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

Installing and using Elasticsearch, Fluentd, and Kibana


Fluentd is software that's frequently used to collect and aggregate logging. Hosted at https://www.fluentd.org, like prometheus it is open source software that is managed under the umbrella of the Cloud Native Computing Foundation (CNCF). When it comes to talking about aggregating logs, the problem has existed long before containers, and ELK was a frequent acronym used to represent a solution, the combination of Elasticsearch, Logstash, and Kibana. When using containers, the number of log sources expands, making the problem of collecting all the logs even larger, and Fluentd evolved to support the same space as Logstash, focusing on structured logging with a JSON format, routing it, and supporting plugins to process the logs. Fluentd was written in Ruby and C, intending to be faster and more efficient than LogStash, and the same pattern is continuing with Fluent Bit (http://fluentbit.io), which has an even smaller memory footprint....