineers to pack, manage, and distribute applications inside software containers easily.                                                                                                                                                

To understand how Docker simplifies the deployment of applications in the cloud, let’s first discuss the role of containerization in the software industry.

What are Containers, and how do they differ from virtual machines?

Agile methodologies used in the DevOps world involve frequent and incremental changes in coding. Therefore, DevOps engineers frequently move apps from a testing environment to a production environment to ensure an appropriate deployment model.

Problems occur when the supporting software environment is not the same in all environments. You test the application using Python and then run it Debian. Perhaps you use a certain version of an SSL library, and the support environment uses another version. Besides the supporting environment, the network topology, security policies, and storage might also vary.

The initial solution to this problem is virtualization. It allows multiple operating systems to run independently on one physical machine. The hypervisor software used in this technology encapsulates a guest version of the OS and emulates hardware resources like server CPU, hard disk, memory that can be shared across multiple virtual machines.

Therefore, multiple operating systems can be run on a single machine. However, virtual machines are heavy and take up a lot of system resources.  

This is when containers step in.

A container bundles an application with all its libraries, dependencies, configuration files and everything necessary for running it, into a single package. It abstracts away the application, its dependencies, differences in OS distributions, and the underlying infrastructure.

What is Docker?

 Solomon Hykes at dotCloud released Docker in 2013, and the project exploded in popularity in 2014.

Docker makes it easy to code, deploy, and run applications on the cloud using containers. Developers can ship an application with all libraries and dependencies in one package to the cloud. This assures that the app will run on any Linux machine regardless of customized settings that could differ from the system used for code development and testing.

As of August 2019, over 105 billion Docker downloads have occurred. Github has “starred” Docker 32,000 times on the platform. The technology has 750+ Docker Enterprise Customers, including big brands like Spotify, VISA, ING, PayPal, to name a few.

The basic terminologies of Docker include:

Docker Images

Each Docker container is instantiated from an image pulled from a Docker registry. You can create many containers using one image. This image determines which component of the application will run in the container and how.

You can create an image from a container, and share these specifications with others so that the app runs the same way in all environments.


A Dockerfile is a text file that contains the commands required to assemble an image. These commands can be configured to use various software versions and dependencies stable code deployments.

These commands are:

  •       ADD – copy files from the host to the container’s own filesystem.
  •       CMD – execute a command.
  •       ENTRYPOINT – set a default app that will be used when a container is created with the image.
  •       EXPOSE – expose the networking port between the container and the outside world.
  •       USER – setting the username (UID) that will run the container.
  •       ENV – set environment variables.
  •       FROM – define the base image for the build process.
  •       MAINTAINER – defines the name and email ID of the image creator.
  •       RUN – Dockerfiles central executing directive
  •       VOLUME – provide access from the container to a directory on the host machine.
  •       WORKDIR – set the path for the CMD command execution.

Docker Swarm

Docker Swarm serves as a clustering tool for Docker containers. Using this tool, coders and IT administrators create and manage clusters of Docker nodes.

The Swarm manager automatically adopts the cluster by adding or removing tasks to maintain its state. The manager uses ingress load balancing to expose services it can use.

Benefits of Docker

 There are a lot of benefits to using Docker as part of your Devops process. They include: 

Simplifying Configuration

 VMs offer the ability to run any platform with its own configuration on your infrastructure.

Docker also offers the same ability but without involving virtual machines. With this technology, you can put your Docker configuration into code and deploy it.  You can use one configuration in various environments, and this decouples infrastructure requirements from the software environment. 

Docker gives you the freedom to run your application across IaaS/PaaS without any changes.

Continuous Deployment and Testing

Because Docker containers consist of all configurations internally, teams use the same container for different environments. This ensures no discrepancies or manual intervention.

Instead of requiring the same production environment, developers can use their own system to run containers on VirtualBox.

It’s easy to upgrade and test containers and implement the changes to existing containers. You can build, test, release, and deploy images on multiple servers.

Eases The Microservices Architecture

 Portable, lightweight, and self-contained Docker makes it easy to work with microservices. This architecture breaks traditional monolithic applications into many smaller, loosely coupled components.

Each component can be scaled, modified, tested, and serviced independently, by separate teams at different times. Docker containers fit the microservices approach and to agile development processes generally.

Multi-Cloud Platforms

Most renowned computing services, including Google Compute Platform (GCP) and Amazon Web Services (AWS), have embraced Docker. Containers run on Amazon EC2 instances, Rackspace or VirtualBox server, Google Compute Engine instance, if the OS supports Docker. These containers can be ported between various environments while achieving similar consistency and functionality.

Dockers work well with other cloud services like Microsoft Azure, and OpenStack, configuration managers such as Chef, Puppet, and Ansible, etc.


Docker ensures that applications running on containers are completely isolated from each other, giving developers full control over traffic management. Each container has unique resources ranging from processing to network stacks.

For security purposes, OS-sensitive mount points serve as read-only mount points in Docker containers. A copy-on-write file system ensures that a container can’t look into the process running inside another container. It also limits system calls to the host OS and works well with AppArmor and SELinux.  

Moreover, each Docker image is digitally signed for authenticity. Since each Docker container is isolated, it never affects applications running on other containers, even if someone hacks your application running on one container.

Environment Standardization

Dockers ensure consistency across multiple development and release cycles, standardizing your environment. Standardized service infrastructure allows teams to work in a production parity environment, and engineers can efficiently analyze and debug the application.

Parity, in the context of Docker, means your images run similarly on all servers and laptops. For developers, this means:

  •       less time spent setting up environments
  •       saving time on debugging environment-related issues
  •       a highly portable and easy-to-set-up codebase.
  •       reliable and easy-to-maintain production infrastructure

This saves time on identifying and fixing bugs, thus allowing more time for development.

When Should I use Docker?

 Docker is a good fit for you want to run multiple apps on a single server while preventing dependency management issues. It offers an isolated environment to start a new tool without spending time on installation and configuration.

If your developers work with different setups, Docker makes it easy to have a local development environment that matches the production environment without needing to secure shell.

Cases such as using a reverse proxy, hosting a site using a LAMP stack or setting up a Minecraft server have an official image on DockerHub. If the default configuration of these images meets your needs, they can save you a lot of time establishing the environment and installing all the required tools.

Docker containers may not be useful if your app is complicated. Also, if performance and security are critical to your app, using Docker may not be a good idea as it can raise some unique challenges.

Note that Docker is not a substitute for configuration management or systems engineering. DevOps engineers should avoid containerization for every application they develop only because Docker is a popular solution. As with any technology, you must first analyze the requirements of your application before deciding whether to use the Docker containerization approach. 

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