Deploy the hawkbit helm chart on Google Kubernetes Engine (GKE)

Question

Pulumi · Accepted Answer

To deploy the Hawkbit helm chart on Google Kubernetes Engine (GKE), you'll need to go through a few steps:

1. Set up a GKE cluster.
2. Configure access to the cluster for `kubectl` and Helm.
3. Use Helm to install the Hawkbit helm chart.

Below is a TypeScript program using Pulumi to accomplish these steps. This program uses the `@pulumi/kubernetes` package to interact with Kubernetes and the `@pulumi/gcp` package to manage Google Cloud resources.

### Program Explanation

#### GKE Cluster Creation
First, we create a GKE cluster using the `gcp.container.Cluster` class. This represents a GKE cluster and requires various properties like the `initialNodeCount`.

#### Configuring Kubernetes Provider
Once the cluster is created, we need to set up the Kubernetes provider to point to the newly created GKE cluster. The `kubernetes.Provider` class is used to configure this, which requires cluster details such as the endpoint and the cluster's credentials for authentication.

#### Deploying Helm Chart
Finally, we use the `kubernetes.helm.v3.Chart` class to deploy the Hawkbit helm chart, pointing it to the necessary repository and specifying the release name.

### Pulumi Program

```typescript
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
import * as k8s from "@pulumi/kubernetes";

// Set up a GKE cluster
const cluster = new gcp.container.Cluster("hawkbit-cluster", {
    initialNodeCount: 1,
    nodeVersion: "latest",
    minMasterVersion: "latest",
});

// Export the Cluster name
export const clusterName = cluster.name;

// Export the Kubeconfig to access the GKE cluster with `kubectl`
export const kubeconfig = pulumi.
    all([cluster.name, cluster.endpoint, cluster.masterAuth]).
    apply(([name, endpoint, masterAuth]) => {
        const context = `${gcp.config.project}_${gcp.config.zone}_${name}`;
        return `apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: ${masterAuth.clusterCaCertificate}
    server: https://${endpoint}
  name: ${context}
contexts:
- context:
    cluster: ${context}
    user: ${context}
  name: ${context}
current-context: ${context}
kind: Config
preferences: {}
users:
- name: ${context}
  user:
    auth-provider:
      config:
        cmd-args: config config-helper --format=json
        cmd-path: gcloud
        expiry-key: '{.credential.token_expiry}'
        token-key: '{.credential.access_token}'
      name: gcp
`;
    });

// Set up the Kubernetes provider to use the GKE cluster credentials
const k8sProvider = new k8s.Provider("k8s-provider", {
    kubeconfig: kubeconfig,
});

// Deploy the Hawkbit helm chart using the Helm Chart class
const hawkbitChart = new k8s.helm.v3.Chart("hawkbit-chart", {
    chart: "hawkbit",
    version: "0.1.0", // Specify the chart version you want to deploy
    fetchOpts:{
        repo: "http://helm-repository-url", // Replace with the actual helm chart repository URL
    },
}, { provider: k8sProvider });

// Export the Hawkbit Helm chart status
export const hawkbitStatus = hawkbitChart.status;

```

### How to use this program

1. Ensure that you have Pulumi installed and configured to use your GCP account.
2. Save the above program to a file named `index.ts` in a new Pulumi project directory.
3. Replace the placeholder `"http://helm-repository-url"` with the actual Hawkbit helm repository URL.
4. Run `pulumi up` to deploy these resources to GCP and create your Hawkbit application via Helm.

This code will perform the tasks we've discussed when executed. Ensure you replace any placeholders with actual values corresponding to your GCP setup and Hawkbit Helm chart repository.

By running the `pulumi up` command, the Pulumi CLI communicates with the Pulumi service to plan and apply the desired state of your infrastructure. In this case, it will set up a GKE cluster and deploy the Hawkbit application using Helm.

Remember to monitor the `pulumi up` output for any errors or issues that may arise during the deployment process. If the deployment is successful, you'll see output indicating the resources that have been created, along with any exported variable values like the cluster name and the Kubeconfig needed to interact with the cluster using `kubectl`.