Book Image

Kubernetes for Developers

By : Joseph Heck
Book Image

Kubernetes for Developers

By: Joseph Heck

Overview of this book

Kubernetes is documented and typically approached from the perspective of someone running software that has already been built. Kubernetes may also be used to enhance the development process, enabling more consistent testing and analysis of code to help developers verify not only its correctness, but also its efficiency. This book introduces key Kubernetes concepts, coupled with examples of how to deploy and use them with a bit of Node.js and Python example code, so that you can quickly replicate and use that knowledge. You will begin by setting up Kubernetes to help you develop and package your code. We walk you through the setup and installation process before working with Kubernetes in the development environment. We then delve into concepts such as automating your build process, autonomic computing, debugging, and integration testing. This book covers all the concepts required for a developer to work with Kubernetes. By the end of this book, you will be in a position to use Kubernetes in development ecosystems.
Table of Contents (16 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

A Kubernetes concept – DaemonSet


A Kubernetes resource that we have now used (through Helm) is DaemonSet. This resource is a wrapper around pods very similar to ReplicaSet, but with the purpose of running a pod on every node in a cluster. When we installed Prometheus using Helm, it created a DaemonSet to run node-collector on each node within the Kubernetes cluster.

There are two common patterns for running software in a support role with your application: the first is using the side-car pattern, and the second is using a DaemonSet. A side-car is when you include a container within your pod whose sole purpose is to run alongside the primary application and provide some supporting, but external, role. An example of a useful side-car might be a cache, or a proxy service of some form. Running a side-car application obviously increases the resources needed for a pod, and if the number of pods is relatively low or they are sparse compared to the size of a cluster, this would be the most efficient...