Continuous Delivery with Jenkins in Kubernetes Engine

Join Sign in

Continuous Delivery with Jenkins in Kubernetes Engine

1 hour 15 minutes 5 Credits


Google Cloud self-paced labs logo


In this lab, you will learn how to set up a continuous delivery pipeline with Jenkins on Kubernetes engine. Jenkins is the go-to automation server used by developers who frequently integrate their code in a shared repository. The solution you'll build in this lab will be similar to the following diagram:

Jenkins and Kubernetes architecture

In the Cloud Architecture Center, see Jenkins on Kubernetes Engine to learn more about running Jenkins on Kubernetes.

What you'll learn

In this lab, you'll complete the following tasks to learn about running Jenkins on Kubernets:

  • Provision a Jenkins application into a Kubernetes Engine Cluster
  • Set up your Jenkins application using Helm Package Manager
  • Explore the features of a Jenkins application
  • Create and exercise a Jenkins pipeline


This is an advanced level lab. Before taking it, you should be comfortable with at least the basics of shell programming, Kubernetes, and Jenkins. Here are some Qwiklabs that can get you up to speed:

Once you are prepared, scroll down to learn more about Kubernetes, Jenkins, and Continuous Delivery.

What is Kubernetes Engine?

Kubernetes Engine is Google Cloud's hosted version of Kubernetes - a powerful cluster manager and orchestration system for containers. Kubernetes is an open source project that can run on many different environments—from laptops to high-availability multi-node clusters; from virtual machines to bare metal. As mentioned before, Kubernetes apps are built on containers - these are lightweight applications bundled with all the necessary dependencies and libraries to run them. This underlying structure makes Kubernetes applications highly available, secure, and quick to deploy—an ideal framework for cloud developers.

What is Jenkins?

Jenkins is an open-source automation server that lets you flexibly orchestrate your build, test, and deployment pipelines. Jenkins allows developers to iterate quickly on projects without worrying about overhead issues that can stem from continuous delivery.

What is Continuous Delivery / Continuous Deployment?

When you need to set up a continuous delivery (CD) pipeline, deploying Jenkins on Kubernetes Engine provides important benefits over a standard VM-based deployment.

When your build process uses containers, one virtual host can run jobs on multiple operating systems. Kubernetes Engine provides ephemeral build executors—these are only utilized when builds are actively running, which leaves resources for other cluster tasks such as batch processing jobs. Another benefit of ephemeral build executors is speed—they launch in a matter of seconds.

Kubernetes Engine also comes pre-equipped with Google's global load balancer, which you can use to automate web traffic routing to your instance(s). The load balancer handles SSL termination and utilizes a global IP address that's configured with Google's backbone network—coupled with your web front, this load balancer will always set your users on the fastest possible path to an application instance.

Now that you've learned a little bit about Kubernetes, Jenkins, and how the two interact in a CD pipeline, it's time to go build one.

Setup and requirements

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.

This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

  • Access to a standard internet browser (Chrome browser recommended).
Note: Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.
  • Time to complete the lab---remember, once you start, you cannot pause a lab.
Note: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your account.

How to start your lab and sign in to the Google Cloud Console

  1. Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:

    • The Open Google Console button
    • Time remaining
    • The temporary credentials that you must use for this lab
    • Other information, if needed, to step through this lab
  2. Click Open Google Console. The lab spins up resources, and then opens another tab that shows the Sign in page.

    Tip: Arrange the tabs in separate windows, side-by-side.

    Note: If you see the Choose an account dialog, click Use Another Account.
  3. If necessary, copy the Username from the Lab Details panel and paste it into the Sign in dialog. Click Next.

  4. Copy the Password from the Lab Details panel and paste it into the Welcome dialog. Click Next.

    Important: You must use the credentials from the left panel. Do not use your Google Cloud Skills Boost credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.
  5. Click through the subsequent pages:

    • Accept the terms and conditions.
    • Do not add recovery options or two-factor authentication (because this is a temporary account).
    • Do not sign up for free trials.

After a few moments, the Cloud Console opens in this tab.

Note: You can view the menu with a list of Google Cloud Products and Services by clicking the Navigation menu at the top-left. Navigation menu icon

Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

  1. Click Activate Cloud Shell Activate Cloud Shell icon at the top of the Google Cloud console.

  2. Click Continue.

It takes a few moments to provision and connect to the environment. When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. The output contains a line that declares the PROJECT_ID for this session:

Your Cloud Platform project in this session is set to YOUR_PROJECT_ID

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

  1. (Optional) You can list the active account name with this command:

gcloud auth list


ACTIVE: * ACCOUNT: To set the active account, run: $ gcloud config set account `ACCOUNT`
  1. (Optional) You can list the project ID with this command:

gcloud config list project


[core] project = <project_ID>

Example output:

[core] project = qwiklabs-gcp-44776a13dea667a6 Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Download the source code

To get set up, open a new session in Cloud Shell and run the following command to set your zone :

gcloud config set compute/zone {{{project_0.default_zone}}}
  1. Then copy the lab's sample code:

gsutil cp gs://spls/gsp051/ . unzip
  1. Now change to the correct directory:

cd continuous-deployment-on-kubernetes

Task 2. Provisioning Jenkins

Creating a Kubernetes cluster

  1. Now, run the following command to provision a Kubernetes cluster:

gcloud container clusters create jenkins-cd \ --num-nodes 2 \ --machine-type n1-standard-2 \ --scopes ",cloud-platform"

This step can take up to several minutes to complete. The extra scopes enable Jenkins to access Cloud Source Repositories and Google Container Registry.

Test completed task

Click Check my progress to verify your performed task. If you have successfully created a Kubernetes cluster, you'll see an assessment score.

Create a Kubernetes cluster (zone: )
  1. Before continuing, confirm that your cluster is running by executing the following command:

gcloud container clusters list
  1. Now, get the credentials for your cluster:

gcloud container clusters get-credentials jenkins-cd
  1. Kubernetes Engine uses these credentials to access your newly provisioned cluster—confirm that you can connect to it by running the following command:

kubectl cluster-info

Task 3. Setup Helm

In this lab, you will use Helm to install Jenkins from the Charts repository. Helm is a package manager that makes it easy to configure and deploy Kubernetes applications. Once you have Jenkins installed, you'll be able to set up your CI/CD pipeline.

  1. Add Helm's stable chart repo:

helm repo add jenkins
  1. Ensure the repo is up to date:

helm repo update

Task 4. Configure and Install Jenkins

When installing Jenkins, a values file can be used as a template to provide values that are necessary for setup.

You will use a custom values file to automatically configure your Kubernetes Cloud and add the following necessary plugins:

  • Kubernetes:1.29.4
  • Workflow-multibranch:latest
  • Git:4.7.1
  • Configuration-as-code:1.51
  • Google-oauth-plugin:latest
  • Google-source-plugin:latest
  • Google-storage-plugin:latest

This will allow Jenkins to connect to your cluster and your GCP project.

  1. Download the custom values file:

gsutil cp gs://spls/gsp330/values.yaml jenkins/values.yaml
  1. Use the Helm CLI to deploy the chart with your configuration settings:

helm install cd jenkins/jenkins -f jenkins/values.yaml --wait

This command may take a couple minutes to complete.

Test completed task

Click Check my progress to verify your performed task. If you have successfully configure a Jenkins chart you will see an assessment score.

Configure and Install Jenkins
  1. Once that command completes ensure the Jenkins pod goes to the Running state and the container is in the READY state:

kubectl get pods

Example Output:

NAME READY STATUS RESTARTS AGE cd-jenkins-7c786475dd-vbhg4 1/1 Running 0 1m
  1. Configure the Jenkins service account to be able to deploy to the cluster:

kubectl create clusterrolebinding jenkins-deploy --clusterrole=cluster-admin --serviceaccount=default:cd-jenkins

You should receive the following output: created
  1. Run the following command to setup port forwarding to the Jenkins UI from the Cloud Shell:

export POD_NAME=$(kubectl get pods --namespace default -l "" -l "" -o jsonpath="{.items[0]}") kubectl port-forward $POD_NAME 8080:8080 >> /dev/null &
  1. Now, check that the Jenkins Service was created properly:

kubectl get svc

Example Output:

NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE cd-jenkins 8080/TCP 3h cd-jenkins-agent 50000/TCP 3h kubernetes 443/TCP 9h

You are using the Kubernetes Plugin so that our builder nodes will be automatically launched as necessary when the Jenkins master requests them. Upon completion of their work, they will automatically be turned down and their resources added back to the clusters resource pool.

Notice that this service exposes ports 8080 and 50000 for any pods that match the selector. This will expose the Jenkins web UI and builder/agent registration ports within the Kubernetes cluster. Additionally, the jenkins-ui services is exposed using a ClusterIP so that it is not accessible from outside the cluster.

Task 5. Connect to Jenkins

  1. The Jenkins chart will automatically create an admin password for you. To retrieve it, run:

printf $(kubectl get secret cd-jenkins -o jsonpath="{.data.jenkins-admin-password}" | base64 --decode);echo
  1. To get to the Jenkins user interface, click on the Web Preview button in Cloud Shell, then click Preview on port 8080:

Preview on port 8080 option

  1. You should now be able to log in with username admin and your auto-generated password.

You now have Jenkins set up in your Kubernetes cluster! Jenkins will drive your automated CI/CD pipelines in the next sections.

Task 6. Understanding the Application

You'll deploy the sample application, gceme, in your continuous deployment pipeline. The application is written in the Go language and is located in the repo's sample-app directory. When you run the gceme binary on a Compute Engine instance, the app displays the instance's metadata in an info card.

Backend that serviced this request page

The application mimics a microservice by supporting two operation modes.

  • In backend mode: gceme listens on port 8080 and returns Compute Engine instance metadata in JSON format.
  • In frontend mode: gceme queries the backend gceme service and renders the resulting JSON in the user interface.

gceme architecture diagram

Task 7. Deploying the Application

You will deploy the application into two different environments:

  • Production: The live site that your users access.

  • Canary: A smaller-capacity site that receives only a percentage of your user traffic. Use this environment to validate your software with live traffic before it's released to all of your users.

  1. In Google Cloud Shell, navigate to the sample application directory:

cd sample-app
  1. Create the Kubernetes namespace to logically isolate the deployment:

kubectl create ns production
  1. Create the production and canary deployments, and the services using the kubectl apply commands:

kubectl apply -f k8s/production -n production kubectl apply -f k8s/canary -n production kubectl apply -f k8s/services -n production

Test completed task

Click Check my progress to verify your performed task. If you have successfully created deployments you will see an assessment score.

Create the production and canary deployments

By default, only one replica of the frontend is deployed. Use the kubectl scale command to ensure that there are at least 4 replicas running at all times.

  1. Scale up the production environment frontends by running the following command:

kubectl scale deployment gceme-frontend-production -n production --replicas 4
  1. Now confirm that you have 5 pods running for the frontend, 4 for production traffic and 1 for canary releases (changes to the canary release will only affect 1 out of 5 (20%) of users):

kubectl get pods -n production -l app=gceme -l role=frontend
  1. Also confirm that you have 2 pods for the backend, 1 for production and 1 for canary:

kubectl get pods -n production -l app=gceme -l role=backend
  1. Retrieve the external IP for the production services:

kubectl get service gceme-frontend -n production

Example Output:

NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE gceme-frontend LoadBalancer 80/TCP 5h

Paste External IP into a browser to see the info card displayed on a card—you should get a similar page:

Backend that serviced this request

  1. Now, store the frontend service load balancer IP in an environment variable for use later:

export FRONTEND_SERVICE_IP=$(kubectl get -o jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend)
  1. Confirm that both services are working by opening the frontend external IP address in your browser.

  2. Check the version output of the service by running the following command (it should read 1.0.0):

curl http://$FRONTEND_SERVICE_IP/version

You have successfully deployed the sample application! Next, you will set up a pipeline for deploying your changes continuously and reliably.

Task 8. Creating the Jenkins Pipeline

Creating a repository to host the sample app source code

  1. Create a copy of the gceme sample app and push it to a Cloud Source Repository:

gcloud source repos create default

You can ignore the warning, you will not be billed for this repository.

Test completed task

Click Check my progress to verify your performed task. If you have successfully created a source repository you will see an assessment score.

Create a repository git init
  1. Initialize the sample-app directory as its own Git repository:

git config credential.helper
  1. Run the following command:

git remote add origin$DEVSHELL_PROJECT_ID/r/default
  1. Set the username and email address for your Git commits. Replace [EMAIL_ADDRESS] with your Git email address and [USERNAME] with your Git username:

git config --global "[EMAIL_ADDRESS]" git config --global "[USERNAME]"
  1. Add, commit, and push the files:

git add . git commit -m "Initial commit" git push origin master

Adding your service account credentials

Configure your credentials to allow Jenkins to access the code repository. Jenkins will use your cluster's service account credentials in order to download code from the Cloud Source Repositories.

Step 1: In the Jenkins user interface, click Manage Jenkins in the left navigation then click Manage Credentials.

Step 2: Click Jenkins

Credentials page

Step 3: Click Global credentials (unrestricted).

Step 4: Click Add Credentials in the left navigation.

Step 5: Select Google Service Account from metadata from the Kind drop-down and click OK.

The global credentials has been added. The name of the credential is the Project ID found in the CONNECTION DETAILS section of the lab.

Global credentials (unrestricted) page

Creating the Jenkins job

Navigate to your Jenkins user interface and follow these steps to configure a Pipeline job.

Step 1: Click Dashboard > New Item in the left panel.

Step 2: Name the project sample-app, then choose the Multibranch Pipeline option and click OK.

Step 3: On the next page, in the Branch Sources section, click Add Source and select git.

Step 4: Paste the HTTPS clone URL of your sample-app repo in Cloud Source Repositories into the Project Repository field. Replace [PROJECT_ID] with your Project ID:[PROJECT_ID]/r/default

Step 5: From the Credentials drop-down, select the name of the credentials you created when adding your service account in the previous steps.

Step 6: Under Scan Multibranch Pipeline Triggers section, check the Periodically if not otherwise run box and set the Interval value to 1 minute.

Step 7: Your job configuration should look like this:

Branch Sources section

Build Configuration section

Step 8: Click Save leaving all other options with their defaults.

After you complete these steps, a job named Branch indexing runs. This meta-job identifies the branches in your repository and ensures changes haven't occurred in existing branches. If you click sample-app in the top left, the master job should be seen.

You have successfully created a Jenkins pipeline! Next, you'll create the development environment for continuous integration.

Task 9. Creating the development environment

Development branches are a set of environments your developers use to test their code changes before submitting them for integration into the live site. These environments are scaled-down versions of your application, but need to be deployed using the same mechanisms as the live environment.

Creating a development branch

To create a development environment from a feature branch, you can push the branch to the Git server and let Jenkins deploy your environment.

  • Create a development branch and push it to the Git server:

git checkout -b new-feature

Modifying the pipeline definition

The Jenkinsfile that defines that pipeline is written using the Jenkins Pipeline Groovy syntax. Using a Jenkinsfile allows an entire build pipeline to be expressed in a single file that lives alongside your source code. Pipelines support powerful features like parallelization and require manual user approval.

In order for the pipeline to work as expected, you need to modify the Jenkinsfile to set your project ID.

  1. Open the Jenkinsfile in your terminal editor, for example vi:

vi Jenkinsfile
  1. Start the editor:

  1. Add your PROJECT_ID to the REPLACE_WITH_YOUR_PROJECT_ID value. (Your PROJECT_ID is your Project ID found in the CONNECTION DETAILS section of the lab. You can also run gcloud config get-value project to find it.

  2. Change the CLUSTER_ZONE to the default compute/zone you set at the beginning of this lab. You can get this value by running gcloud config get compute/zone.

PROJECT = "REPLACE_WITH_YOUR_PROJECT_ID" APP_NAME = "gceme" FE_SVC_NAME = "${APP_NAME}-frontend" CLUSTER = "jenkins-cd" CLUSTER_ZONE = "{{{project_0.default_zone}}}" IMAGE_TAG = "${PROJECT}/${APP_NAME}:${env.BRANCH_NAME}.${env.BUILD_NUMBER}" JENKINS_CRED = "${PROJECT}"
  1. Save the Jenkinsfile file: hit Esc then (for vi users):


Modify the site

To demonstrate changing the application, you will change the gceme cards from blue to orange.

  1. Open html.go:

vi html.go
  1. Start the editor:

  1. Change the two instances of <div class="card blue"> with following:

<div class="card orange">
  1. Save the html.go file: press Esc then:

  1. Open main.go:

vi main.go
  1. Start the editor:

  1. The version is defined in this line:
const version string = "1.0.0"

Update it to the following:

const version string = "2.0.0"
  1. Save the main.go file one more time: Esc then:


Task 10. Kick off Deployment

  1. Commit and push your changes:

git add Jenkinsfile html.go main.go git commit -m "Version 2.0.0" git push origin new-feature

This will kick off a build of your development environment.

After the change is pushed to the Git repository, navigate to the Jenkins user interface where you can see that your build started for the new-feature branch. It can take up to a minute for the changes to be picked up.

  1. After the build is running, click the down arrow next to the build in the left navigation and select Console output:

Navigation pane

  1. Track the output of the build for a few minutes and watch for the kubectl --namespace=new-feature apply... messages to begin. Your new-feature branch will now be deployed to your cluster.

If you didn't see anything in Build Executor, not to worry. Just go to the Jenkins homepage > sample app. Verify that the new-feature pipeline has been created.

  1. Once that's all taken care of, start the proxy in the background:

kubectl proxy &
  1. If it stalls, press Ctrl + C to exit out. Verify that your application is accessible by sending a request to localhost and letting kubectl proxy forward it to your service:

curl \ http://localhost:8001/api/v1/namespaces/new-feature/services/gceme-frontend:80/proxy/version

You should see it respond with 2.0.0, which is the version that is now running.

If you receive a similar error:

{ "kind": "Status", "apiVersion": "v1", "metadata": { }, "status": "Failure", "message": "no endpoints available for service \"gceme-frontend:80\"", "reason": "ServiceUnavailable", "code": 503
  1. It means your frontend endpoint hasn't propagated yet—wait a little bit and try the curl command again. Move on when you get the following output:

You have set up the development environment! Next, you will build on what you learned in the previous module by deploying a canary release to test out a new feature.

Task 11. Deploying a canary release

You have verified that your app is running the latest code in the development environment, so now deploy that code to the canary environment.

  1. Create a canary branch and push it to the Git server:

git checkout -b canary git push origin canary
  1. In Jenkins, you should see the canary pipeline has kicked off. Once complete, you can check the service URL to ensure that some of the traffic is being served by your new version. You should see about 1 in 5 requests (in no particular order) returning version 2.0.0.

export FRONTEND_SERVICE_IP=$(kubectl get -o \ jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend) while true; do curl http://$FRONTEND_SERVICE_IP/version; sleep 1; done
  1. If you keep seeing 1.0.0, try running the above commands again. Once you've verified that the above works, end the command with Ctrl + C.

That's it! You have deployed a canary release. Next you will deploy the new version to production.

Task 12. Deploying to production

Now that our canary release was successful and we haven't heard any customer complaints, deploy to the rest of your production fleet.

  1. Create a canary branch and push it to the Git server:

git checkout master git merge canary git push origin master

In Jenkins, you should see the master pipeline has kicked off.

  1. Once complete (which may take a few minutes), you can check the service URL to ensure that all of the traffic is being served by your new version, 2.0.0.

export FRONTEND_SERVICE_IP=$(kubectl get -o \ jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend) while true; do curl http://$FRONTEND_SERVICE_IP/version; sleep 1; done
  1. Once again, if you see instances of 1.0.0 try running the above commands again. You can stop this command by pressing Ctrl + C.

Example output:

gcpstaging9854_student@qwiklabs-gcp-df93aba9e6ea114a:~/continuous-deployment-on-kubernetes/sample-app$ while true; do curl http://$FRONTEND_SERVICE_IP/version; sleep 1; done 2.0.0 2.0.0 2.0.0 2.0.0 2.0.0 2.0.0 ^C

You can also navigate to site on which the gceme application displays the info cards. The card color changed from blue to orange.

  1. Here's the command again to get the external IP address so you can check it out:

kubectl get service gceme-frontend -n production

Example output:

Backend that serviced this request page

Task 13. Test your Understanding

Below are multiple-choice questions to reinforce your understanding of this lab's concepts. Answer them to the best of your abilities.

You're done!

Awesome job, you have successfully deployed your application to production!


This concludes this hands-on lab deploying and working with Jenkins in Kubernetes Engine to enable a Continuous Delivery / Continuous Deployment pipeline. You've had the opportunity to deploy a significant DevOps tool in Kubernetes Engine and configure it for production use. You've worked with the kubectl command-line tool and deployment configurations in YAML files, and have learned a bit about setting up Jenkins pipelines for a development / deployment process. With this practical hands-on experience you should feel comfortable applying these tools in your own DevOps shop.

Finish your quest

This self-paced lab is part of the Kubernetes in the Google Cloud, Cloud Architecture, and DevOps Essentials quests. A quest is a series of related labs that form a learning path. Completing a quest earns you a badge to recognize your achievement. You can make your badge or badges public and link to them in your online resume or social media account. Enroll in any quest that contains this lab and get immediate completion credit. See the Google Cloud Skills Boost catalog to see all available quests.

Take your next lab

Continue your quest with Hello Node Kubernetes, or check out these Google Cloud Skills Boost labs:

Next steps / Learn more

Google Cloud training and certification

...helps you make the most of Google Cloud technologies. Our classes include technical skills and best practices to help you get up to speed quickly and continue your learning journey. We offer fundamental to advanced level training, with on-demand, live, and virtual options to suit your busy schedule. Certifications help you validate and prove your skill and expertise in Google Cloud technologies.

Manual Last Updated August 04, 2022

Lab Last Tested August 04, 2022

Copyright 2022 Google LLC All rights reserved. Google and the Google logo are trademarks of Google LLC. All other company and product names may be trademarks of the respective companies with which they are associated.