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Creating Kubernetes Cluster Using Kind on local computer

Learning Kubernetes

Rahul Lokurte
·Aug 31, 2021·

4 min read

Creating Kubernetes Cluster Using Kind on local computer

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Kubernetes is an open-source tool for automating deployment, scaling, and management of containerized applications.

Developers push the code multiple times a day. Packaging our applications as containers, enables our application to be updated multiple times without downtime. Kubernetes helps us to run the containerized applications.

We can create a Kubernetes cluster in our local computer by using tools such as minikube and kind. In this blog, we will look into the Kind.

Prerequisite:

  • Docker

Tools :

  • kubectl - A Kubernetes command-line tool that allows us to run commands against Kubernetes clusters. We can deploy applications, inspect and monitor the cluster resources, and view logs using kubectl.

  • kind - It is a tool that lets us run the Kubernetes cluster on our local computer.

Install Kubectl

  1. macOS

  2. Windows

Install Kind

macOS

$brew install kind

Windows

$curl.exe -Lo kind-windows-amd64.exe https://kind.sigs.k8s.io/dl/v0.11.1/kind-windows-amd64
$Move-Item .\kind-windows-amd64.exe c:\some-dir-in-your-PATH\kind.exe

Create a Kubernetes cluster

Once kind is installed, create a kubernetes cluster using the command

$kind create cluster --name learning-kubernetes-dev

When the cluster is created, the cluster configuration file is stored at the location ${home}/.kube/config

We can create multiple kubernetes clusters. Let us define one more cluster for production

$kind create cluster --name learning-kubernetes-prod

To verify, if the cluster has been created, issue the below command.

$kind get clusters

learning-kubernetes-dev
learning-kubernetes-prod

To interact with a particular cluster, we need to specify the kind-<cluster-name> as a context in kubectl as shown below.

$kubectl cluster-info --context kind-learning-kubernetes-dev
Kubernetes control plane is running at https://127.0.0.1:52083
CoreDNS is running at https://127.0.0.1:52083/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

➜  $kubectl cluster-info --context kind-learning-kubernetes-prod
Kubernetes control plane is running at https://127.0.0.1:52449
CoreDNS is running at https://127.0.0.1:52449/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

To verify which context is currently used, we can issue the below command.

$kubectl config get-contexts

CURRENT   NAME                            CLUSTER                         AUTHINFO                        NAMESPACE
          kind-learning-kubernetes-dev    kind-learning-kubernetes-dev    kind-learning-kubernetes-dev
*         kind-learning-kubernetes-prod   kind-learning-kubernetes-prod   kind-learning-kubernetes-prod

The indicates the current cluster. So the current cluster context is *kind-learning-kubernetes-prod

To switch between the clusters, we can issue the below command.

$kubectl config use-context kind-learning-kubernetes-dev

Switched to context "kind-learning-kubernetes-dev"

Let us verify again, this time, the current context is kind-learning-kubernetes-dev

$kubectl config get-contexts
CURRENT   NAME                            CLUSTER                         AUTHINFO                        NAMESPACE
*         kind-learning-kubernetes-dev    kind-learning-kubernetes-dev    kind-learning-kubernetes-dev
          kind-learning-kubernetes-prod   kind-learning-kubernetes-prod   kind-learning-kubernetes-prod

Namespace

The virtual clusters which are created within the physical cluster are called namespaces. If we have multiple teams/projects, we can use the same cluster, but for each team/project, we can define the namespaces.

If we do not define any namespaces, then we get a default namespace. We can use the below command to see the namespaces.

kubectl get namespaces

NAME                 STATUS   AGE
default              Active   23m

Create a namespace

We can define multiple namespaces in kubernetes clusters. In our learning-kubernetes-dev, we can have two namespaces. One is used by team-1 and the other is used by team-2.

Let's first switch the context to create a namespace in the learning-kubernetes-dev cluster

$kubectl config use-context kind-learning-kubernetes-dev

create a file called team1-namespace.json with the below content.

{
  "apiVersion": "v1",
  "kind": "Namespace",
  "metadata": {
    "name": "team-1",
    "labels": {
      "name": "team-1"
    }
  }
}

Use the below command to create a namespace.

$kubectl create -f team1-namespace.json

namespace/team-1 created

create a file called team2-namespace.json with the below content.

{
  "apiVersion": "v1",
  "kind": "Namespace",
  "metadata": {
    "name": "team-2",
    "labels": {
      "name": "team-2"
    }
  }
}

Use the below command to create a namespace.

$kubectl create -f team2-namespace.json

namespace/team-2 created

Use the below command to verify the namespaces.

$kubectl get namespace

NAME                 STATUS   AGE
default              Active   44m
team-1               Active   2m13s
team-2               Active   18s

Create a Pod in a Namespace

A Kubernetes namespace provides the scope for Pods, Services, and Deployments in the cluster.

let's create a simple Deployment and Pods for both Team-1 and Team-2 namespace. Team-1 needs an NGINX server of 1 instance and Team-2 needs 2 instances.

$kubectl create deployment nginx-team-1 --image nginx -n team-1 --replicas=1

deployment.apps/nginx-team-1 created
$kubectl create deployment nginx-team-2 --image nginx -n team-2 --replicas=2
deployment.apps/nginx-team-2 created

Let's verify the number of pods created for team-1 and team-2

kubectl get pods -n team-1

NAME                            READY   STATUS    RESTARTS   AGE
nginx-team-1-544dd7f5bd-qk5g6   1/1     Running   0          113s
kubectl get pods -n team-2

NAME                            READY   STATUS    RESTARTS   AGE
nginx-team-2-55f89d7667-2wd9n   1/1     Running   0          87s
nginx-team-2-55f89d7667-8xd95   1/1     Running   0          87s

Conclusion

In this blog post, we saw how easy it is to create a Kubernetes cluster in your local computer. Once installed, we can play with Kubernetes and it helps us learn about pods, deployments. We saw how to create a namespace so that we can use one cluster with multiple teams deploying applications on the same cluster.

GitHub Repository: https://github.com/rahulmlokurte/devops-stuff/tree/main/kubernetes/kubernetes-kind

This is just the starting point. Check out the below documents to get into the depth of Kubernetes.

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