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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

Common K8s tools/techniques for troubleshooting EKS

Any troubleshooting process begins with trying to understand the problem and differentiate between symptoms and the root cause of the problem. Symptoms can often be mistaken for the root cause, so the troubleshooting process tends to be iterative, with constant testing and observation as you focus on what the actual problem is and disregard the symptoms and false positives.

Once you understand the problem, it’s now a case of understanding how to mitigate, solve, or ignore it. Not all problems can be solved then and there, so you may need a strategy to work around them for the time being.

The final stage will be the resolution/fixing of the problem. This might require an update to your cluster, application code, or both, and depending on the nature of the problem, the number of clusters you manage and the impact on the users/customers may be quite an involved process.

Generally, I use the following checklist when trying...

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