Book Image

Kubernetes – An Enterprise Guide - Second Edition

By : Marc Boorshtein, Scott Surovich
Book Image

Kubernetes – An Enterprise Guide - Second Edition

By: Marc Boorshtein, Scott Surovich

Overview of this book

Kubernetes has taken the world by storm, becoming the standard infrastructure for DevOps teams to develop, test, and run applications. With significant updates in each chapter, this revised edition will help you acquire the knowledge and tools required to integrate Kubernetes clusters in an enterprise environment. The book introduces you to Docker and Kubernetes fundamentals, including a review of basic Kubernetes objects. You’ll get to grips with containerization and understand its core functionalities such as creating ephemeral multinode clusters using KinD. The book has replaced PodSecurityPolicies (PSP) with OPA/Gatekeeper for PSP-like enforcement. You’ll integrate your container into a cloud platform and tools including MetalLB, externalDNS, OpenID connect (OIDC), Open Policy Agent (OPA), Falco, and Velero. After learning to deploy your core cluster, you’ll learn how to deploy Istio and how to deploy both monolithic applications and microservices into your service mesh. Finally, you will discover how to deploy an entire GitOps platform to Kubernetes using continuous integration and continuous delivery (CI/CD).
Table of Contents (17 chapters)
15
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16
Index

Enhancing load balancers for the enterprise

In this third, and final section, we will discuss some of the limitations of certain load balancer features and how we can configure a cluster to resolve the limitations. Our examples have been good for learning, but in an enterprise, nobody wants to access a workload running on the cluster using an IP address. Also, in an enterprise, you will commonly run services on multiple clusters to provide some failover for your applications. So far, the options discussed can't address these two key points. In this section, we will explain how to resolve these issues so your enterprise can offer easier access to workloads that are highly available by names, including across multiple clusters.