Configure PetClinic Development Deployment to Meet your Organization's Requirements¹¶

Manage resource across environments with Kustomize¶

Kustomize is a tool for customizing Kubernetes resource configuration.

From the documentation overview

Kustomize traverses a Kubernetes manifest to add, remove or update configuration options without forking. It is available both as a standalone binary and as a native feature of kubectl. See the Introducing Kustomize Kubernetes Blog Post for a more in-depth overview of Kustomize and its purpose.

As part of doing things the "cloud native" way you will be using Kustomize to manage resource changes across your dev and staging environments as well as injecting information from your pipeline (such as newly created container image information with git commits) into your Kubernetes (OpenShift) resources.

To see how you use Kustomize, see the Kustomize configuration in your GitHub code in the subdirectories of the ocp-files directory.

For more information on how kubectl (and oc through kubectl) integrates Kustomize, see the kubectl documentation.

Creating Custom Task for Kustomize¶

Since there is no ClusterTask defined for Kustomize, you will create a custom task for this purpose. It will change into the Kustomize directory, run a Kustomize command on the directory, and then apply the files from the directory using the built-in Kustomize functionality of the oc command line tool (via kubectl's Kustomize support)

Copy the kustomize task using the following definition (copy by clicking on the copy icon in the top right of the box below):

apiVersion: tekton.dev/v1beta1
kind: Task
metadata:
  name: kustomize
spec:
  description: >-
    This task runs commands against the cluster where the task run is being
    executed.

    Kustomize is a tool for Kubernetes native configuration management.  It
    introduces a template-free way to customize application configuration that
    simplifies the use of off-the-shelf applications.  Now, built into kubectl
    as apply -k and oc as oc apply -k.
  params:
  - default: ocp-files
    description: The directory where the kustomization yaml file(s) reside in the git directory
    name: KUSTOMIZE_DIR
    type: string
  - default: base
    description: subdirectory of KUSTOMIZE_DIR used for extra configuration of current resources
    name: EDIT_SUDBDIR
    type: string
  - default: overlay/dev
    description: subdirectory of KUSTOMIZE_DIR used for specifying resources for a specific release such as dev or staging
    name: RELEASE_SUBDIR
    type: string
  - default: kustomize --help
    description: The Kustomize CLI command to run
    name: SCRIPT
    type: string
  steps:
  - image: 'quay.io/gmoney23/kustomize-s390x:v4.1.2'
    name: kustomize
    resources:
      limits:
        cpu: 200m
        memory: 200Mi
      requests:
        cpu: 200m
        memory: 200Mi
    workingDir: "$(workspaces.source.path)/$(params.KUSTOMIZE_DIR)/$(params.EDIT_SUDBDIR)"
    script: $(params.SCRIPT)
  - image: 'image-registry.openshift-image-registry.svc:5000/openshift/cli:latest'
    name: apply-oc-files
    resources:
      limits:
        cpu: 200m
        memory: 200Mi
      requests:
        cpu: 200m
        memory: 200Mi
    script: oc apply -k "$(workspaces.source.path)/$(params.KUSTOMIZE_DIR)/$(params.RELEASE_SUBDIR)"
  workspaces:
  - name: source
    description: The git source code

Create the kustomize Task

a. Click Import YAML to bring up the box where you can create Kubernetes resource definitions from yaml

b. Paste the kustomize Task into the box

c. Scroll down and click Create to create the kustomize Task

You should now see the created kustomize Task.

Back to Pipelines

Finally, navigate back to the Pipelines section of the OpenShift UI and go back to editing your pipeline.

Add Kustomize Task to Pipeline¶

Add a sequential task after clean-image and when you Select Task choose the kustomize task.
Configure kustomize task

Since your initial deploy will be for the dev environment, the only values you need to change are the Display Name and the SCRIPT (copy and paste boxes below image):
Display Name
```
kustomize-dev
```
SCRIPT
```
kustomize edit set image spring-petclinic=$(params.IMAGE_NAME)-minimal:$(params.COMMIT_SHA)
```
SOURCE (choose from dropdown)
```
workspace
```
Save the pipeline

Clean Old PetClinic Instances at the Beginning of a Run¶

Go back to editing your pipeline via Actions -> Edit Pipeline
Add a Task named cleanup-resources sequentially at the beginning of the pipeline before fetch-repository (using the openshift-client ClusterTask).
Configure the task with the following parameters (copy and paste boxes below image for changes):
Display Name
```
cleanup-resources
```
SCRIPT
```
oc delete deployment,cm,svc,route -l app=$(params.APP_NAME) --ignore-not-found
```
and an empty ARGS value.

No help please!

Make sure help is deleted from the ARGS section (click the - button to delete the default help args line).

Update Deploy Task to deploy-dev¶

Click on the deploy Task at the end of the pipeline and change the following parameters to the corresponding values (copy and paste boxes below image):
Display Name
```
deploy-dev
```
SCRIPT
```
echo "$(params.GIT_MESSAGE)" && oc $@
```
New Last Arg
```
deploy/spring-petclinic-dev
```
Save your pipeline!

Run the Updated Pipeline¶

Go to Actions -> Start in the right hand corner of the pipeline menu
Manually trigger a PipelineRun by accepting the default values and clicking on Start.

Persistent Volume Claim Note

Please select a PersistentVolumeClaim if it is not already filled out for you to complete your pipeline. If it is already filled out for you then jump right to starting the pipeline.
Watch the results of your build pipeline run. It should complete successfully as in the pictures below.

How long will your pipeline take to run?

The pipeline run may take anywhere from 10-25 minutes to complete depending on the current system load. You can see the progress of your build, as well as if any errors occur, via the UI. Thus, by monitoring the UI, you can make sure things are going as planned.

Pipeline Run Success View Perspective:

Pipeline Run Details View

In the pipeline run Details view, you can see the pipeline run succeeded with all tasks having a green check mark. Additionally, the pipeline run in the above screenshot was Triggered By a user versus an automated source such as an event listener watching for a GitHub push...

Pipeline Run Success Logs Perspective:

Pipeline Run Logs View

From the pipeline run Logs view you can see that the pipeline run tasks all have green check marks and that this was a manual build (from the message in the log output of the final [deploy-dev] task).

Summary ¶

Congratulations! You successfully deployed your PetClinic application to your development environment with automated checks and configuration to meet your needs. This means that whenever your pipeline is triggered it will automatically spin up resources to build, test and deploy your application according to the specification you need to meet for your organization¹.

For the purposes of this lab, you are fulfilling the requirements of a fictional organization. These requirements could change for your specific organization but would follow a similar pattern with different specifics. ↩↩

Last update: July 7, 2023
Created: May 20, 2021

Configure PetClinic Development Deployment to Meet your Organization's Requirements1¶