Book Image

Certified Kubernetes Administrator (CKA) Exam Guide

By : Mélony Qin
4 (1)
Book Image

Certified Kubernetes Administrator (CKA) Exam Guide

4 (1)
By: Mélony Qin

Overview of this book

Kubernetes is the most popular container orchestration tool in the industry. The Kubernetes Administrator certification will help you establish your credibility and enable you to efficiently support the business growth of individual organizations with the help of this open source platform. The book begins by introducing you to Kubernetes architecture and the core concepts of Kubernetes. You'll then get to grips with the main Kubernetes API primitives, before diving into cluster installation, configuration, and management. Moving ahead, you’ll explore different approaches while maintaining the Kubernetes cluster, perform upgrades for the Kubernetes cluster, as well as backup and restore etcd. As you advance, you'll deploy and manage workloads on Kubernetes and work with storage for Kubernetes stateful workloads with the help of practical scenarios. You'll also delve into managing the security of Kubernetes applications and understand how different components in Kubernetes communicate with each other and with other applications. The concluding chapters will show you how to troubleshoot cluster- and application-level logging and monitoring, cluster components, and applications in Kubernetes. By the end of this Kubernetes book, you'll be fully prepared to pass the CKA exam and gain practical knowledge that can be applied in your day-to-day work.
Table of Contents (17 chapters)
1
Part 1: Cluster Architecture, Installation, and Configuration
5
Part 2: Managing Kubernetes
10
Part 3: Troubleshooting

Monitoring on a cluster node

Monitoring is essential for Kubernetes administrators when it comes to getting a clear understanding of what’s going on in your Kubernetes cluster. You need to know all of the different metrics to help you get on track in terms of the health of your Kubernetes cluster components. You also need to make sure that your components are operating as expected and that all workloads that are deployed on your worker nodes are functional and have enough resources, such as CPU, memory, and storage. Moreover, you should also check whether any worker nodes are available and have sufficient resources to scale or schedule more workloads.

In Kubernetes, Metrics Server collects CPU/memory metrics and to some extent adjusts the resources needed by containers automatically. Metrics Server collects those metrics every 15 seconds from the kubelet agent and then exposes them in the API server of the Kubernetes master via the Metrics API. This process is described...