Book Image

Mastering Kubernetes - Third Edition

By : Gigi Sayfan
Book Image

Mastering Kubernetes - Third Edition

By: Gigi Sayfan

Overview of this book

The third edition of Mastering Kubernetes is updated with the latest tools and code enabling you to learn Kubernetes 1.18’s latest features. This book primarily concentrates on diving deeply into complex concepts and Kubernetes best practices to help you master the skills of designing and deploying large clusters on various cloud platforms. The book trains you to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. With the two new chapters, you will gain expertise in serverless computing and utilizing service meshes. As you proceed through the chapters, you will explore different options for network configuration and learn to set up, operate, and troubleshoot Kubernetes networking plugins through real-world use cases. Furthermore, you will understand the mechanisms of custom resource development and its utilization in automation and maintenance workflows. By the end of this Kubernetes book, you will graduate from an intermediate to advanced Kubernetes professional.
Table of Contents (19 chapters)
17
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18
Index

Logging with Kubernetes

We need to carefully consider our logging strategy with Kubernetes. There are several types of logs that are relevant for monitoring purposes. Our workloads run in containers, of course, and we care about these logs, but we also care about the logs of Kubernetes components such as kubelets and the container runtime. In addition, chasing logs across multiple nodes and containers is a non-starter. The best practice is to use central logging (also known as log aggregation). There are several options here that we will explore soon.

Container logs

Kubernetes stores the standard output and standard error of every container. They are made available through the kubectl logs command.

Here is a pod manifest that prints the current date and time every 10 seconds:

apiVersion: v1
kind: Pod
metadata:
  name: now
spec:
  containers:
    - name: now
      image: g1g1/py-kube:0.2
      command: ["/bin/bash", "-c", "while true; do sleep...