Book Image

DevOps with Kubernetes - Second Edition

By : Hideto Saito, Hui-Chuan Chloe Lee, Cheng-Yang Wu
Book Image

DevOps with Kubernetes - Second Edition

By: Hideto Saito, Hui-Chuan Chloe Lee, Cheng-Yang Wu

Overview of this book

Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure.
Table of Contents (14 chapters)

Summary

At the start of this chapter, we described how to get the status of running containers quickly by means of built-in functions such as kubectl. Then, we expanded the discussion to look at the concepts and principles of monitoring, including why, what, and how to monitor our application on Kubernetes. Afterward, we built a monitoring system with Prometheus as the core, and set up exporters to collect metrics from our application, system components, and Kubernetes units. The fundamentals of Prometheus, such as its architecture and query domain-specific language were also introduced, so we can now use metrics to gain insights into our cluster, as well as the applications running inside, to not only retrospectively troubleshoot, but also detect potential failures. After that, we described common logging patterns and how to deal with them in Kubernetes, and deployed an EFK stack...