Create a release pipeline and deploy to local Kubernetes cluster with Azure Devops

On a previous article I described how you could create your self hosted agent to run your pipelines on Azure Devops. In this article I will explain how you can use this agent to deploy resources on your local Kubernetes cluster. As a prerequisite you should already have a kubernetes cluster locally. You can do that by installing Docker and enable the option for a kube cluster.

First things first you should connect your local Kubernetes cluster with Azure devops. For that reason you should go on Project settings -> Service connections and select Kubernetes

You can select between three different options. I selected kubeconfig

Get the output of the below command and paste it on the box. Then select untrusted certificates and add press verify and save.

kubectl config view --raw

Then you should go and create a release pipeline. Go on releases tab and press create release.

In the setup of the release pipeline you can change the trigger from automatic to manual. You should select your build pipeline that will trigger the release. In my case I selected the one I created on a previous article.

On the tasks of the release pipeline you should select the agent pool, as a result your self hosted agent. Depending on which pool you placed your agent you should add it appropriately. In my case it was on the default pool.

Then you can go and create the tasks of the release.

I chose two tasks, one for a deployment creation through kubectl commands and another one for a service exposure. You could also apply a .yml config file.

In this deployment I selected a sample image I created on a previous article, selected the namespace, added the requested parameters and selected create as the command. KubernetesConnection is the service connection that you will create and add on the first steps.

When you run the release pipeline you should see that the self hosted agent will be prepared for the run.

The job will start on your locally deployed agent.

The stages will start running.

Taken into account that everything is correct with your commands and configuration the job will be successful.

The green button of result indicate the win of your try.

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