One place for hosting & domains


      Segregating Test Environments With CircleCI

      How to Join

      This Tech Talk is free and open to everyone. Register below to get a link to join the live event.

      July 7, 202111:00 a.m.–12:00 p.m. ET / 3:00–4:00 p.m. GMT

      About the Talk

      No two teams have the same path to production but having flexible tools allows high-performing teams to implement workflows that prevent roadblocks later. Modern DevOps practices like containerizing, segregating test environments, and automating tests and delivery can reduce risk and time to market.

      In this Tech Talk, explore how you can use CircleCI to automate your development process with continuous integration on DigitalOcean to reduce cost and increase velocity without compromising quality.

      What You’ll Learn

      • Optimize your pipelines for speed and performance by leveraging caching and flexible resources classes
      • Eliminate bottlenecks from long-running tests by taking advantage of parallelism and test splitting
      • Mitigate the risk of unplanned downtime by implementing multi-cloud pipelines

      This Talk is Designed For

      DevOps and engineering leaders, developers, and cloud architects.


      Familiarity with the software development lifecycle.


      The path to production: how and where to segregate test environments Blog post Video

      To join the live Tech Talk, register here.

      Source link

      How To Automate Deployment Using CircleCI and GitHub on Ubuntu 18.04

      The author selected International Medical Corps to receive a donation as part of the Write for DOnations program.


      Continuous Integration/Continuous Deployment (CI/CD) is a development practice that allows software teams to build, test, and deploy applications easier and quicker on multiple platforms. CircleCI is a popular automation platform that allows you to build and maintain CI/CD workflows for your projects.

      Having continuous deployment is beneficial in many ways. It helps to standardize the deployment steps of an application and to protect it from un-recorded changes. It also helps avoid performing repetitive steps and lets you focus more on development. With CircleCI, you can have a single view across all your different deployment processes for development, testing, and production.

      In this tutorial, you’ll build a Node.js app locally and push it to GitHub. Following that, you’ll configure CircleCI to connect to a virtual private server (VPS) that’s running Ubuntu 18.04, and you’ll go through the steps to set up your code for auto-deployment on the VPS. By the end of the article, you will have a working CI/CD pipeline where CircleCI will pick up any code you push from your local environment to the GitHub repo and deploy it on your VPS.


      Before you get started, you’ll need to have the following:

      Step 1 — Creating a Local Node Project

      In this step, you’ll create a Node.js project locally that you will use during this tutorial as an example application. You’ll push this to a repo on GitHub later.

      Go ahead and run these commands on your local terminal so that you can set up a quick Node development environment.

      First, create a directory for the test project:

      Change into the new directory:

      Follow this up by initializing a npm environment to pull the dependencies if you have any. The -y flag will auto-accept every prompt thrown by npm init:

      For more information on npm, check out our How To Use Node.js Modules with npm and package.json tutorial.

      Next, create a basic server that serves Hello World! when someone accesses any route. Using a text editor, create a file called app.js in the root directory of the project. This tutorial will use nano:

      Add the following code to the app.js file:


      const http = require('http');
      http.createServer(function (req, res) {
        res.write('Hello World!'); 
      }).listen(8080, ''); 

      This sample server uses the http package to listen to any incoming requests on port 8080 and fires a request listener function that replies with the string Hello World.

      Save and close the file.

      You can test this on your local machine by running the following command from the same directory in the terminal. This will create a Node process that runs the server (app.js):

      Now visit the http://localhost:8080 URL in your browser. Your browser will render the string Hello World!. Once you have tested the app, stop the server by pressing CTRL+C on the same terminal where you started the Node process.

      You’ve now set up your sample application. In the next step, you will add a configuration file in the project so that CircleCI can use it for deployment.

      Step 2 — Adding a Config File to Your Project

      CircleCI executes workflows according to a configuration file in your project folder. In this step, you will create that file to define the deployment workflow.

      Create a folder called .circleci in the root directory of your project:

      Add a new file called config.yml in it:

      • nano .circleci/config.yml

      This will open a file with the YAML file extension. YAML is a language that is often used for configuration management.

      Add the following configuration to the new config.yml file:


      version: 2.1
      # Define the jobs we want to run for this project
            - image: arvindr226/alpine-ssh
            - checkout
            - run: ssh -oStrictHostKeyChecking=no -v $USER@$IP "./"
      # Orchestrate our job run sequence
        version: 2
            - pull-and-build:
                      - main

      Save this file and exit the text editor.

      This file tells the CircleCI pipeline the following:

      • There is a job called pull-and-build whose steps involve spinning up a Docker container, SSHing from it to the VPS, and then running the file.
      • The Docker container serves the purpose of creating a temporary environment for executing the commands mentioned in the steps section of the config. In this case, all you need to do is SSH into the VPS and run sh command, so the environment needs to be lightweight but still allow the SSH command. The Docker image arvindr226/alpine-ssh is an Alpine Linux image that supports SSH.
      • is a file that you will create in the VPS. It will run every time as a part of the deployment process and will contain steps specific to your project.
      • In the workflows section, you inform CircleCI that it needs to perform this job based on some filters, which in this case is that only changes to the main branch will trigger this job.

      Next, you will commit and push these files to a GitHub repository. You will do this by running the following commands from the project directory.

      First, initialize the Node.js project directory as a git repo:

      Go ahead and add the new changes to the git repo:

      Then commit the changes:

      • git commit -m "initial commit"

      If this is the first time committing, git will prompt you to run some git config commands to identify you.

      From your browser navigate to GitHub and log in with your GitHub account. Create a new repository called circleci-test without a README or license file. Once you’ve created the repository, return to the command line to push your local files to GitHub.

      To follow GitHub protocol, rename your branch main with the following command:

      Before you push the files for the first time, you need to add GitHub as a remote repository. Do that by running:

      • git remote add origin

      Follow this with the push command, which will transfer the files to GitHub:

      You have now pushed your code to GitHub. In the next step, you’ll create a new user in the VPS that will execute the steps in the pull-and-build part.

      Step 3 — Creating a New User for Deployment

      Now that you have the project ready, you will create a deployment user in the VPS.

      Connect to your VPS as your sudo user

      • ssh your_username@your_server_ip

      Next, create a new user that doesn’t use a password for login using the useradd command.

      • sudo useradd -m -d /home/circleci -s /bin/bash circleci

      This command creates a new user on the system. The -m flag instructs the command to create a home directory specified by the -d flag.

      circleci will be the new deployment user in this case. For security purposes, you are not going to add this user to the sudo group, since the only job of this user is to create an SSH connection from the VPS to the CircleCI network and run the script.

      Make sure that the firewall on your VPS is open to port 8080:

      You now need to create an SSH key, which the new user can use to log in. You are going to create an SSH key with no passphrase, or else CircleCI will not be able to decrypt it. You can find more information in the official CircleCI documentation. Also, CircleCI expects the format of the SSH keys to be in the PEM format, so you are going to enforce that while creating the key pair.

      Back on your local system, move to your home folder:

      Then run the following command:

      • ssh-keygen -m PEM -t rsa -f .ssh/circleci

      This command creates an RSA key with the PEM format specified by the -m flag and the key type specified by the -t flag. You also specify the -f to create a new key pair called circleci and Specifying the name will avoid overwriting your existing id_rsa file.

      Print out the new public key:

      This outputs the public key that you generated. You will need to register this public key in your VPS. Copy this to your clipboard.

      Back on the VPS, create a .ssh directory for the circleci user:

      • sudo mkdir /home/circleci/.ssh

      Here you’ll add the public key you copied from the local machine into a file called authorized_keys:

      • sudo nano /home/circleci/.ssh/authorized_keys

      Add the copied public key here, save the file, and exit the text editor.

      Give the circleci user its directory permissions so that it doesn’t run into permission issues during deployment.

      • sudo chown -R circleci:circleci /home/circleci

      Verify if you can log in as the new user by using the private key. Open a new terminal on your local system and run:

      • ssh circleci@your_server_ip -i ~/.ssh/circleci

      You will now log in as the circleci user into your VPS. This shows that the SSH connection is successful. Next, you will connect your GitHub repo to CircleCI.

      Step 4 — Adding Your GitHub Project to CircleCI

      In this step, you’ll connect your GitHub account to your CircleCI account and add the circleci-test project for CI/CD. If you signed up with your GitHub account, then your GitHub will be automatically linked with your CircleCI account. If not, head over to and connect it.

      To add your circleci-test project, navigate to your CircleCI project dashboard at

      CircleCI Projects Tab

      Here you will find all the projects from GitHub listed. Click on Set Up Project for the project circleci-test. This will bring you to the project setup page:

      Setting up a project in the CircleCI Interface

      You’ll now have the option to set the config for the project, which you have already set in the repo. Since this is already set up, choose the Use Existing Config option. This will bring up a popup box confirming that you want to build the pipeline:

      Popup confirming the config file for the CircleCI build

      From here, go ahead and click on Start Building. This will bring you to the circleci-test pipeline page. For now, this pipeline will fail. This is because you must first update the SSH keys for your project.

      Navigate to the project settings at and select the SSH keys section on the left.

      Retrieve the private key named circleci you created earlier from your local machine by running:

      Copy the output from this command.

      Under the Additional SSH Keys section, click on the Add SSH Key button.

      Adding SSH Keys section of the settings page

      This will open up a window asking you to enter the hostname and the SSH key. Enter a hostname of your choice, and add in the private SSH key that you copied from your local environment.

      CircleCI will now be able to log in as the new circleci user to the VPS using this key.

      The last step is to provide the username and IP of the VPS to CircleCI. In the same Project Settings page, go to the Environment Variables tab on the left:

      Environment Variables section of the settings page

      Add an environment variable named USER with a value of circleci and IP with the value of the IP address of your VPS (or domain name of your VPS, if you have a DNS record).

      Once you’ve created these variables, you have completed the setup needed for CircleCI. Next, you will give the circleci user access to GitHub via SSH.

      Step 5 — Adding SSH Keys to GitHub

      You now need to provide a way that the circleci user can authenticate with GitHub so that it can perform git operations like git pull.

      To do this, you will create an SSH key for this user to authenticate against GitHub.

      Connect to the VPS as the circleci user:

      • ssh circleci@your_server_ip -i ~/.ssh/circleci

      Create a new SSH key pair with no passphrase:

      Then output the public key:

      Copy the output, then head over to your circleci-test GitHub repo’s deploy key settings at

      Click on Add deploy key to add the copied public key. Fill the Title field with your desired name for the key, then add the copied public key in the Key field. Finally, click the Add key button to add the key to your account.

      Now that the circleci user has access to your GitHub account, you’ll use this SSH authentication to set up your project.

      Step 6 — Setting Up the Project on the VPS

      Now for setting up the project, you are going to clone the repo and make the initial setup of the project on the VPS as the circleci user.

      On your VPS, run the following command:

      Navigate into it:

      First, install the dependencies:

      Now test the app out by running the server you built:

      Head over to your browser and try the address http://your_vps_ip:8080. You will receive the output Hello World!.

      Stop this process with CTRL+C and use pm2 to run this app as a background process.

      Install pm2 so that you can run the Node app as an independent process. pm2 is a versatile process manager written in Node.js. Here it will help you keep the sample Node.js project running as an active process even after you log out of the server. You can read a bit more about this in the How To Set Up a Node.js Application for Production on Ubuntu 18.04 tutorial.

      Note: On some systems such as Ubuntu 18.04, installing an npm package globally can result in a permission error, which will interrupt the installation. Since it is a security best practice to avoid using sudo with npm install, you can instead resolve this by changing npm’s default directory. If you encounter an EACCES error, follow the instructions at the official npm documentation.

      You can use the pm2 start command to run the app.js file as a Node process. You can name it app using the --name flag to identify it later:

      • pm2 start app.js --name "app"

      You will also need to provide the deployment instructions. These commands will run every time the circleci user deploys the code.

      Head back to the home directory since that will be the path the circleci user will land in during a successful login attempt:

      Go ahead and create the file, which will contain the deploy instructions:

      You will now use a Bash script to automate the deployment:

      #replace this with the path of your project on the VPS
      cd ~/circleci-test
      #pull from the branch
      git pull origin main
      # followed by instructions specific to your project that you used to do manually
      npm install
      export PATH=~/.npm-global/bin:$PATH
      source ~/.profile
      pm2 restart app

      This will automatically change the working directory to the project root, pull the code from GitHub, install the dependencies, then restart the app. Save and exit the file.

      Make this file an executable by running:

      Now head back to your local machine and make a quick change to test it out. Change into your project directory:

      Open up your app.js file:

      • nano circleci-test/app.js

      Now add in the following highlighted line:


      const http = require('http');
      http.createServer(function (req, res) {
        res.write('Foo Bar!');
      }).listen(8080, '');

      Save the file and exit the text editor.

      Add this change and commit it:

      • git add .
      • git commit -m "modify app.js"

      Now push this to your main branch:

      This will trigger a new pipeline for deployment. Navigate to to view the pipeline in action.

      Once it’s successful, refresh the browser at http://your_vps_ip:8080. Foo Bar! will now render in your browser.


      These are the steps to integrate CircleCI with your GitHub repository and Linux-based VPS. You can modify the for more specific instructions related to your project.

      If you would like to learn more about CI/CD, check out our CI/CD topic page. For more on setting up workflows with CircleCI, head over to the CircleCI documentation.

      Source link

      How To Automate Deployments to DigitalOcean Kubernetes with CircleCI

      The author selected the Tech Education Fund to receive a donation as part of the Write for DOnations program.


      Having an automated deployment process is a requirement for a scalable and resilient application, and GitOps, or Git-based DevOps, has rapidly become a popular method of organizing CI/CD with a Git repository as a “single source of truth.” Tools like CircleCI integrate with your GitHub repository, allowing you to test and deploy your code automatically every time you make a change to your repository. When this kind of CI/CD is combined with the flexibility of Kubernetes infrastructure, you can build an application that scales easily with changing demand.

      In this article you will use CircleCI to deploy a sample application to a DigitalOcean Kubernetes (DOKS) cluster. After reading this tutorial, you’ll be able to apply these same techniques to deploy other CI/CD tools that are buildable as Docker images.


      To follow this tutorial, you’ll need to have:

      For this tutorial, you will use Kubernetes version 1.13.5 and kubectl version 1.10.7.

      Step 1 — Creating Your DigitalOcean Kubernetes Cluster

      Note: You can skip this section if you already have a running DigitalOcean Kubernetes cluster.

      In this first step, you will create the DigitalOcean Kubernetes (DOKS) cluster from which you will deploy your sample application. The kubectl commands executed from your local machine will change or retrieve information directly from the Kubernetes cluster.

      Go to the Kubernetes page on your DigitalOcean account.

      Click Create a Kubernetes cluster, or click the green Create button at the top right of the page and select Clusters from the dropdown menu.

      [Creating a Kubernetes Cluster on DigitalOcean](

      The next page is where you are going to specify the details of your cluster. On Select a Kubernetes version pick version 1.13.5-do.0. If this one is not available, choose a higher one.

      For Choose a datacenter region, choose the region closest to you. This tutorial will use San Francisco – 2.

      You then have the option to build your Node pool(s). On Kubernetes, a node is a worker machine, which contains the services necessary to run pods. On DigitalOcean, each node is a Droplet. Your node pool will consist of a single Standard node. Select the 2GB/1vCPU configuration and change to 1 Node on the number of nodes.

      You can add extra tags if you want; this can be useful if you plan to use DigitalOcean API or just to better organize your node pools.

      On Choose a name, for this tutorial, use kubernetes-deployment-tutorial. This will make it easier to follow throughout while reading the next sections. Finally, click the green Create Cluster button to create your cluster.

      After cluster creation, there will be a button on the UI to download a configuration file called Download Config File. This is the file you will be using to authenticate the kubectl commands you are going to run against your cluster. Download it to your kubectl machine.

      The default way to use that file is to always pass the --kubeconfig flag and the path to it on all commands you run with kubectl. For example, if you downloaded the config file to Desktop, you would run the kubectl get pods command like this:

      • kubectl --kubeconfig ~/Desktop/kubernetes-deployment-tutorial-kubeconfig.yaml get pods

      This would yield the following output:


      No resources found.

      This means you accessed your cluster. The No resources found. message is correct, since you don’t have any pods on your cluster.

      If you are not maintaining any other Kubernetes clusters you can copy the kubeconfig file to a folder on your home directory called .kube. Create that directory in case it does not exist:

      Then copy the config file into the newly created .kube directory and rename it config:

      • cp current_kubernetes-deployment-tutorial-kubeconfig.yaml_file_path ~/.kube/config

      The config file should now have the path ~/.kube/config. This is the file that kubectl reads by default when running any command, so there is no need to pass --kubeconfig anymore. Run the following:

      You will receive the following output:


      No resources found.

      Now access the cluster with the following:

      You will receive the list of nodes on your cluster. The output will be similar to this:


      NAME STATUS ROLES AGE VERSION kubernetes-deployment-tutorial-1-7pto Ready <none> 1h v1.13.5

      In this tutorial you are going to use the default namespace for all kubectl commands and manifest files, which are files that define the workload and operating parameters of work in Kubernetes. Namespaces are like virtual clusters inside your single physical cluster. You can change to any other namespace you want; just make sure to always pass it using the --namespace flag to kubectl, and/or specifying it on the Kubernetes manifests metadata field. They are a great way to organize the deployments of your team and their running environments; read more about them in the official Kubernetes overview on Namespaces.

      By finishing this step you are now able to run kubectl against your cluster. In the next step, you will create the local Git repository you are going to use to house your sample application.

      Step 2 — Creating the Local Git Repository

      You are now going to structure your sample deployment in a local Git repository. You will also create some Kubernetes manifests that will be global to all deployments you are going to do on your cluster.

      Note: This tutorial has been tested on Ubuntu 18.04, and the individual commands are styled to match this OS. However, most of the commands here can be applied to other Linux distributions with little to no change needed, and commands like kubectl are platform-agnostic.

      First, create a new Git repository locally that you will push to GitHub later on. Create an empty folder called do-sample-app in your home directory and cd into it:

      • mkdir ~/do-sample-app
      • cd ~/do-sample-app

      Now create a new Git repository in this folder with the following command:

      Inside this repository, create an empty folder called kube:

      • mkdir ~/do-sample-app/kube/

      This will be the location where you are going to store the Kubernetes resources manifests related to the sample application that you will deploy to your cluster.

      Now, create another folder called kube-general, but this time outside of the Git repository you just created. Make it inside your home directory:

      This folder is outside of your Git repository because it will be used to store manifests that are not specific to a single deployment on your cluster, but common to multiple ones. This will allow you to reuse these general manifests for different deployments.

      With your folders created and the Git repository of your sample application in place, it's time to arrange the authentication and authorization of your DOKS cluster.

      Step 3 — Creating a Service Account

      It's generally not recommended to use the default admin user to authenticate from other Services into your Kubernetes cluster. If your keys on the external provider got compromised, your whole cluster would become compromised.

      Instead you are going to use a single Service Account with a specific Role, which is all part of the RBAC Kubernetes authorization model.

      This authorization model is based on Roles and Resources. You start by creating a Service Account, which is basically a user on your cluster, then you create a Role, in which you specify what resources it has access to on your cluster. Finally, you create a Role Binding, which is used to make the connection between the Role and the Service Account previously created, granting to the Service Account access to all resources the Role has access to.

      The first Kubernetes resource you are going to create is the Service Account for your CI/CD user, which this tutorial will name cicd.

      Create the file cicd-service-account.yml inside the ~/kube-general folder, and open it with your favorite text editor:

      • nano ~/kube-general/cicd-service-account.yml

      Write the following content on it:


      apiVersion: v1
      kind: ServiceAccount
        name: cicd
        namespace: default

      This is a YAML file; all Kubernetes resources are represented using one. In this case you are saying this resource is from Kubernetes API version v1 (internally kubectl creates resources by calling Kubernetes HTTP APIs), and it is a ServiceAccount.

      The metadata field is used to add more information about this resource. In this case, you are giving this ServiceAccount the name cicd, and creating it on the default namespace.

      You can now create this Service Account on your cluster by running kubectl apply, like the following:

      • kubectl apply -f ~/kube-general/

      You will recieve output similar to the following:


      serviceaccount/cicd created

      To make sure your Service Account is working, try to log in to your cluster using it. To do that you first need to obtain their respective access token and store it in an environment variable. Every Service Account has an access token which Kubernetes stores as a Secret.

      You can retrieve this secret using the following command:

      • TOKEN=$(kubectl get secret $(kubectl get secret | grep cicd-token | awk '{print $1}') -o jsonpath='{.data.token}' | base64 --decode)

      Some explanation on what this command is doing:

      $(kubectl get secret | grep cicd-token | awk '{print $1}')

      This is used to retrieve the name of the secret related to our cicd Service Account. kubectl get secret returns the list of secrets on the default namespace, then you use grep to search for the lines related to your cicd Service Account. Then you return the name, since it is the first thing on the single line returned from the grep.

      kubectl get secret preceding-command -o jsonpath='{.data.token}' | base64 --decode

      This will retrieve only the secret for your Service Account token. You then access the token field using jsonpath, and pass the result to base64 --decode. This is necessary because the token is stored as a Base64 string. The token itself is a JSON Web Token.

      You can now try to retrieve your pods with the cicd Service Account. Run the following command, replacing server-from-kubeconfig-file with the server URL that can be found after server: in ~kube/config. This command will give a specific error that you will learn about later in this tutorial:

      • kubectl --insecure-skip-tls-verify --kubeconfig="/dev/null" --server=server-from-kubeconfig-file --token=$TOKEN get pods

      --insecure-skip-tls-verify skips the step of verifying the certificate of the server, since you are just testing and do not need to verify this. --kubeconfig="/dev/null" is to make sure kubectl does not read your config file and credentials but instead uses the token provided.

      The output should be similar to this:


      Error from server (Forbidden): pods is forbidden: User "system:serviceaccount:default:cicd" cannot list resource "pods" in API group "" in the namespace "default"

      This is an error, but it shows us that the token worked. The error you received is about your Service Account not having the neccessary authorization to list the resource secrets, but you were able to access the server itself. If your token had not worked, the error would have been the following one:


      error: You must be logged in to the server (Unauthorized)

      Now that the authentication was a success, the next step is to fix the authorization error for the Service Account. You will do this by creating a role with the necessary permissions and binding it to your Service Account.

      Step 4 — Creating the Role and the Role Binding

      Kubernetes has two ways to define roles: using a Role or a ClusterRole resource. The difference between the former and the latter is that the first one applies to a single namespace, while the other is valid for the whole cluster.

      As you are using a single namespace on this tutorial, you will use a Role.

      Create the file ~/kube-general/cicd-role.yml and open it with your favorite text editor:

      • nano ~/kube-general/cicd-role.yml

      The basic idea is to grant access to do everything related to most Kubernetes resources in the default namespace. Your Role would look like this:


      kind: Role
        name: cicd
        namespace: default
        - apiGroups: ["", "apps", "batch", "extensions"]
          resources: ["deployments", "services", "replicasets", "pods", "jobs", "cronjobs"]
          verbs: ["*"]

      This YAML has some similarities with the one you created previously, but here you are saying this resource is a Role, and it's from the Kubernetes API You are naming your role cicd, and creating it on the same namespace you created your ServiceAccount, the default one.

      Then you have the rules field, which is a list of resources this role has access to. In Kubernetes resources are defined based on the API group they belong to, the resource kind itself, and what actions you can do on then, which is represented by a verb. Those verbs are similar to the HTTP ones.

      In our case you are saying that your Role is allowed to do everything, *, on the following resources: deployments, services, replicasets, pods, jobs, and cronjobs. This also applies to those resources belonging to the following API groups: "" (empty string), apps, batch, and extensions. The empty string means the root API group. If you use apiVersion: v1 when creating a resource it means this resource is part of this API group.

      A Role by itself does nothing; you must also create a RoleBinding, which binds a Role to something, in this case, a ServiceAccount.

      Create the file ~/kube-general/cicd-role-binding.yml and open it:

      • nano ~/kube-general/cicd-role-binding.yml

      Add the following lines to the file:


      kind: RoleBinding
        name: cicd
        namespace: default
        - kind: ServiceAccount
          name: cicd
          namespace: default
        kind: Role
        name: cicd

      Your RoleBinding has some specific fields that have not yet been covered in this tutorial. roleRef is the Role you want to bind to something; in this case it is the cicd role you created earlier. subjects is the list of resources you are binding your role to; in this case it's a single ServiceAccount called cicd.

      Note: If you had used a ClusterRole, you would have to create a ClusterRoleBinding instead of a RoleBinding. The file would be almost the same. The only difference would be that it would have no namespace field inside the metadata.

      With those files created you will be able to use kubectl apply again. Create those new resources on your Kubernetes cluster by running the following command:

      • kubectl apply -f ~/kube-general/

      You will receive output similar to the following:

      Output created created serviceaccount/cicd created

      Now, try the command you ran previously:

      • kubectl --insecure-skip-tls-verify --kubeconfig="/dev/null" --server=server-from-kubeconfig-file --token=$TOKEN get pods

      Since you have no pods, this will yield the following output:


      No resources found.

      In this step, you gave the Service Account you are going to use on CircleCI the necessary authorization to do meaningful actions on your cluster like listing, creating, and updating resources. Now it's time to create your sample application.

      Step 5 — Creating Your Sample Application

      Note: All commands and files created from now on will start from the folder ~/do-sample-app you created earlier. This is becase you are now creating files specific to the sample application that you are going to deploy to your cluster.

      The Kubernetes Deployment you are going to create will use the Nginx image as a base, and your application will be a simple static HTML page. This is a great start because it allows you to test if your deployment works by serving a simple HTML directly from Nginx. As you will see later on, you can redirect all traffic coming to a local address:port to your deployment on your cluster to test if it's working.

      Inside the repository you set up earlier, create a new Dockerfile file and open it with your text editor of choice:

      • nano ~/do-sample-app/Dockerfile

      Write the following on it:


      FROM nginx:1.14
      COPY index.html /usr/share/nginx/html/index.html

      This will tell Docker to build the application container from an nginx image.

      Now create a new index.html file and open it:

      • nano ~/do-sample-app/index.html

      Write the following HTML content:


      <!DOCTYPE html>
        Kubernetes Sample Application

      This HTML will display a simple message that will let you know if your application is working.

      You can test if the image is correct by building and then running it.

      First, build the image with the following command, replacing dockerhub-username with your own Docker Hub username. You must specify your username here so when you push it later on to Docker Hub it will just work:

      • docker build ~/do-sample-app/ -t dockerhub-username/do-kubernetes-sample-app

      Now run the image. Use the following command, which starts your image and forwards any local traffic on port 8080 to the port 80 inside the image, the port Nginx listens to by default:

      • docker run --rm -it -p 8080:80 dockerhub-username/do-kubernetes-sample-app

      The command prompt will stop being interactive while the command is running. Instead you will see the Nginx access logs. If you open localhost:8080 on any browser it should show an HTML page with the content of ~/do-sample-app/index.html. In case you don't have a browser available, you can open a new terminal window and use the following curl command to fetch the HTML from the webpage:

      You will receive the following output:


      <!DOCTYPE html> <title>DigitalOcean</title> <body> Kubernetes Sample Application </body>

      Stop the container (CTRL + C on the terminal where it's running), and submit this image to your Docker Hub account. To do this, first log in to Docker Hub:

      Fill in the required information about your Docker Hub account, then push the image with the following command (don't forget to replace the dockerhub-username with your own):

      • docker push dockerhub-username/do-kubernetes-sample-app

      You have now pushed your sample application image to your Docker Hub account. In the next step, you will create a Deployment on your DOKS cluster from this image.

      Step 6 — Creating the Kubernetes Deployment and Service

      With your Docker image created and working, you will now create a manifest telling Kubernetes how to create a Deployment from it on your cluster.

      Create the YAML deployment file ~/do-sample-app/kube/do-sample-deployment.yml and open it with your text editor:

      • nano ~/do-sample-app/kube/do-sample-deployment.yml

      Write the following content on the file, making sure to replace dockerhub-username with your Docker Hub username:


      apiVersion: apps/v1
      kind: Deployment
        name: do-kubernetes-sample-app
        namespace: default
          app: do-kubernetes-sample-app
        replicas: 1
            app: do-kubernetes-sample-app
              app: do-kubernetes-sample-app
              - name: do-kubernetes-sample-app
                image: dockerhub-username/do-kubernetes-sample-app:latest
                  - containerPort: 80
                    name: http

      Kubernetes deployments are from the API group apps, so the apiVersion of your manifest is set to apps/v1. On metadata you added a new field you have not used previously, called metadata.labels. This is useful to organize your deployments. The field spec represents the behavior specification of your deployment. A deployment is responsible for managing one or more pods; in this case it's going to have a single replica by the spec.replicas field. That is, it's going to create and manage a single pod.

      To manage pods, your deployment must know which pods it's responsible for. The spec.selector field is the one that gives it that information. In this case the deployment will be responsible for all pods with tags app=do-kubernetes-sample-app. The spec.template field contains the details of the Pod this deployment will create. Inside the template you also have a spec.template.metadata field. The labels inside this field must match the ones used on spec.selector. spec.template.spec is the specification of the pod itself. In this case it contains a single container, called do-kubernetes-sample-app. The image of that container is the image you built previously and pushed to Docker Hub.

      This YAML file also tells Kubernetes that this container exposes the port 80, and gives this port the name http.

      To access the port exposed by your Deployment, create a Service. Make a file named ~/do-sample-app/kube/do-sample-service.yml and open it with your favorite editor:

      • nano ~/do-sample-app/kube/do-sample-service.yml

      Next, add the following lines to the file:


      apiVersion: v1
      kind: Service
        name: do-kubernetes-sample-app
        namespace: default
          app: do-kubernetes-sample-app
        type: ClusterIP
          - port: 80
            targetPort: http
            name: http
          app: do-kubernetes-sample-app

      This file gives your Service the same labels used on your deployment. This is not required, but it helps to organize your applications on Kubernetes.

      The service resource also has a spec field. The spec.type field is responsible for the behavior of the service. In this case it's a ClusterIP, which means the service is exposed on a cluster-internal IP, and is only reachable from within your cluster. This is the default spec.type for services. spec.selector is the label selector criteria that should be used when picking the pods to be exposed by this service. Since your pod has the tag app: do-kubernetes-sample-app, you used it here. spec.ports are the ports exposed by the pod's containers that you want to expose from this service. Your pod has a single container which exposes port 80, named http, so you are using it here as targetPort. The service exposes that port on port 80 too, with the same name, but you could have used a different port/name combination than the one from the container.

      With your Service and Deployment manifest files created, you can now create those resources on your Kubernetes cluster using kubectl:

      • kubectl apply -f ~/do-sample-app/kube/

      You will receive the following output:


      deployment.apps/do-kubernetes-sample-app created service/do-kubernetes-sample-app created

      Test if this is working by forwarding one port on your machine to the port that the service is exposing inside your Kubernetes cluster. You can do that using kubectl port-forward:

      • kubectl port-forward $(kubectl get pod --selector="app=do-kubernetes-sample-app" --output jsonpath='{.items[0]}') 8080:80

      The subshell command $(kubectl get pod --selector="app=do-kubernetes-sample-app" --output jsonpath='{.items[0]}') retrieves the name of the pod matching the tag you used. Otherwise you could have retrieved it from the list of pods by using kubectl get pods.

      After you run port-forward, the shell will stop being interactive, and will instead output the requests redirected to your cluster:


      Forwarding from -> 80 Forwarding from [::1]:8080 -> 80

      Opening localhost:8080 on any browser should render the same page you saw when you ran the container locally, but it's now coming from your Kubernetes cluster! As before, you can also use curl in a new terminal window to check if it's working:

      You will receive the following output:


      <!DOCTYPE html> <title>DigitalOcean</title> <body> Kubernetes Sample Application </body>

      Next, it's time to push all the files you created to your GitHub repository. To do this you must first create a repository on GitHub called digital-ocean-kubernetes-deploy.

      In order to keep this repository simple for demonstration purposes, do not initialize the new repository with a README, license, or .gitignore file when asked on the GitHub UI. You can add these files later on.

      With the repository created, point your local repository to the one on GitHub. To do this, press CTRL + C to stop kubectl port-forward and get the command line back, then run the following commands to add a new remote called origin:

      • cd ~/do-sample-app/
      • git remote add origin

      There should be no output from the preceding command.

      Next, commit all the files you created up to now to the GitHub repository. First, add the files:

      Next, commit the files to your repository, with a commit message in quotation marks:

      • git commit -m "initial commit"

      This will yield output similar to the following:


      [master (root-commit) db321ad] initial commit 4 files changed, 47 insertions(+) create mode 100644 Dockerfile create mode 100644 index.html create mode 100644 kube/do-sample-deployment.yml create mode 100644 kube/do-sample-service.yml

      Finally, push the files to GitHub:

      • git push -u origin master

      You will be prompted for your username and password. Once you have entered this, you will see output like this:


      Counting objects: 7, done. Delta compression using up to 8 threads. Compressing objects: 100% (7/7), done. Writing objects: 100% (7/7), 907 bytes | 0 bytes/s, done. Total 7 (delta 0), reused 0 (delta 0) To * [new branch] master -> master Branch master set up to track remote branch master from origin.

      If you go to your GitHub repository page you will now see all the files there. With your project up on GitHub, you can now set up CircleCI as your CI/CD tool.

      Step 7 — Configuring CircleCI

      For this tutorial, you will use CircleCI to automate deployments of your application whenever the code is updated, so you will need to log in to CircleCI using your GitHub account and set up your repository.

      First, go to their homepage, and press Sign Up.


      You are using GitHub, so click the green Sign Up with GitHub button.

      CircleCI will redirect to an authorization page on GitHub. CircleCI needs some permissions on your account to be able to start building your projects. This allows CircleCI to obtain your email, deploy keys and permission to create hooks on your repositories, and add SSH keys to your account. If you need more information on what CircleCI is going to do with your data, check their documentation about GitHub integration.


      After authorizing CircleCI you will be redirected to their dashboard.


      Next, set up your GitHub repository in CircleCI. Click on Set Up New Projects from the CircleCI Dashboard, or as a shortcut, open the following link changing the highlighted text with your own GitHub username:

      After that press Start Building. Do not create a config file in your repository just yet, and don't worry if the first build fails.


      Next, specify some environment variables in the CircleCI settings. You can find the settings of the project by clicking on the small button with a cog icon on the top right section of the page then selecting Environment Variables, or you can go directly to the environment variables page by using the following URL (remember to fill in your username): Press Add Variable to create new environment variables.

      First, add two environment variables called DOCKERHUB_USERNAME and DOCKERHUB_PASS which will be needed later on to push the image to Docker Hub. Set the values to your Docker Hub username and password, respectively.


      The value of KUBERNETES_TOKEN will be the value of the local environment variable you used earlier to authenticate on your Kubernetes cluster using your Service Account user. If you have closed the terminal, you can always run the following command to retrieve it again:

      • kubectl get secret $(kubectl get secret | grep cicd-token | awk '{print $1}') -o jsonpath='{.data.token}' | base64 --decode

      KUBERNETES_SERVER will be the string you passed as the --server flag to kubectl when you logged in with your cicd Service Account. You can find this after server: in the ~/.kube/config file, or in the file kubernetes-deployment-tutorial-kubeconfig.yaml downloaded from the DigitalOcean dashboard when you made the initial setup of your Kubernetes cluster.

      KUBERNETES_CLUSTER_CERTIFICATE should also be available on your ~/.kube/config file. It's the certificate-authority-data field on the clusters item related to your cluster. It should be a long string; make sure to copy all of it.

      Those environment variables must be defined here because most of them contain sensitive information, and it is not secure to place them directly on the CircleCI YAML config file.

      With CircleCI listening for changes on your repository, and the environment variables configured, it's time to create the configuration file.

      Make a directory called .circleci inside your sample application repository:

      • mkdir ~/do-sample-app/.circleci/

      Inside this directory, create a file named config.yml and open it with your favorite editor:

      • nano ~/do-sample-app/.circleci/config.yml

      Add the following content to the file, making sure to replace dockerhub-username with your Docker Hub username:


      version: 2.1
            - image: circleci/buildpack-deps:stretch
            IMAGE_NAME: dockerhub-username/do-kubernetes-sample-app
          working_directory: ~/app
            - checkout
            - setup_remote_docker
            - run:
                name: Build Docker image
                command: |
                  docker build -t $IMAGE_NAME:latest .
            - run:
                name: Push Docker Image
                command: |
                  echo "$DOCKERHUB_PASS" | docker login -u "$DOCKERHUB_USERNAME" --password-stdin
                  docker push $IMAGE_NAME:latest
        version: 2
            - build:
                    only: master

      This sets up a Workflow with a single job, called build, that runs for every commit to the master branch. This job is using the image circleci/buildpack-deps:stretch to run its steps, which is an image from CircleCI based on the official buildpack-deps Docker image, but with some extra tools installed, like Docker binaries themselves.

      The workflow has four steps:

      • checkout retrieves the code from GitHub.
      • setup_remote_docker sets up a remote, isolated environment for each build. This is required before you use any docker command inside a job step. This is necessary because as the steps are running inside a docker image, setup_remote_docker allocates another machine to run the commands there.
      • The first run step builds the image, as you did previously locally. For that you are using the environment variable you declared in environment:, IMAGE_NAME (remember to change the highlighted section with your own information).
      • The last run step pushes the image to Dockerhub, using the environment variables you configured on the project settings to authenticate.

      Commit the new file to your repository and push the changes upstream:

      • cd ~/do-sample-app/
      • git add .circleci/
      • git commit -m "add CircleCI config"
      • git push

      This will trigger a new build on CircleCI. The CircleCI workflow is going to correctly build and push your image to Docker Hub.

      CircleCI build page with success build info

      Now that you have created and tested your CircleCI workflow, you can set your DOKS cluster to retrieve the up-to-date image from Docker Hub and deploy it automatically when changes are made.

      Step 8 — Updating the Deployment on the Kubernetes Cluster

      Now that your application image is being built and sent to Docker Hub every time you push changes to the master branch on GitHub, it's time to update your deployment on your Kubernetes cluster so that it retrieves the new image and uses it as a base for deployment.

      To do that, first fix one issue with your deployment: it's currently depending on an image with the latest tag. This tag does not tell us which version of the image you are using. You cannot easily lock your deployment to that tag because it's overwritten everytime you push a new image to Docker Hub, and by using it like that you lose one of the best things about having containerized applications: Reproducibility.

      You can read more about that on this article about why depending on Docker latest tag is a anti-pattern.

      To correct this, you first must make some changes to your Push Docker Image build step in the ~/do-sample-app/.circleci/config.yml file. Open up the file:

      • nano ~/do-sample-app/.circleci/config.yml

      Then add the highlighted lines to your Push Docker Image step:


            - run:
                name: Push Docker Image
                command: |
                  echo "$DOCKERHUB_PASS" | docker login -u "$DOCKERHUB_USERNAME" --password-stdin
                  docker tag $IMAGE_NAME:latest $IMAGE_NAME:$CIRCLE_SHA1
                  docker push $IMAGE_NAME:latest
                  docker push $IMAGE_NAME:$CIRCLE_SHA1

      Save and exit the file.

      CircleCI has some special environment variables set by default. One of them is CIRCLE_SHA1, which contains the hash of the commit it's building. The changes you made to ~/do-sample-app/.circleci/config.yml will use this environment variable to tag your image with the commit it was built from, always tagging the most recent build with the latest tag. That way, you always have specific images available, without overwriting them when you push something new to your repository.

      Next, change your deployment manifest file to point to that file. This would be simple if inside ~/do-sample-app/kube/do-sample-deployment.yml you could set your image as dockerhub-username/do-kubernetes-sample-app:$COMMIT_SHA1, but kubectl doesn't do variable substitution inside the manifests when you use kubectl apply. To account for this, you can use envsubst. envsubst is a cli tool, part of the GNU gettext project. It allows you to pass some text to it, and if it finds any variable inside the text that has a matching environment variable, it's replaced by the respective value. The resulting text is then returned as their output.

      To use this, you will create a simple bash script which will be responsible for your deployment. Make a new folder called scripts inside ~/do-sample-app/:

      • mkdir ~/do-sample-app/scripts/

      Inside that folder create a new bash script called and open it with your favorite text editor:

      • nano ~/do-sample-app/scripts/

      Inside it write the following bash script:


      #! /bin/bash
      # exit script when any command ran here returns with non-zero exit code
      set -e
      # We must export it so it's available for envsubst
      export COMMIT_SHA1=$COMMIT_SHA1
      # since the only way for envsubst to work on files is using input/output redirection,
      #  it's not possible to do in-place substitution, so we need to save the output to another file
      #  and overwrite the original with that one.
      envsubst <./kube/do-sample-deployment.yml >./kube/do-sample-deployment.yml.out
      mv ./kube/do-sample-deployment.yml.out ./kube/do-sample-deployment.yml
      echo "$KUBERNETES_CLUSTER_CERTIFICATE" | base64 --decode > cert.crt
        apply -f ./kube/

      Let's go through this script, using the comments in the file. First, there is the following:

      set -e

      This line makes sure any failed command stops the execution of the bash script. That way if one command fails, the next ones are not executed.

      export COMMIT_SHA1=$COMMIT_SHA1

      These lines export the CircleCI $CIRCLE_SHA1 environment variable with a new name. If you had just declared the variable without exporting it using export, it would not be visible for the envsubst command.

      envsubst <./kube/do-sample-deployment.yml >./kube/do-sample-deployment.yml.out
      mv ./kube/do-sample-deployment.yml.out ./kube/do-sample-deployment.yml

      envsubst cannot do in-place substitution. That is, it cannot read the content of a file, replace the variables with their respective values, and write the output back to the same file. Therefore, you will redirect the output to another file and then overwrite the original file with the new one.

      echo "$KUBERNETES_CLUSTER_CERTIFICATE" | base64 --decode > cert.crt

      The environment variable $KUBERNETES_CLUSTER_CERTIFICATE you created earlier on CircleCI's project settings is in reality a Base64 encoded string. To use it with kubectl you must decode its contents and save it to a file. In this case you are saving it to a file named cert.crt inside the current working directory.

        apply -f ./kube/

      Finally, you are running kubectl. The command has similar arguments to the one you ran when you were testing your Service Account. You are calling apply -f ./kube/, since on CircleCI the current working directory is the root folder of your project. ./kube/ here is your ~/do-sample-app/kube folder.

      Save the file and make sure it's executable:

      • chmod +x ~/do-sample-app/scripts/

      Now, edit ~/do-sample-app/kube/do-sample-deployment.yml:

      • nano ~/do-sample-app/kube/do-sample-deployment.yml

      Change the tag of the container image value to look like the following one:


            # ...
              - name: do-kubernetes-sample-app
                image: dockerhub-username/do-kubernetes-sample-app:$COMMIT_SHA1
                  - containerPort: 80
                    name: http

      Save and close the file. You must now add some new steps to your CI configuration file to update the deployment on Kubernetes.

      Open ~/do-sample-app/.circleci/config.yml on your favorite text editor:

      • nano ~/do-sample-app/.circleci/config.yml

      Write the following new steps, right below the Push Docker Image one you had before:


            - run:
                name: Install envsubst
                command: |
                  sudo apt-get update && sudo apt-get -y install gettext-base
            - run:
                name: Install kubectl
                command: |
                  curl -LO$(curl -s
                  chmod u+x ./kubectl
            - run:
                name: Deploy Code
                command: ./scripts/

      The first two steps are installing some dependencies, first envsubst, and then kubectl. The Deploy Code step is responsible for running our deploy script.

      To make sure the changes are really going to be reflected on your Kubernetes deployment, edit your index.html. Change the HTML to something else, like:


      <!DOCTYPE html>
        Automatic Deployment is Working!

      Once you have saved the above change, commit all the modified files to the repository, and push the changes upstream:

      • cd ~/do-sample-app/
      • git add --all
      • git commit -m "add deploy script and add new steps to circleci config"
      • git push

      You will see the new build running on CircleCI, and successfully deploying the changes to your Kubernetes cluster.

      Wait for the build to finish, then run the same command you ran previously:

      • kubectl port-forward $(kubectl get pod --selector="app=do-kubernetes-sample-app" --output jsonpath='{.items[0]}') 8080:80

      Make sure everything is working by opening your browser on the URL localhost:8080 or by making a curl request to it. It should show the updated HTML:

      You will receive the following output:


      <!DOCTYPE html> <title>DigitalOcean</title> <body> Automatic Deployment is Working! </body>

      Congratulations, you have set up automated deployment with CircleCI!


      This was a basic tutorial on how to do deployments to DigitalOcean Kubernetes using CircleCI. From here, you can improve your pipeline in many ways. The first thing you can do is create a single build job for multiple deployments, each one deploying to different Kubernetes clusters or different namespaces. This can be extremely useful when you have different Git branches for development/staging/production environments, ensuring that the deployments are always separated.

      You could also build your own image to be used on CircleCI, instead of using buildpack-deps. This image could be based on it, but could already have kubectl and envsubst dependencies installed.

      If you would like to learn more about CI/CD on Kubernetes, check out the tutorials for our CI/CD on Kubernetes Webinar Series, or for more information about apps on Kubernetes, see Modernizing Applications for Kubernetes.

      Source link