Book Image

Implementing Modern DevOps

By : Danny Varghese, David Gonzalez
Book Image

Implementing Modern DevOps

By: Danny Varghese, David Gonzalez

Overview of this book

This book follows a unique approach to modern DevOps using cutting-edge tools and technologies such as Ansible, Kubernetes, and Google Cloud Platform. This book starts by explaining the organizational alignment that has to happen in every company that wants to implement DevOps in order to be effective, and the use of cloud datacenters in combination with the most advanced DevOps tools to get the best out of a small team of skilled engineers. It also delves into how to use Kubernetes to run your applications in Google Cloud Platform, minimizing the friction and hassle of maintaining a cluster but ensuring its high availability. By the end of this book, you will be able to realign teams in your company and create a Continuous Delivery pipeline with Kubernetes and Docker. With strong monitoring in place, you will also be able to react to adverse events in your system, minimizing downtime and improving the overall up-time and stability of your system.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Docker volumes


So far, we have seen how to create images, how to store the images in a registry, and how Docker images work in general (layers and containers versus images). An important part of any application is the storage. In general, Docker applications should be stateless, but with the new orchestration software, such as Kubernetes, Docker Swarm, and similar, every day, more and more engineers are moving toward containerized databases. Docker solves this problem in a very elegant way: you can mount a folder from the local machine into the container as if it were a normal folder. This is a very powerful abstraction as it leverages the ability to push data out of the container to be saved into a Network Attached Storage (NAS) or any other storage technology (it is possible to use a bucket in the Google Cloud Storage or S3 as the volume mounted in a container).

Let's start with the basics. Just run a MySQL database:

docker run --name my-mysql -e MYSQL_ROOT_PASSWORD=my-secret-pw -d mysql...