Docker

Hey guys welcome to week 4 blog. This week I am going to talk about Docker and why is Important. we learn about this in last few classes and I am writing about this platform because it help me and you getting deep understand about how to operate and use this application in seitan way. so let’s start this with what is Docker? so docker is tool that designed to make it easier to create, deploy, and run application by using Containers. It includes packages, libraries and other dependencies. You probably wondering how this Work. Well it’s work on Virtual machine. It kind a uses Linux machine. And importantly, it’s open source!!!

you wondering, who is Docker for? Docker is a tool that is designed to benefit both developers and system administrators, making it a part of many DevOps toolchains. For example developers can focused on writing code without worrying about the system that it will ultimately be running on. it also allows them to get a head start by using one of thousands of programs already designed to run in docker to run in Docker containers part of the application. I have used programing platform call QT. Qt is software development platform where you can write code and make you own application and it require a C++ language to run your software. but Docker run on command line. this make developer really easy to developer application and Quicker too.

This are the three processing tools that you need to run docker. Every Docker container starts with a simple text file containing instructions for how to build the Docker container image. Docker File automates the process of Docker image creation. It’s essentially a list of commands that Docker Engine will run in order to assemble the image. then docker images Docker images contain executable application source code as well as all the tools, libraries, and dependencies that the application code needs to run as a container. When you run the Docker image, it becomes one instance (or multiple instances) of the container. Docker containers are the live, running instances of Docker images. While Docker images are read-only files, containers are live, ephemeral, executable content. Users can interact with them, and administrators can adjust their settings and conditions.

This container can be thought of as necessitating three categories of software: Builder, Engine, and Orchestration. the main point of using this is making application build faster and docker is way to do it.

Now I will tell you why Docker is good for data Science. When I started as a Data Scientist my focus was always on finding the best algorithm by conducting experiments that would improve my model’s performance. I never really thought much about how I would share my findings and code with others, other than Most of this was the environment setup. In many cases, it would be time-consuming and I would give up and get on a call with the main Developer. when you data Scientist you deal with data a lot and also as algorithms. when you run data in Docker you build Docker Image , Run Image.

Sours: https://opensource.com/tags/docker

https://www.docker.com/blog/

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