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README.md

☁ Deploy to Kubernetes in Google Cloud: Challenge Lab | logbook

In this article, we will go through the lab GSP318 Deploy to Kubernetes in Google Cloud: Challenge Lab, which is an expert-level exercise (formerly known as Kubernetes in Google Cloud: Challenge Lab) on Qwiklabs. You will practice the skills and knowledge for configuring Docker images and containers and deploying fully-fledged Kubernetes Engine applications.

The challenge contains 4 required tasks:

  • Create a Docker image and store the Dockerfile
  • Test the created Docker image
  • Push the Docker image in the Google Container Repository
  • Create and expose a deployment in Kubernetes
  • Increase the replicas from 1 to [Replica Count]
  • Update the deployment with a new version of valkyrie-app
  • Create a pipeline in Jenkins to deploy your app

Task 1: Create a Docker image and store the Dockerfile

Hint: Refer procedures and modify the codes in the lab GSP055 Introduction to Docker

  • First of all, you have to run the following command in Cloud Shell.
source <(gsutil cat gs://cloud-training/gsp318/marking/setup_marking_v2.sh)

It installs the marking scripts, which use to check your progress.

  • Then, run the commands below to clone the valkyrie-app source code repository to the Cloud Shell. (Remember to replace YOUR_PROJECT_ID with your Project ID)
export PROJECT=$YOUR_PROJECT_ID
gcloud source repos clone valkyrie-app --project=$PROJECT
  • Create a Dockerfile under the valkyrie-app directory and add the configuration to the file. Copy the given codes from the lab page to the following snippet, and then run the commands in the Cloud Shell.
cd valkyrie-app
cat > Dockerfile <<EOF  
FROM golang:1.10
WORKDIR /go/src/app
COPY source .
RUN go install -v
ENTRYPOINT ["app","-single=true","-port=8080"]
EOF
  • Build the image with the following command:
  • Replace [Image Name] with Image Name And [Tag name] with Tag name
docker build -t [Image Name]:[Tag name] .
  • Run docker images to look at the images you built.

Before clicking Check my progress on the lab page, don’t forget to run the following commands to execute the marking script:

cd ~/marking
./step1_v2.sh

Task 2: Test the created Docker image

Hint: Refer procedures and modify the codes in the lab GSP055 Introduction to Docker

The lab instruction requires you to run the docker image built in Task 1 and show the running application by Web Preview on port 8080. Based on the requirements, the docker command will be:

  • In the Cloud Shell, go back to the valkyrie-app directory, and run the below command.
  • Replace [Image Name] with Image Name and [Image with tag] with Image with tag
docker run -p 8080:8080 --name [Image name] [Image with tag] &
  • Click Web Preview to see the running app.
  • After that, open a new Cloud Shell to run the step2_v2.sh marking script.
cd ~/marking
./step2_v2.sh

Task 3: Push the Docker image in the Container Repository

Hint: Refer procedures and modify the codes in the lab GSP055 Introduction to Docker

In this task, you will push the Docker image valkyrie-app:v0.0.1 into the Container Registry with a tag gcr.io/YOUR_PROJECT_ID/valkyrie-app:v0.0.1.

Thus, you should format the docker commands as below.

Replace [Image with tag] with Image with tag

docker tag [Image with tag] gcr.io/$PROJECT/[Image with tag]
docker images
docker push gcr.io/$PROJECT/[Image with Tag]

After pushing the container, the [Image name] repository will appear in the Cloud Console as shown in the image below.

Push the Docker image of valkyrie-app in the Google Container Repository

Task 4: Create and expose a deployment in Kubernetes

Hint: Refer procedures in the labs GSP100 Kubernetes Engine: Qwik Start and GSP021 Orchestrating the Cloud with Kubernetes for steps 1-2 and steps 3-4, respectively.

  • In the Cloud Shell, go to the valkyrie-app subdirectory.
cd valkyrie-app
  • Get authentication credentials for the cluster
gcloud container clusters get-credentials valkyrie-dev --region us-east1-d
  • Use a text editor to modify deployment.yaml and replace IMAGE_HERE with gcr.io/YOUR_PROJECT_ID/valkyrie-dev:[Tag name] at line no 20 and 35
gcloud container clusters get-credentials valkyrie-dev --zone us-east1-d
kubectl create -f k8s/deployment.yaml
kubectl create -f k8s/service.yaml

Task 5: Update the deployment with a new version of valkyrie-app

Hint: Refer the skills in lab GSP053 Managing Deployments Using Kubernetes Engine or my previous article Qwiklabs/Logbook: Scale Out and Update a Containerized Application on a Kubernetes Cluster

  • Replace [Replicas count] with Replicas count
kubectl scale deployment valkyrie-dev --replicas [Replicas count]
  • Go back to the valkyrie-app directory in the Cloud Shell.
  • Merge the branch called kurt-dev into master using the following git command:
git merge origin/kurt-dev
  • Build and push the new version with tagged [Updated Version]:

Replace [Updated Version] with Updated Version, [Image Name] with [Image Name] and [PROJECT_ID] with PROJECT_ID

docker build -t valkyrie-app:[Updated Version] .
docker tag valkyrie-app:[Updated Version] gcr.io/PROJECT_ID/[Image Name]:[Updated Version]
docker images
docker push gcr.io/PROJECT_ID/[Image Name]:[Updated Version]
  • Trigger a rolling update by running the following command:

Replace [Updated Version] with Updated Version, [Image Name] with [Image Name] and [PROJECT_ID] with PROJECT_ID

kubectl set image deployment valkyrie-dev backend=gcr.io/PROJECT_ID/[Image Name]:[Updated Version] frontend=gcr.io/PROJECT_ID/[Image Name]:[Updated Version]

Task 6: Create a pipeline in Jenkins to deploy your app

Hint: Refer procedures in the labs GSP051 Continuous Delivery with Jenkins in Kubernetes Engine

In this task, you will need to:

  • Connect to Jenkins
  • Adding your service account credentials
  • Creating a Jenkins job
  • Modifying the pipeline definition
  • Modify the site
  • Kick off Deployment
  • Get the password with the following command:
printf $(kubectl get secret cd-jenkins -o jsonpath="{.data.jenkins-admin-password}" | base64 --decode);echo
  • If there is another running container, use the docker commands below to kill it:
docker ps
docker container kill $(docker ps -aq)
  • Connect to the Jenkins console using the commands below:
export POD_NAME=$(kubectl get pods --namespace default -l "app.kubernetes.io/component=jenkins-master" -l "app.kubernetes.io/instance=cd" -o jsonpath="{.items[0].metadata.name}")
kubectl port-forward $POD_NAME 8080:8080 >> /dev/null &
  • Click on the Web Preview button in cloud shell, then click “Preview on port 8080” to connect to the Jenkins console.
  • Username: admin
  • In the Jenkins user interface, click Credentials in the left navigation.
  • Click Jenkins
  • Click Global credentials (unrestricted).
  • Click Add Credentials in the left navigation.
  • Select Google Service Account from metadata from the Kind drop-down and click OK.
  • Create a pipeline job that points to your */master branch on your source code.
  • Click Jenkins > New Item in the left navigation:
  • Name the project valkyrie-app, then choose the Pipeline option and click OK.
  • On the next page, in the Pipeline section, click Pipeline script from SCM and select git in SCM .
  • Paste the HTTPS clone URL of your sample-app repo in Cloud Source Repositories
https://source.developers.google.com/p/YOUR_PROJECT_ID/r/valkyrie-app

into the Project Repository field.

  • Remember to replace YOUR_PROJECT_ID with your GCP Project ID.
  • From the Credentials drop-down, select the name of the credentials you created when adding your service account in the previous steps.
  • Open Jenkinsfile file in a text editor, and replace YOUR_PROJECT with your GCP project ID.
  • Open source/html.go file in a text editor, and change the color of headings from green to orange at line 37 and 81.
  • Commit and push the changes:
git config --global user.email "[email protected]"
git config --global user.name "student"
git add *
git commit -m 'green to orange'
git push origin master

Finally, manually trigger the build in the Jenkins console

Congratulations! You completed this challenge lab.

Stay tuned till the next blog

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