Book Image

Docker High Performance - Second Edition

By : Allan Espinosa, Russ McKendrick
Book Image

Docker High Performance - Second Edition

By: Allan Espinosa, Russ McKendrick

Overview of this book

Docker is an enterprise-grade container platform that allows you to build and deploy your apps. Its portable format lets you run your code right from your desktop workstations to popular cloud computing providers. This comprehensive guide will improve your Docker work?ows and ensure your application's production environment runs smoothly. This book starts with a refresher on setting up and running Docker and details the basic setup for creating a Docker Swarm cluster. You will then learn how to automate this cluster by using the Chef server and cookbooks. After that, you will run the Docker monitoring system with Prometheus and Grafana, and deploy the ELK stack. You will also learn best practices for optimizing Docker images. After deploying containers with the help of Jenkins, you will then move on to a tutorial on using Apache JMeter to analyze your application's performance. You will learn how to use Docker Swarm and NGINX to load-balance your application, and how common debugging tools in Linux can be used to troubleshoot Docker containers. By the end of this book, you will be able to integrate all the optimizations that you have learned and put everything into practice in your applications.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

The importance of monitoring


Monitoring is important as it provides a source of feedback on the Docker deployment that we built. It provides an in-depth view of our application, from the performance of the low-level operating system to high-level business targets. Having proper instrumentation inserted in our Docker hosts allows us to identify our system's state. We can use this source of feedback to identify whether our application is behaving as originally planned.

If our initial hypothesis was incorrect, we can use the feedback data to revise our plan and change our system accordingly by tuning our Docker host and containers or updating our running Docker application. We can also use the same monitoring process to identify errors and bugs after our system is deployed to production.

Docker has built-in features to log and monitor. By default, a Docker host stores a Docker container's standard output and error streams to JSON files in /var/lib/docker/<container_id>/<container_id...