Getting Started With Kubernetes
This chapter covers
— In-depth exploration of containerization with Docker, Podman, and Colima
— Steps for effective application containerization
— Introduction to Kubernetes and its role in orchestration
— The deployment of applications through a first cluster was created with Minikube
— Best practices and architectural considerations for migrating projects to Kubernetes
— Core components of Kubernetes architecture
— Fundamental concepts such as pods, nodes, and clusters
— Overview of Kubernetes interfaces, including CNI, CSI, and CRI
— Insights into command-line tools and plugins for efficient cluster management
Key Learnings
— Grasp the distinctions between Docker and Kubernetes containers.
— Master effective project migration to Kubernetes.
— Understand the fundamental architecture of Kubernetes.
— Explore the Kubernetes ecosystem and interfaces.
— Develop proficiency in managing Kubernetes using command-line tools.
Recipes:
— Wrap Your Application into a Container
— Deploying Your First Application to Kubernetes
— Use Podman for Kubernetes Migration
— Lightweight Distributions: Setting Up k3s and microk8s
— Enabling Calico CNI in Minikube and Exploring Its Features
— Enhancing Your CLI Cluster Management with Krew: kubectx, kubens, kubetail, kubectl-tree, and kubecolor
Introduction
Welcome to Chapter 2, where we demystify Kubernetes, the cloud-native orchestration platform revolutionizing the deployment and management of containerized applications at scale. We will delve into containerization, starting with Docker and contrasting traditional packaging with containerization’s benefits in the software development lifecycle. Exploring tools like Podman and Colima, we analyze Docker alternatives and enhance container configurations. Moving to Kubernetes, we unveil its orchestration capabilities, introducing Pods, Nodes, Clusters, and Deployments. Practical examples guide you in setting up a Kubernetes Cluster with Minikube, touching on alternatives like K3s and Microk8s. The chapter concludes by highlighting Kubernetes’ extensible plugin ecosystem, empowering you with enhanced kubectl functionalities. By the end, you’ve navigated containerization, mastered Kubernetes essentials, and gained confidence in managing clusters.
Docker and Kubernetes: Understanding Containerization
Traditional Ways to Package Software
Deploying software involves installing both the software itself and its dependencies on a server, coupled with the necessity of appropriate application configuration. This process demands considerable effort, time, and skills and is prone to errors.
To streamline this cumbersome task, engineers have devised solutions such as Ansible, Puppet, or Chef, which automate the installation and configuration of software on servers. These tools adopt a declarative approach to system configuration and management, often emphasizing idempotency as a crucial feature. Another strategy to simplify installation in specific programming languages is to package the application into a single file. For instance, in the Java Runtime Environment (JRE), Java class files can be bundled using JAR files.
Various methods can achieve a similar goal. Options like Omnibus or Homebrew packages offer diverse approaches to creating installers. Omnibus excels in crafting full-stack installers, while Homebrew packages leverage formulae written in Ruby. Alternatively, one can utilize virtual machine snapshots from VirtualBox or VMWare to encapsulate the entire state of the operating system alongside the installed application. Despite their continued use, these solutions exhibit notable limitations compared to Docker.
Containerization
As evidenced in the evolution of application packaging, containerization has emerged as a predominant format, encapsulating only essential libraries and dependencies for software delivery. It utilizes OS-level virtualization to run the code and create a single lightweight executable called a container that runs consistently on any infrastructure.
This OS-level virtualization is a complex subject, and its intricacies are beyond the scope of this book. In essence, it is a technology in which the kernel permits the existence of multiple isolated user-space instances. Each instance is a virtual environment with CPU, memory, block I/O, network, and process space. This mechanism is made possible through various underlying technologies such as filesystem (chroot), namespaces (unshare), and control groups (cgroups).
Understanding Docker
Nowadays, Docker has practically become synonymous with containers, and this reputation is well-deserved. Docker was the first tool to show many users the concept of containers. It made managing container lifecycle, communication, and orchestration easier.
What is Docker?
The term “Docker” encompasses various meanings. At a broad level, Docker refers to a collection of containerization tools, including Docker Desktop and Docker Compose. At a more detailed level, Docker represents a container image format, a container runtime library, and a suite of command-line tools. Additionally, Docker, Inc. handles developing and maintaining these tools. Finally, Docker, Inc. founded the Open Container Initiative (OCI), a critical governance structure for container standards.
Docker Engine vs. Docker Desktop
As of today, Docker, Inc. offers two primary methods to use Docker: Docker Engine and Docker Desktop.
If you have a popular Linux system, you can install Docker Engine. Run the official installation script or use your package manager. Docker Engine installation includes the Docker Daemon (dockerd) and Docker Client (docker). Docker Engine is highly regarded for its user-friendly nature and ease of use.
Docker Desktop helps you use Docker Engine with a graphical interface and useful tools. If you are on macOS or Windows, the exclusive way to use Docker is through Docker Desktop. To use Docker Engine on these operating systems, you need to run it on a Linux virtual machine. You can use tools like VirtualBox, Hyper-V, or Vagrant to manage and set up the VMs.
Docker Desktop itself uses a virtual machine. The virtual machine runs a Linux environment. The Linux environment has Docker Engine as its core component. The choice of virtualization technology depends on the host operating system. It can use Windows Subsystem for Linux (WSL) or Hyper-V on Windows. On MacOS, it may use HyperKit or QEMU. You don’t have to know how Docker Desktop’s virtualization works and use it like Docker Engine.
Exploring Podman
Podman (the POD Manager) is a more recent container engine initially released by RedHat in 2018. Podman differs from Docker because it doesn’t need a separate daemon to run containers. It utilizes the libpod library for running OCI-based containers on Linux. On macOS, each Podman machine is backed by QEMU, and on Windows, by WSL. Unlike Docker, Podman can run rootless containers by default without any prerequisites.
Podman makes it easy to migrate your project to Kubernetes. It is capable of generating manifests and quickly deploying them in your cluster. This chapter will delve deeper into Podman and its migration capabilities.
Colima: The Newcomer
Colima is a relatively new development tool released in 2021. It uses Lima on Linux virtual machines. Lima has containerd runtime with nerdctl installed. Colima adds support for Docker and Kubernetes runtime. Colima’s virtual machines use QEMU with an HVF accelerator. Colima works on MacOS and Linux and is easier to use than Docker Desktop. The good part is that it’s completely free. Yet, it’s important to note that Colima is still in its early stages and has a few limitations.
Docker, Podman,