Webinar Series: Getting Started with Kubernetes
Webinar Series: Getting Started with Kubernetes


Webinar Series: Getting Started with Kubernetes


This article supplements a webinar series on deploying and managing containerized workloads in the cloud. The series covers the essentials of containers, including managing container lifecycles, deploying multi-container applications, scaling workloads, and working with Kubernetes. It also highlights best practices for running stateful applications.

This tutorial includes the concepts and commands in the third session of the series, Getting Started with Kubernetes.


In the previous tutorial in this series, we explored managing multi-container applications with Docker Compose. While the Docker Command Line Interface (CLI) and Docker Compose can deploy and scale containers running on a single machine, Kubernetes is designed to handle multi-container applications deployed across multiple machines or hosts.

Kubernetes is an open-source container orchestration tool for managing containerized applications. A Kubernetes cluster has two key components: Master Nodes and Worker Nodes. A set of Master Nodes act as the control plane that manage the Worker Nodes and deployed applications. The Worker Nodes are the workhorses of a Kubernetes cluster that are responsible for running the containerized applications.

The Master Nodes expose an API through which the command-line tools and rich clients submit a job, which contains the definition of an application. Each application consists of one or more containers, the storage definitions and the internal and external ports through which they are exposed. The control plane running on Master Nodes schedules the containers in one of the Worker Nodes. When an application is scaled, the control plane launches additional containers on any of the available Worker Nodes.

For a detailed introduction to Kubernetes, refer to the tutorial An Introduction to Kubernetes.

StackPointCloud deploys a Kubernetes cluster in three steps using a web-based interface. It hides the complexity of installing and configuring Kubernetes through a simplified user experience. DigitalOcean is one of StackPoint’s supported cloud platforms. Developers who are not familiar with systems administration and configuration can use StackPoint to install Kubernetes on DigitalOcean quickly. For details on the supported features and pricing, refer to their site.

In this tutorial, you’ll set up and configure Kubernetes on DigitalOcean through StackPoint and deploy a containerized application to your cluster.


To follow this tutorial, you will need

  • A local machine with the curl command installed, which you’ll use to download a command-line tool to manage your Kubernetes cluster. The curl command is already installed on macOS and Ubuntu 16.04.
  • A DigitalOcean account. In this tutorial, you’ll use StackPoint to connect to your DigitalOcean account and provision three 1GB Droplets.

Step 1 – Installing Kubernetes

To start the installation of Kubernetes on DigitalOcean, visit Stackpoint.io and click on the Login button.

The StackPoint web page

This takes you to a page where you can choose an identity provider and log in with existing credentials. Choose DigitalOcean from the list and log in with your DigitalOcean username and password.

Choosing a Provider

On the next page, choose DigitalOcean from the list of available cloud platforms.

Select the DigitalOcean provider

You can now configure the cluster. Click on the EDIT button to edit the settings for the DigitalOcean provider:

DigitalOcean provider overview

This takes you to the Configure Provider screen.

DigitalOcean provider configuration page

Choose a region of your choice from the Region dropdown list. You can leave the other settings at their default values. Click on Submit when you are done.

On the next screen, enter a cluster name of your choice and click Submit.

Enter the cluster name

The cluster installation will now start and you’ll be taken to a page where you can track the cluster’s progress. The installation will take about 15 minutes.

The status of your cluster

Once the cluster is configured, we can set up a command-line tool to work with it.

Step 2 – Configuring the Kubernetes CLI

To talk to the Kubernetes cluster running in DigitalOcean, we need a command line tool in our development machine. We’ll use kubectl, the CLI for Kubernetes.

Run the following commands to install kubectl from Google’s servers:

  • curl -LO https://storage.googleapis.com/kubernetes-release/release/`curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt`/bin/darwin/amd64/kubectl

You’ll see this output:

% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 63.7M 100 63.7M 0 0 5441k 0 0:00:12 0:00:12 --:--:-- 4644k

The kubectl binary was downloaded to your current directory, Let’s change the permissions of the downloaded binary and move it to the /usr/local/bin directory so we can run it from anywhere:

  • chmod +x ./kubectl
  • sudo mv ./kubectl /usr/local/bin/kubectl

Now let’s point the kubectl app at our Kubernetes cluster. For that, we need to download a configuration file from Stackpoint. Return to the cluster status page in your browser. After verifying that the cluster is ready and stable, click on the cluster name as shown in the following figure:

The cluster name

Click on the kubeconfig link in the left-hand menu to download the configuration file to your local machine:


Back in your terminal, set the environment variable KUBECONFIG to the path of the downloaded file. Assuming your file downloaded to the Downloads folder in your home directory, you’d issue this command:

  • export KUBECONFIG=~/Downloads/kubeconfig

With kubectl configured, let’s make sure we can communicate with our cluster.

Step 3 – Verifying the Kubernetes Installation

Now that we have the fully configured cluster along with the client, let’s run a few commands to verify the environment.

Run the following command to get information about the cluster.

  • kubectl cluster-info

You’ll see this output:

Kubernetes master is running at Heapster is running at KubeDNS is running at To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

The output confirms that the cluster is working and that the Kubernetes Master Nodes are up and running.

Next, let’s verify the health of all the components running in the Master Nodes. If the cluster is just configured, it may take a while before all the components show a healthy status. These components are a part of the Kubernetes Master Nodes that act as the control plane.

Execute this command:

  • kubectl get cs

You’ll see this output:

NAME STATUS MESSAGE ERROR scheduler Healthy ok controller-manager Healthy ok etcd-0 Healthy {"health": "true"}

Finally, let’s list all the nodes of the running Kubernetes cluster.

  • kubectl get nodes

You’ll see output like this:

NAME STATUS ROLES AGE VERSION spc52y2mk3-master-1 Ready master 29m v1.8.5 spc52y2mk3-worker-1 Ready <none> 22m v1.8.5 spc52y2mk3-worker-2 Ready <none> 22m v1.8.5

This confirms that the cluster with one Master Node and two Worker Nodes is ready for us to deploy applications. So let’s deploy an application to the cluster.

Step 4 – Deploying and Accessing an Application

Let’s launch a simple Nginx web server and access its default web page from our local machine. Execute this command to pull the Nginx image from Docker Hub and create a deployment called myweb:

  • kubectl run --image=nginx:latest myweb

This command is similar to the docker run command, except that it packages and deploys the container in a Kubernetes-specific artifact called a Pod. You’ll learn more about Pods in the next part of this series.

When you execute the command, you’ll see this output:

deployment "myweb" created

Now check that the Pod is created with the nginx container:

  • kubectl get pods

You’ll see this output:

NAME READY STATUS RESTARTS AGE myweb-59d7488cb9-jvnwn 1/1 Running 0 3m

To access the web server running inside the Pod, we need to expose it to the public Internet. We achieve that with the following command:

  • kubectl expose pod myweb-59d7488cb9-jvnwn --port=80 --target-port=80 --type=NodePort
service "myweb-59d7488cb9-jvnwn" exposed

The Pod is now exposed on every Node of the cluster on an arbitrary port. The --port and --target-port switches indicate the ports through which the web server becomes available. The switch --NodePortensures that we can use any Node on the cluster to access the application.

To get the NodePort of the myweb deployment, run the following command.

  • kubectl get svc myweb-59d7488cb9-jvnwn
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE myweb-59d7488cb9-jvnwn NodePort <none> 80:31930/TCP 6m

In this case, the NodePort is port 31930. Every Worker Node uses this port to respond to HTTP requests. Let’s test it out.

Use the DigitalOcean Console to get the IP address of one of the Worker Nodes.


Use the curl command to make an HTTP request to one of the nodes on port 31930.

  • curl http://your_worker_1_ip_address:31930/

You’ll see the response containing the Nginx default home page:

<!DOCTYPE html> <html> <head> <title>Welcome to nginx!</title> ... Commercial support is available at <a href="http://nginx.com/">nginx.com</a>.</p> <p><em>Thank you for using nginx.</em></p> </body> </html>

You have successfully deployed a containerized application to your Kubernetes cluster.


Kubernetes is a popular container management platform. StackPoint makes it easy to install Kubernetes on DigitalOcean.

In the next part of this series, we will explore the building blocks of Kubernetes in more detail.

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