Docker Image Size – Does It Matter?

Does Docker image size matter? The answer I usually hear is “yes”.
The logical question that follows is “why?”.

I’ve heard the following two answers too often for my liking:

Two Key Docker Benefits and How to Attain Them

In 2013, Solomon Hykes showed a demo of the first version of Docker during the PyCon conference in Santa Clara. Since then, the benefits of Docker containers have spread to seemingly every corner of the software industry. While Docker (the project and the company) made containers so popular, they were not the first project to leverage containers out there; and they are definitely not the last either.

System metrics with Docker, Telegraf, Influxdb and Grafana

We’ll use Docker, for the quick deployment our monitoring system, also it’ll gives us a freedom to use any software with dependency free and keep our system clean after. Topical, You can look at Docker from this side too, as a cross-platform package system.

Also, we’ll use part of Tick stack, namely an Influxdb base to store our metrics and Telegraf, like an agent on remote system, for nice and pretty graphs we’ll take Grafana.

Docker in Action

With Docker you can easily deploy a web application along with it’s dependencies, environment variables, and configuration settings - everything you need to recreate your environment quickly and efficiently.

We’ll start by creating a Docker container for running a Python Flask application. From there, we’ll look at a nice development workflow to manage the local development of an app as well as continuous integration and delivery, step by step …

Offline Python Deployments With Docker

In cases when a production server does not have access to the Internet or to the internal network, you will need to bundle up the Python dependencies (as wheel files) and interpreter along with the source code.

Objectives

By the end of this post, you will be able to…

1. Describe the difference between a Python wheel and egg
2. Explain why you may want to build Python wheel files within a Docker container
3. Spin up a custom environment for building Python wheels using Docker
4. Bundle and deploy a Python project to an environment without access to the Internet
5. Explain how this deployment setup can be considered immutable

Continuous Integration With Python: An Introduction

What Is Continuous Integration?

Continuous integration (CI) is the practice of frequently building and testing each change done to your code automatically and as early as possible. Prolific developer and author Martin Fowler defines CI as follows:

“Continuous Integration is a software development practice where members of a team integrate their work frequently, usually each person integrates at least daily - leading to multiple integrations per day. Each integration is verified by an automated build (including test) to detect integration errors as quickly as possible.” (Source)

Comandos frecuentes de Docker ;)

Los contenedores son para Maquinas Virtuales como los threads son para los procesos. O puedes pensar en ellos como chroots en esteroides.

Lifecycle

• docker create crea un contenedor pero no lo comienza.
• docker rename permite renombrar al contenedor.
• docker run crea y comienza un contenedor en una operación.
• docker rm borra un contenedor.
• docker update actualiza los recursos limitados de un contenedor.

Lifecycle of docker container

Image Source and Credits: http://docker-saigon.github.io/post/Docker-Internals/