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


    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:

    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.