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 application

There are two scale dimensions for applications running on top of AKS. The first scale dimension is the number of pods a deployment has, while the second scale dimension in AKS is the number of nodes in the cluster.

By adding new pods to a deployment, also known as scaling out, you can add additional compute power to the deployed application. You can either scale out your applications manually or have Kubernetes take care of this automatically via HPA. HPA can monitor metrics such as the CPU to determine whether pods need to be added to your deployment.

The second scale dimension in AKS is the number of nodes in the cluster. The number of nodes in a cluster defines how much CPU and memory are available for all the applications running on that cluster. You can scale your cluster manually by changing the number of nodes, or you can use the cluster autoscaler to automatically scale out your cluster. The cluster autoscaler watches the cluster for pods that...