How do I deploy Jupyter Notebooks on Kubernetes using Pulumi?

In this guide, we will deploy Jupyter Notebooks on Kubernetes. Jupyter Notebooks are great tools for data scientists to develop and document code, and Kubernetes helps in managing containerized applications. This setup will use a Deployment and a Service to manage the Jupyter Notebook instances.

Step-by-step Explanation

Define the Kubernetes Provider: Establish a connection with the Kubernetes cluster.
Create a Namespace: Create a namespace to logically group resources.
Configure the Deployment: Use a Deployment resource to manage the Jupyter Notebook containers.
Set Up the Service: Make the Jupyter Notebooks accessible within the cluster and, optionally, expose them outside the cluster.
Export the URLs for Access: Provide access information to the Jupyter Notebooks.

Let’s take a look at the code:

import * as pulumi from "@pulumi/pulumi";
import * as kubernetes from "@pulumi/kubernetes";

const jupyter_ns = new kubernetes.core.v1.Namespace("jupyter-ns", {metadata: {
    name: "jupyter",
}});
const jupyter_deployment = new kubernetes.apps.v1.Deployment("jupyter-deployment", {
    metadata: {
        name: "jupyter-notebook",
        namespace: jupyter_ns.metadata.apply(metadata => metadata.name),
    },
    spec: {
        replicas: 1,
        selector: {
            matchLabels: {
                app: "jupyter",
            },
        },
        template: {
            metadata: {
                labels: {
                    app: "jupyter",
                },
            },
            spec: {
                containers: [{
                    name: "jupyter",
                    image: "jupyter/base-notebook:latest",
                    ports: [{
                        containerPort: 8888,
                    }],
                    env: [{
                        name: "JUPYTER_TOKEN",
                        value: "secret-token",
                    }],
                }],
            },
        },
    },
});
const jupyter_service = new kubernetes.core.v1.Service("jupyter-service", {
    metadata: {
        name: "jupyter-service",
        namespace: jupyter_ns.metadata.apply(metadata => metadata.name),
    },
    spec: {
        selector: {
            app: "jupyter",
        },
        ports: [{
            port: 80,
            targetPort: 8888,
        }],
        type: kubernetes.core.v1.ServiceSpecType.ClusterIP,
    },
});
export const jupyterNotebookUrl = jupyter_service.metadata.apply(metadata => metadata.name);

Summary

In this example, we set up a Kubernetes environment to host Jupyter Notebooks. We defined a namespace to isolate our resources, created a deployment to manage the Jupyter containers, and set up a service to expose the notebooks within the cluster. The code also exports the service URL for accessing the Jupyter Notebook. This setup is ideal for data scientists looking to leverage the power of Kubernetes for scalable and efficient notebook management.

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