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
About the Author
About the Reviewer
Customer Feedback

The test system

In order to articulate a continuous delivery pipeline, we need a system to play with, and after some talks and demos, I have developed one that I tend to use, as it has pretty much no business logic and leaves a lot of space to think about the underlying infrastructure.

I call the system Chronos, and as you can guess, its purpose is related to the management of time zones and formats of dates. The system is very simple:

We have three services:

  • An API aggregator

  • A service that translates a timestamp into a date in ISO format

  • A service that translates a timestamp into a date in UTC format

These services work in coordination to translate a timestamp into a date in different formats, but it is also open to extensions as we can aggregate more services to add more capabilities and expose them through the API Aggregator.

Every service will be packed into a different Docker image, deployed as a Deployment in Kubernetes and exposed via Services (externals and internals) to the cluster and...