Book Image

The Complete Kubernetes Guide

By : Jonathan Baier, Gigi Sayfan, Jesse White
Book Image

The Complete Kubernetes Guide

By: Jonathan Baier, Gigi Sayfan, Jesse White

Overview of this book

If you are running a number of containers and want to be able to automate the way they’re managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: • Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White • Mastering Kubernetes - Second Edition by Gigi Sayfan
Table of Contents (26 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Detecting node problems


In Kubernetes' conceptual model, the unit of work is the pod. However, pods are scheduled on nodes. When it comes to monitoring and reliability, the nodes are what require the most attention, because Kubernetes itself (the scheduler and replication controllers) takes care of the pods. Nodes can suffer from a variety of problems that Kubernetes is unaware of. As a result, it will keep scheduling pods to the bad nodes and the pods might fail to function properly. Here are some of the problems that nodes may suffer while still appearing functional:

  • Bad CPU
  • Bad memory
  • Bad disk
  • Kernel deadlock
  • Corrupt filesystem
  • Problems with the Docker daemon

The kubelet and cAdvisor don't detect these issues, another solution is needed. Enter the node problem detector.

Node problem detector

The node problem detector is a pod that runs on every node. It needs to solve a difficult problem. It needs to detect various problems across different environments, different hardware, and different OSes...