July 14, 2020 By Eric Jodet 6 min read

Learn how to use the new IBM Cloud DevOps Toolchain Templates to automatically set up and use Tekton pipelines to build, test, and deploy your application.

IBM® Cloud Continuous Delivery includes open toolchains that automate the building and deployment of applications. Toolchain templates include specific sets of tool integrations that support development, deployment, and operations tasks.

In this blog post, we will use the new templates to create a toolchain that will use Tekton pipeline to deploy your application to a Kubernetes cluster.

About Tekton

Tekton pipelines is an open source project that you can use to configure and run continuous integration and continuous delivery pipelines within a Kubernetes cluster. Tekton pipelines are defined in yaml files, which are typically stored in a Git repository.


Create the Toolchain

  • Go to the Toolchain creation page.
  • Select Delivery Pipeline – Tekton.
  • Select the Develop a Kubernetes app with Helm template (you may exercise other templates later):
  • Review the Toolchain’s default settings:
    • Toolchain name: You may choose a name of your choice.
    • Region: Ensure the Dallas region is selected (to benefit from IBM Managed Public Workers). Note: As of today, public workers are available only in Dallas region. If creating the Toolchain in another region, you will need to set-up and add your own Private Worker.
    • Resource Group: Keep the Default Resource Group
  • Review the Git Repo and Issue Tracking settings. Each toolchain comes with a sample app, but you can select another repo to use. Learn more about Track deployment of code changes option by reading this blog.
  • Click the Delivery Pipeline tab. These fields are displayed:
    • App name: Enter the name for your application. If you’d like, you can use the default value.
    • IBM Cloud API Key: Click on the New button next to the IBM Cloud API Key field and select OK in the resulting dialog box to create a new, unique API Key.
    • Container Registry Region: Select the region in which you want the container images to be created. The default setting is to use the same registry region and cluster region.
    • Container Registry Namespace: This namespace is your folder in the global image registry in a region, which is used to manage your set of images. Either enter or select a namespace. 
    • Cluster Region: Select the region for the target cluster. This region is the region of the Kubernetes cluster that you created at the start of the tutorial or the cluster in the shared account. 
    • Resource Group: Select the resource group for your delivery pipeline. For more information about Resource Groups, see “Best practices for organizing resources in a resource group.”
    • Cluster Name: Select the name of the Kubernetes cluster that you created at the start of the tutorial or the cluster in the shared account. 
    • Cluster Namespace: Use explicit namespaces in clusters to separate deployed resources. Use distinct namespaces to insulate deployments within the same Kubernetes cluster. You can leave this setting at its default prod value.
  • Note: The new pipeline type selector enables you to switch from “Classic” to Tekton pipeline:
  • Click Create. After a few moments, your new toolchain overview page opens:

The Tekton pipeline dashboard

  • Click on the Delivery Pipeline card to explore the Tekton pipeline dashboard:
  • See the following definitions of the options on the left-hand menu:
    • Definitions: This is where the different Tekton resources stored in repositories will be referenced (along with relevant branch/tag and path).
    • Worker: Tekton pipelines are executed by Workers. Ensure IBM Managed Worker is selected. If you intend to run your pipelines on a Private Worker and you have not added one to this toolchain yet, click here:
    • Triggers: This is where you specify what happens when a specified event occurs.
    • Environment properties: This allows you to store name value pairs for use in your pipeline.
  • More details about the various sections can be found in the documentation

Tekton resources definitions

IBM Cloud Continuous Delivery support for Tekton provides a set of Custom Resources extensions to Kubernetes to define pipelines:

  • Click the Definitions section of the pipeline. Each entry links to a repository, branch, and path hosting Tekton resources used by this pipeline:
  • Click on the simple-helm-toolchain link to open the Github repository. Switch to dual-template branch.
  • Go to the .pipeline directory and open the pipeline.yaml file to explore the various the set of tasks that compose this pipeline.
  • Explore more repositories or jump to the next step—committing your first changes.

Make, commit, and deploy a change

  • Back on the main Toolchain page, click the Orion Web IDE tile:
  • Navigate to the hello-helm project and edit app.js:
  • At line 28, modify the app’s welcome message and change the text to “IBM Cloud DevOps in action!”:
  • Click on the Git icon on the left-hand side:
  • Add a comment and commit your changes by clicking the Commit button on the right:
  • Push your changes to the Git repository:
  • Navigate back to your Toolchain and click on the Delivery Pipeline. Observe that the Pipeline has been triggered by your commit. 
  • Click on PipelineRun to view the pipeline tasks and steps execution details:
  • Explore the various steps logs.
  • Click on the deploy-to-kubernetes task, then click on the execute step.
  • Scroll down to the bottom of the log and locate the section:
  • Copy the application URL and paste it in a new tab to verify that your changes were deployed:


Congratulations! You created a Toolchain that uses Helm charts to deploy an app to a secure container in a Kubernetes cluster using a Tekton pipeline. You updated the app and pushed the updates to the Git repo. After the delivery pipeline deployed the app, you verified the update.

Going further

Add a manual trigger to your Tekton pipeline with the following steps:

  • Select the Triggers section, click the Add trigger button, and select Manual:
  • Keep the defaults and add Trigger properties:
    • Repository: The URL of the repository hosting the code to deploy.
    • Branch: The branch from which to fetch the code.
  • Save your changes:
  • Back on the PipelineRuns Dashboard, click the Run Pipeline button and trigger a manual run:
  • Observe that a new build has been triggered:

Additional resources

Report a problem or look for help

Get help fast directly from the IBM Cloud development teams by joining us on Slack.

Was this article helpful?

More from Cloud

IBM Tech Now: April 8, 2024

< 1 min read - ​Welcome IBM Tech Now, our video web series featuring the latest and greatest news and announcements in the world of technology. Make sure you subscribe to our YouTube channel to be notified every time a new IBM Tech Now video is published. IBM Tech Now: Episode 96 On this episode, we're covering the following topics: IBM Cloud Logs A collaboration with IBM watsonx.ai and Anaconda IBM offerings in the G2 Spring Reports Stay plugged in You can check out the…

The advantages and disadvantages of private cloud 

6 min read - The popularity of private cloud is growing, primarily driven by the need for greater data security. Across industries like education, retail and government, organizations are choosing private cloud settings to conduct business use cases involving workloads with sensitive information and to comply with data privacy and compliance needs. In a report from Technavio (link resides outside ibm.com), the private cloud services market size is estimated to grow at a CAGR of 26.71% between 2023 and 2028, and it is forecast to increase by…

Optimize observability with IBM Cloud Logs to help improve infrastructure and app performance

5 min read - There is a dilemma facing infrastructure and app performance—as workloads generate an expanding amount of observability data, it puts increased pressure on collection tool abilities to process it all. The resulting data stress becomes expensive to manage and makes it harder to obtain actionable insights from the data itself, making it harder to have fast, effective, and cost-efficient performance management. A recent IDC study found that 57% of large enterprises are either collecting too much or too little observability data.…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters