You might be wondering what this Docker is all about. So let me tell you that Docker, which is a source code for the Core Docker project, is nothing but an infrastructure management platform that is required for running as well as the deployment of software. The main motive behind using Docker is that containers of an OS system level are used as an abstraction layer on top of the application and deployment operations.
The best part of Docker is that it can package up applications along with all the required operating system dependencies for flexible deployment across environments. Moreover, it has also been noticed that in the long run, Docker has the potential to act as an abstraction layer. With this, it can easily run on any of the servers irrespective of the server on which it is about to be hosted.
In addition, to all this, you will be amazed to know that within just five years of release, Docker has gained tremendous popularity by the user. As per the Docker official report, there are more than three and half million apps that have been containerized with the help of this technology. And also, there are more than fifteen thousand Docker-related jobs which are listed on Linkedin.
Talking about its benefits, you will find that Docker is highly efficient. The reason behind it is that Docker makes use of the shared operating system, and thus it leaves behind unnecessary padding that is associated with the virtual machines. This all helps to make Docker a cost-effective as well as faster application. As per the user experience, Docker works best with a web application such as Flask or Django.
You might be wondering how Docker can be used with the python application tool. So the first thing which we need to do is write an application that is just similar to Docker’s welcome world. It can be said that the main motive behind this program is to print the welcome world message. This should only be displayed when we try to execute the container with the help of an app that is completely based on Python with Docker.
In order to do this, the first thing which we need to do is create a new project. This could only be done when you create a new file that is named main.py and then write the main code to it. Here, our main code is to display a welcome world. After the coding part is done then the next thing which needs to be done is the creation of a Docker file. For this, there is a set of code that you need to enter; the code explains the version of python that you are using, followed by the RUN, work directory, copy, and the entry point. Let me explain in brief all the points.
As mentioned earlier, Python with Docker streamlines the development lifecycles just by enabling the developers to work in a standardized environment with the help of a local container that provides services and applications. Moreover, it has also been noted that containers are great for the continuous integration and delivery of the workflows. For instance, just think of a scenario where you will write a code locally and then share the same with your colleague with the use of a Python Docker Container. After which, Docker Python is used for pushing the application into the test environment. There manual or automated tests are performed where bugs are encountered and fixed so that they could be deployed again to the test environment and thereafter to the higher environment. Thus, it can be said that with Docker, there is a faster way of delivery of the application.
You will be astonished to know that Docker allows an individual for a higher portable workload. In addition to this, Docker can be executed on the local laptop of the developers or on any virtual machine. Thus, you can easily manage your workload with it. If you have any intention of scaling up or tearing down the application, then it has been made easy with Docker.
Moreover, Docker Python also provides a platform that helps to manage the lifecycle of a container.
Micropyramid is a software development and cloud consulting partner for enterprise businesses across the world. We work on python, Django, Salesforce, Angular, Reactjs, React Native, MySQL, PostgreSQL, Docker, Linux, Ansible, git, amazon web services. We are Amazon and salesforce consulting partner with 5 years of cloud architect experience. We develop e-commerce, retail, banking, machine learning, CMS, CRM web and mobile applications.
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