Minikube#

During this blog, we’ll be using Minikube to practice with Kubernetes. In production, you probably wouldn’t use Minikube, you would use a cluster of servers, probably in the cloud. That’s expensive! Minikube is a fantastic tool that allows you to run a single-node Kubernetes cluster on your local machine.

Kubectl#

The Kubernetes command-line tool, kubectl, allows you to run commands against Kubernetes clusters. It’s a client that communicates with a Kubernetes API server.

Installing kubectl#

Follow the official installation instructions for kubectl.

Verify Installation#

Run kubectl version --client to verify that kubectl is installed correctly.

Install Minikube#

Follow the official installation instructions for Minikube. Select the correct instructions for your system, choose either Linux/WSL or macOS.If you don’t have the system requirements, you’ll have a hard time getting everything up and running, unfortunately.

Verify Installation#

Run minikube version to verify that Minikube is installed correctly.

Run Minikube#

We’ll be using Kubernetes with Docker, which is arguably the most common way to use Kubernetes. Make sure your Docker daemon is running before starting Minikube.

Next, run:

minikube start 

Previous Minikube Installations#

If you’ve installed minikube in the past, you might have conflicts. If you don’t care about your old minikube clusters, you can delete them by running:

minikube stop
minikube delete

Then restart minikube.

Deploying an Image#

The kubectl create deployment command will create a “deployment” for us. We’ll talk more about the nuances of “deployments” later. But to put it simply, we only need to provide two things:

1. The name of the deployment (this can be anything, it’s used to identify the deployment)
2. The ID of the Docker image we want to deploy (it would be a full URL if we weren’t hosting the image on Docker Hub, which is the default)

kubectl create deployment synergychat-web --image=docker.io/bootdotdev/synergychat-web:latest

This command will deploy a container built from this Docker image to your local k8s cluster.

Viewing Deployments#

To make sure the deployment was successful, run:

kubectl get deployments

Accessing the Web Page#

By default, resources inside of Kubernetes run on a private, isolated network. They’re visible to other resources within the cluster, but not to the outside world.

In order to access the application from your local network, you’ll need to use kubectl to do some port forwarding. First, run:

kubectl get pods

We’ll talk more about pods later, but for now, a pod is an abstraction over a container, and remember, a container is just a running instance of an image. To oversimplify, a pod is a running application.

You should see something like this:

NAME                                   READY   STATUS    RESTARTS   AGE
synergychat-web-679cbcc6cd-cq6vx       1/1     Running   0          20m

Next, run:

kubectl port-forward PODNAME 8080:8080

Be sure to replace PODNAME with your pod’s name. In my case, it was synergychat-web-679cbcc6cd-cq6vx.

Minikube vs. Prod#

Minikube is a great tool for learning Kubernetes, but it’s not a production-scale Kubernetes cluster. The primary difference is that Minikube runs a single-node cluster, whereas production clusters are multi-node distributed systems.

Distributed Systems Are Complex#

Whenever you’re dealing with a system that involves multiple machines talking to each other over a network, you’re dealing with a distributed system. Distributed systems are inherently complex, and Kubernetes is no exception, but that complexity is generally abstracted away from you as a K8s user. That’s what makes Kubernetes so cool! It does a lot of the hard work for you.

Resources and Nodes#

To zoom way out, Kubernetes’ job is to run software applications, and applications require resources. Resources are things like:

• CPU
• Memory
• Disk space

Kubernetes’ job is to manage those resources and allocate them to the applications that are running on it. Let’s look at an oversimplified example:

3 Nodes (Machines)#

5 Pods (Applications)#

Kubernetes looks at the resources required by each application and decides which node to run it on. In this case, it might do something like this:

What happens if we get a new application that requires 10GB of RAM? The cluster doesn’t have enough resources to run it! The solution? Easy. Just add another node to the cluster and let Kubernetes figure out where to run it.

This Won’t Work With Minikube#

With Minikube, you only get one node! So once your machine runs out of resources, you’re out of luck. That’s why Minikube is great for learning, but not for production.

Kubernetes clusters are running in production that have thousands of nodes. That’s a lot of resources to manage! But that’s the beauty of Kubernetes.

If you’re interested, you can find some case studies here. I liked this one from Bloomberg that shows they run hundreds of clusters with thousands of nodes each. for more pods