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Mastering Elastic Kubernetes Service on AWS

Mastering Elastic Kubernetes Service on AWS

By : Malcolm Orr, Yang-Xin Cao, Yang-Xin Cao (Eason)
4.9 (23)
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Mastering Elastic Kubernetes Service on AWS

Mastering Elastic Kubernetes Service on AWS

4.9 (23)
By: Malcolm Orr, Yang-Xin Cao, Yang-Xin Cao (Eason)

Overview of this book

Kubernetes has emerged as the de facto standard for container orchestration, with recent developments making it easy to deploy and handle a Kubernetes cluster. However, a few challenges such as networking, load balancing, monitoring, and security remain. To address these issues, Amazon EKS offers a managed Kubernetes service to improve the performance, scalability, reliability, and availability of AWS infrastructure and integrate with AWS networking and security services with ease. You’ll begin by exploring the fundamentals of Docker, Kubernetes, Amazon EKS, and its architecture along with different ways to set up EKS. Next, you’ll find out how to manage Amazon EKS, encompassing security, cluster authentication, networking, and cluster version upgrades. As you advance, you’ll discover best practices and learn to deploy applications on Amazon EKS through different use cases, including pushing images to ECR and setting up storage and load balancing. With the help of several actionable practices and scenarios, you’ll gain the know-how to resolve scaling and monitoring issues. Finally, you will overcome the challenges in EKS by developing the right skill set to troubleshoot common issues with the right logic. By the end of this Kubernetes book, you’ll be able to effectively manage your own Kubernetes clusters and other components on AWS.
Table of Contents (28 chapters)
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1
Part 1: Getting Started with Amazon EKS
7
Part 2: Deep Dive into EKS
13
Part 3: Deploying an Application on EKS
20
Part 4: Advanced EKS Service Mesh and Scaling
24
Part 5: Overcoming Common EKS Challenges

Scaling applications with Horizontal Pod Autoscaler

HPA is a component of Kubernetes that allows you to scale pods (through a Deployment/ReplicaSet) based on metrics rather than manual scaling commands. The metrics are collected by the K8s metrics server, so you will need to have this deployed in your cluster. The following diagram illustrates the general flow.

Figure 18.7 – High-level HPA flow

Figure 18.7 – High-level HPA flow

In the preceding diagram, we can see the following:

  1. HPA reads metrics from the metrics server.
  2. There is a control loop that triggers HPA to read the metrics every 15 seconds.
  3. HPA assesses these metrics against the desired state of the autoscaling configuration and will scale the deployment if needed.

Now we’ve looked at the concepts behind the HPA, let’s configure and test it.

Installing HPA in your EKS cluster

As we’ve discussed, HPA is a feature of K8s, so no installation is necessary; however, it does depend...

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