Deploy the python-webapp helm chart on Google Kubernetes Engine (GKE)

Question

Pulumi · Accepted Answer

To deploy a Python web application using a Helm chart on Google Kubernetes Engine (GKE), you will need to follow several steps. First, you’ll need to create a GKE cluster where the application will run. After the cluster is ready, you will deploy the Helm chart to the cluster. Helm charts are packages that contain all necessary resources and configuration to deploy an application to a Kubernetes cluster.

Below is a Pulumi program written in TypeScript that creates a GKE cluster and deploys a Helm chart representing a Python web application. This program uses `@pulumi/gcp` to create the cluster and `@pulumi/kubernetes` to deploy the Helm chart.

Before you run this program, ensure that you’ve installed the required Pulumi packages and configured access to your GCP account through the `gcloud` tool or by setting the appropriate environment variables.

This program follows these steps:
1. It sets up the GKE cluster by creating a new instance of `gcp.container.Cluster`.
2. It initializes the `kubernetes` provider with the kubeconfig from the created GKE cluster.
3. It uses the `kubernetes.helm.v3.Chart` resource to deploy the Helm chart.

Here is how you can do it:

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

// Create a GKE cluster
const cluster = new gcp.container.Cluster('python-gke-cluster', {
    initialNodeCount: 1,
    nodeConfig: {
        preemptible: true,
        machineType: 'n1-standard-1',
    },
});

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

// Export the Kubeconfig
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
`;
    });

// Create a Kubernetes provider instance that uses our cluster from above.
const clusterProvider = new k8s.Provider('gkeK8s', {
    kubeconfig: kubeconfig,
});

// Now, create a Helm Chart for the Python web application
const pythonAppChart = new k8s.helm.v3.Chart('python-webapp-chart', {
    chart: 'python-webapp', // The name of the chart
    version: '1.0.0', // The version of the chart
    fetchOpts: {
        repo: 'http://example.com/helm-charts', // The Helm repository URL where your chart is located
    },
}, { provider: clusterProvider });

// Export the web application's service IP
export const pythonAppServiceIP = pythonAppChart.getResourceProperty(
    'v1/Service', 'python-webapp-chart', 'status', 'loadBalancer', 'ingress', 0, 'ip',
);

```

To deploy your application:
1. Save this code to a file named `index.ts`.
2. Run `pulumi up` to execute the code and create the resources.

Remember, the above code assumes that the Helm chart named `python-webapp` is hosted in a repository at `http://example.com/helm-charts`. You should replace this URL with the actual URL of your Helm chart repository.

The `kubeconfig` output from this program will allow you to use `kubectl` to interact with your GKE cluster. The IP address of the Python web application service is also exported, which you can use to check the deployed application.

Always ensure that your Helm chart and its values (if any) are configured correctly for your application's needs.