How to get started with Kubernetes

From Hello Minikube to Kubernetes Anywhere to example microservices apps, the options for learning Google’s container orchestration tool abound

Senior Writer, InfoWorld |

How to get started with Kubernetes — Thinkstock

With every innovation comes new complications. Containers made it possible to package and run applications in a convenient, portable form factor, but managing containers at scale is challenging to say the least.

Kubernetes, the product of work done internally at Google to solve that problem, provides a single framework for managing how containers are run across a whole cluster. The services it provides are generally lumped together under the catch-all term “orchestration,” but that covers a lot of territory: scheduling containers, service discovery between containers, load balancing across systems, rolling updates/rollbacks, high availability, and more.

In this guide we’ll walk through the basics of setting up Kubernetes and populating it with container-based applications. This isn’t intended to be an introduction to Kubernetes’s concepts, but rather a way to show how those concepts come together in simple examples of running Kubernetes.

Use a Kubernetes distribution

Kubernetes was born to manage Linux containers. However, as of Kubernetes 1.5, Kubernetes also supports Windows Server Containers, though the Kubernetes control plane must continue to run on Linux. Of course, with the aid of virtualization, you can get started with Kubernetes on any platform.

If you’re opting to run Kubernetes on your own hardware or VMs, one common way to do this is to obtain a packaged Kubernetes distribution, which typically combine the upstream Kubernetes bits with other pieces — container registry, networking, storage, security, logging, monitoring, continuous integration pipeline, etc. — needed for a complete deployment. Plus, Kubernetes distributions generally can be installed and run in any virtual machine infrastructure: Amazon EC2, Azure Virtual Machines, Google Compute Engine, OpenStack, and so on.

Canonical Kubernetes, Cloud Foundry Container Runtime, Mesosphere Kubernetes Service, Oracle Linux Container Services, Pivotal Container Service, Rancher, Red Hat OpenShift, and Suse CaaS Platform are just a few of the dozens of Kubernetes distributions available. Note that the Canonical, Red Hat, and Suse offerings bundle Kubernetes with a Linux distribution, which does away with the need for setting up Kubernetes on a given operating system—not only the download-and-install process, but even some of the configure-and-manage process.

Another approach is to run Kubernetes atop a conventional Linux distribution, although that typically comes with more management overhead and manual fiddling. Red Hat Enterprise Linux has Kubernetes in its package repository, for instance, but even Red Hat recommends its use only for testing and experimentation. Rather than try to cobble something together by hand, Red Hat stack users are recommended to use Kubernetes by way of the OpenShift PaaS, as OpenShift now uses Kubernetes as its own native orchestrator.

Many conventional Linux distributions provide special tooling for setting up Kubernetes and other large software stacks. Ubuntu, for instance, provides a tool called conjure-up that can be used to deploy the upstream version of Kubernetes on both cloud and bare-metal instances. Canonical also provides MicroK8s, a version of Kubernetes that installs via the Snap package system.

Use a Kubernetes service in the cloud

Kubernetes is available as a standard-issue item in many clouds, though it appears most prominently as a native feature in Google Cloud Platform (GCP). GCP offers two main ways to run Kubernetes. The most convenient and tightly integrated way is by way of Google Kubernetes Engine, which allows you to run Kubernetes’s command-line tools to manage the created cluster.

Alternatively, you could use Google Compute Engine to set up a compute cluster and deploy Kubernetes manually. This method requires more heavy lifting, but allows for customizations that aren’t possible with Container Engine. Stick with Container Engine if you’re just starting out with containers. Later on, after you get your sea legs and want to try something more advanced, like a custom version of Kubernetes or your own modifications, you can deploy VMs running a Kubernetes distro.

With Amazon, one originally had to run Kubernetes by deploying a compute cluster in EC2. That is still an option, but Amazon now offers the Elastic Container Service for Kubernetes (EKS). With EKS, Amazon runs the control plane and you focus on deploying the containers you’ll use with the configuration you want. EKS also runs a standard upstream edition of Kubernetes. One smart feature is the integration of Kubernetes with rest of the AWS portfolio. AWS services appear in EKS as Kubernetes-native Custom Resource Definitions, so any changes to either AWS or Kubernetes won’t break such connections.

Many Kubernetes distributions come with detailed instructions for getting set up on AWS and elsewhere. Red Hat OpenShift, for instance, can be installed on one or more hosts via an interactive installer or a script, or by using the Terraform “infrastructure-as-code” provisioning tool. Alternatively, Kubernetes’s Kops tool can be used to provision a cluster of generic VMs on AWS, with support for Google Cloud Engine, VMware vSphere, and other clouds in the works.

Microsoft Azure has support for Kubernetes by way of the Azure Kubernetes Service. Here Azure manages the Kubernetes master nodes, while you create the clusters via Resource Manager templates or Terraform. If you want control of both the master and the agent nodes, you can always install a Kubernetes distribution on an Azure Virtual Machine. That said, one key advantage of AKS is that you don’t pay for the use of the master node, just the agents.

One quick way to provision a basic Kubernetes cluster in a variety of environments, cloud or otherwise, is to use a project called Kubernetes Anywhere. This script works on Google Compute Engine, Microsoft Azure, VMware vSphere (vCenter is required), and OpenStack. In each case, Kubernetes Anywhere provides some degree of automation for the setup.

Use Minikube to run Kubernetes locally

If you’re only running Kubernetes in a local environment like a development machine, and you don’t need the entire Kubernetes enchilada, there are a few ways to set up “just enough” Kubernetes for such use.

One that is provided by the Kubernetes development team itself is Minikube. Run it and you’ll get a single-node Kubernetes cluster deployed in a virtualization host of your choice. Minikube has a few prerequisites, but they are all easy enough to meet on MacOS, Linux, or Windows.

Run a Kubernetes demo app

Once you have Kubernetes running, you’re ready to begin deploying and managing containers. You can ease into container ops by drawing on one of the many container-based app demos available.

Take an existing container-based app demo, assemble it yourself to see how it is composed, deploy it, and then modify it incrementally until it approaches something useful to you. If you have chosen Minikube to find your footing, you can use the Hello Minikube tutorial to create a Docker container holding a simple Node.js app in a single-node Kubernetes demo installation. Once you get the idea, you can swap in your own containers and practice deploying those as well.

The next step up is to deploy an example application that resembles one you might be using in production, and becoming familiar with more advanced Kubernetes concepts such as pods (one or more containers that comprise an application), services (logical sets of pods), replica sets (to provide self-healing on machine failure), and deployments (application versioning).

Lift the hood of the WordPress/MySQL sample application, for instance, and you’ll see more than just instructions on how to deploy the pieces into Kubernetes and get them running. You will also see implementation details for many concepts used by production-level Kubernetes applications. You’ll learn how to set up persistent volumes to preserve the state of an application, how to expose pods to each other and to the outside world by way of services, how to store application passwords and API keys as secrets, and so on.

Weaveworks has an example app, the Sock Shop, that shows how a microservices pattern can be used to compose an application in Kubernetes. The Sock Shop will be most useful to people familiar with the underlying technologies—Node.js, Go kit, and Spring Boot—but the core principles are meant to transcend particular frameworks and illustrate cloud-native technologies.

If you glanced at the WordPress/MySQL application and imagined there might be a pre-baked Kubernetes app that meets your needs, you’re probably right. Kubernetes has an application definition system called Helm, which provides a way to package, version, and share Kubernetes applications. A number of popular apps (GitLab, WordPress) and app building blocks (MySQL, Nginx) have Helm “charts” readily available by way of the Kubeapps portal.

Manage containers with Kubernetes

Kubernetes simplifies container management through powerful abstractions like pods and services, while providing a great deal of flexibility through mechanisms like labels and namespaces, which can be used to segregate pods, services, and deployments (such as development, staging, and production workloads).

If you take one of the above examples and set up different instances in multiple namespaces, you can then practice making changes to components in each namespace independent of the others. You can then use deployments to allow those updates to be rolled out across pods in a given namespace, incrementally.

The next step is learning how Kubernetes can be driven by tools for managing infrastructure. Puppet, for instance, has a module for creating and manipulating resources in Kubernetes. Similarly, HashiCorp’s Terraform has growing support for Kubernetes as a resource. If you plan on using such a resource manager, note that different tools might bring vastly different assumptions to the table. Puppet and Terraform, for instance, default to using mutable and immutable infrastructures respectively. Those philosophical and behavioral differences can determine how easy or difficult it will be to create the Kubernetes setup you need.

Serdar Yegulalp is a senior writer at InfoWorld, focused on machine learning, containerization, devops, the Python ecosystem, and periodic reviews.

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