Mastering Kubernetes Third Edition

Go beyond simply learning Kubernetes fundamentals and its deployment, and explore more advanced concepts, including serverless computing and service meshes with the latest updates

▶Book Description
The third edition of Mastering Kubernetes is updated with the latest tools and code enabling you to learn Kubernetes 1.18's latest features. This book primarily concentrates on diving deeply into complex concepts and Kubernetes best practices to help you master the skills of designing and deploying large clusters on various cloud platforms.

The book trains you to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. With the two new chapters, you will gain expertise in serverless computing and utilizing service meshes.

As you proceed through the chapters, you will explore different options for network configuration and learn to set up, operate, and troubleshoot Kubernetes networking plugins through real-world use cases. Furthermore, you will understand the mechanisms of custom resource development and its utilization in automation and maintenance workflows.

By the end of this Kubernetes book, you will graduate from an intermediate to advanced Kubernetes professional.

▶What You Will Learn
⦁Master the fundamentals of Kubernetes architecture and design
⦁Build and run stateful applications and complex microservices on Kubernetes
⦁Master Kubernetes Networking with load balancing options like Ingress
⦁Achieve high-availability Kubernetes clusters
⦁Improve Kubernetes observability with tools like Prometheus, Grafana, and Jaeger
⦁Extend Kubernetes working with Kubernetes API, plugins, and webhooks

▶Key Features
⦁Master Kubernetes architecture and design to build and deploy secure distributed applications
⦁Learn advanced concepts like autoscaling, cluster federation, serverless computing, and service mesh integration for observability
⦁Explore Kubernetes 1.18 features and its rich ecosystem of tools like Kubectl, Knative, and Helm

▶Who This Book Is For
If you are a system administrator or a cloud developer with working knowledge of Kubernetes and are keen to master its advanced features, along with learning everything from building microservices to utilizing service meshes, Mastering Kubernetes is for you. Basic familiarity with networking concepts will be helpful.

▶What this book covers
⦁ Chapter 1, Understanding Kubernetes Architecture, in this chapter, we will build together the foundation necessary to utilize Kubernetes to its full potential. We will start by understanding what Kubernetes is, what Kubernetes isn't, and what container orchestration means exactly. Then we will cover important Kubernetes concepts that will form the vocabulary we will use throughout the book.

⦁ Chapter 2, Creating Kubernetes Clusters, in this chapter, we will roll up our sleeves and build some Kubernetes clusters using minikube, KinD, and k3d. We will discuss and evaluate other tools such as Kubeadm, Kube-spray, bootkube, and stackube. We will also look into deployment environments such as local, cloud, and bare metal.

⦁ Chapter 3, High Availability and Reliability, in this chapter, we will dive into the topic of highly available clusters. This is a complicated topic. The Kubernetes project and the community haven't settled on one true way to achieve high-availability nirvana. There are many aspects to highly available Kubernetes clusters, such as ensuring that the control plane can keep functioning in the face of failures, protecting the cluster state in etcd, protecting the system's data, and recovering capacity and/or performance quickly. Different systems will have different reliability and availability requirements.

⦁ Chapter 4, Securing Kubernetes, in this chapter, we will explore the important topic of security. Kubernetes clusters are complicated systems composed of multiple layers of interacting components. Isolation and compartmentalization of different layers is very important when running critical applications. To secure the system and ensure proper access to resources, capabilities, and data, we must first understand the unique challenges facing Kubernetes as a general-purpose orchestration platform that runs unknown workloads. Then we can take advantage of various securities, isolation, and access control mechanisms to make sure the cluster, the applications running on it, and the data are all safe. We will discuss various best practices and when it is appropriate to use each mechanism.

⦁ Chapter 5, Using Kubernetes Resources in Practice, in this chapter, we will design a fictional massive-scale platform that will challenge Kubernetes' capabilities and scalability. The Hue platform is all about creating an omniscient and omnipotent digital assistant. Hue is a digital extension of you. Hue will help you do anything, find anything, and, in many cases will do a lot on your behalf. It will obviously need to store a lot information, integrate with many external services, respond to notifications and events, and be smart about interacting with you.

⦁ Chapter 6, Managing Storage, in this chapter, we'll look at how Kubernetes manages storage. Storage is very different from compute, but at a high level they are both resources. Kubernetes as a generic platform takes the approach of abstracting storage behind a programming model and a set of plugins for storage providers.

⦁ Chapter 7, Running Stateful Applications with Kubernetes, in this chapter, we will learn how to run stateful applications on Kubernetes. Kubernetes takes a lot of work out of our hands by automatically starting and restarting pods across the cluster nodes as needed, based on complex requirements and configurations such as namespaces, limits, and quotas. But when pods run storage-aware software, such as databases and queues, relocating a pod can cause the system to break.

⦁ Chapter 8, Deploying and Updating Applications, in this chapter, we will explore the automated pod scalability that Kubernetes provides, how it affects rolling updates, and how it interacts with quotas. We will touch on the important topic of provisioning and how to choose and manage the size of the cluster. Finally, we will go over how the Kubernetes team improved the performance of Kubernetes and how they test the limits of Kubernetes with the Kubemark tool.

⦁ Chapter 9, Packaging Applications, in this chapter, we are going to look into Helm, the Kubernetes package manager. Every successful and non-trivial platform must have a good packaging system. Helm was developed by Deis (acquired by Microsoft on April 4, 2017) and later contributed to the Kubernetes project directly. It became a CNCF project in 2018. We will start by understanding the motivation for Helm, its architecture, and its components.

⦁ Chapter 10, Exploring Advanced Networking, in this chapter, we will examine the important topic of networking. Kubernetes as an orchestration platform manages containers/pods running on different machines (physical or virtual) and requires an explicit networking model.

⦁ Chapter 11, Running Kubernetes on Multiple Clouds and Cluster Federation, in this chapter, we'll take it to the next level, with running Kubernetes on multiple clouds, multiple clusters, and cluster federation. A Kubernetes cluster is a closely-knit unit where all the components run in relative proximity and are connected by a fast network (typically a physical data center or cloud provider availability zone). This is great for many use cases, but there are several important use cases where systems need to scale beyond a single cluster.

⦁ Chapter 12, Serverless Computing on Kubernetes, in this chapter, we will explore the fascinating world of serverless computing in the cloud. The term "serverless" is getting a lot of attention, but it is a misnomer used to describe two different paradigms. A true serverless application runs as a web application in the user's browser or a mobile app and only interacts with external services. The types of serverless systems we build on Kubernetes are different.

⦁ Chapter 13, Monitoring Kubernetes Clusters, in this chapter, we're going to talk about how to make sure your systems are up and running and performing correctly and how to respond when they aren't. In Chapter 3, High Availability and Reliability, we discussed related topics. The focus here is about knowing what's going on in your system and what practices and tools you can use.

⦁ Chapter 14, Utilizing Service Meshes, in this chapter, we will learn how service meshes allow you to externalize cross-cutting concerns like monitoring and observability from the application code. The service mesh is a true paradigm shift in the way you can design, evolve, and operate distributed systems on Kubernetes. I like to think of it as aspect-oriented programming for cloud-native distributed systems.

⦁ Chapter 15, Extending Kubernetes, in this chapter, we will dig deep into the guts of Kubernetes. We will start with the Kubernetes API and learn how to work with Kubernetes programmatically via direct access to the API, the Python client, and automating Kubectl. Then, we'll look into extending the Kubernetes API with custom resources. The last part is all about the various plugins Kubernetes supports. Many aspects of Kubernetes operation are modular and designed for extension. We will examine the API aggregation layer and several types of plugins, such as custom schedulers, authorization, admission control, custom metrics, and volumes. Finally, we'll look into extending Kubectl and adding your own commands.

⦁ Chapter 16, The Future of Kubernetes, in this chapter, we'll look at the future of Kubernetes from multiple angles. We'll start with the momentum of Kubernetes since its inception, across dimensions such as community, ecosystem, and mindshare. Spoiler alert: Kubernetes won the container orchestration wars by a land slide. As Kubernetes grows and matures, the battle lines shift from beating competitors to fighting against its own complexity. Usability, tooling, and education will play a major role as container orchestration is still new, fast-moving, and not a well-understood domain. Then we will take a look at some very interesting patterns and trends, and finally, we will review my predictions from the 2nd edition and I will make some new predictions.