You're reading from Hands-on Kubernetes on Azure, Third Edition Use Azure Kubernetes Service to automate management, scaling, and deployment of containerized applications

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781801079945

Length 528 pages

Edition 3rd Edition

Languages

JavaScript

Tools

Azure

Concepts

Containerization

Authors (3):

Gunther Lenz

Nills Franssens

Shivakumar Gopalakrishnan

View More author details

Table of Contents (22) Chapters

Preface

Hands-on Kubernetes on Azure – Third Edition

Foreword

Section 1: The Basics FREE CHAPTER

1. Introduction to containers and Kubernetes

2. Getting started with Azure Kubernetes Service

Section 2: Deploying on AKS

3. Application deployment on AKS

4. Building scalable applications

5. Handling common failures in AKS

6. Securing your application with HTTPS

7. Monitoring the AKS cluster and the application

Section 3: Securing your AKS cluster and workloads

8. Role-based access control in AKS

9. Azure Active Directory pod‑managed identities in AKS

10. Storing secrets in AKS

11. Network security in AKS

Section 4: Integrating with Azure managed services

12. Connecting an application to an Azure database

13. Azure Security Center for Kubernetes

14. Serverless functions

15. Continuous integration and continuous deployment for AKS

Index

Scaling your cluster

In the previous section, you dealt with scaling the application running on top of a cluster. In this section, you'll learn how you can scale the actual cluster you are running. First, you will manually scale your cluster to one node. Then, you'll configure the cluster autoscaler. The cluster autoscaler will monitor your cluster and scale out when there are pods that cannot be scheduled on the cluster.

Manually scaling your cluster

You can manually scale your AKS cluster by setting a static number of nodes for the cluster. The scaling of your cluster can be done either via the Azure portal or the command line.

In this section, you'll learn how you can manually scale your cluster by scaling it down to one node. This will cause Azure to remove one of the nodes from your cluster. First, the workload on the node that is about to be removed will be rescheduled onto the other node. Once the workload is safely rescheduled, the node will be removed...