Book Image

Kubernetes in Production Best Practices

By : Aly Saleh, Murat Karslioglu
Book Image

Kubernetes in Production Best Practices

By: Aly Saleh, Murat Karslioglu

Overview of this book

Although out-of-the-box solutions can help you to get a cluster up and running quickly, running a Kubernetes cluster that is optimized for production workloads is a challenge, especially for users with basic or intermediate knowledge. With detailed coverage of cloud industry standards and best practices for achieving scalability, availability, operational excellence, and cost optimization, this Kubernetes book is a blueprint for managing applications and services in production. You'll discover the most common way to deploy and operate Kubernetes clusters, which is to use a public cloud-managed service from AWS, Azure, or Google Cloud Platform (GCP). This book explores Amazon Elastic Kubernetes Service (Amazon EKS), the AWS-managed version of Kubernetes, for working through practical exercises. As you get to grips with implementation details specific to AWS and EKS, you'll understand the design concepts, implementation best practices, and configuration applicable to other cloud-managed services. Throughout the book, you’ll also discover standard and cloud-agnostic tools, such as Terraform and Ansible, for provisioning and configuring infrastructure. By the end of this book, you’ll be able to leverage Kubernetes to operate and manage your production environments confidently.
Table of Contents (12 chapters)

Choosing a persistent storage solution

Two of the biggest stateful application challenges in Kubernetes are storage orchestration and data management. There are an infinite number of solutions out there. First, we will explain the main storage attributes and topologies we need to consider when evaluating storage alternatives. Let's review the topologies used by the most common storage systems:

  • Centralized: Traditional, or also referred to as monolithic, storage systems are most often tightly coupled with a proprietary hardware and internal communication protocols. They are usually associated with scale-up models since it is difficult to scale-out tightly coupled components of the storage nodes.
  • Distributed: Distributed storage systems are more likely to be a software-defined solution and they may be architected to favor availability, consistency, durability, performance, or scalability. Usually, distributed systems scale out better than others to support many storage...