pulumi-kubernetes 1.0.1a1567015168

A Pulumi package for creating and managing Kubernetes resources.

Pulumi Kubernetes Resource Provider

The Kubernetes resource provider for Pulumi lets you create, deploy, and manage Kubernetes API resources and workloads in a running cluster.

• Introduction
  • Kubernetes API Version Support
  • How does API support for Kubernetes work?
• References
• Prerequisites
• Installing
• Quick Examples
  • Deploying a YAML Manifest
  • Deploying a Helm Chart
  • Deploying a Workload using the Resource API
• Contributing
• Code of Conduct

Introduction

pulumi-kubernetes provides an SDK to create any of the API resources available in Kubernetes.

This includes the resources you know and love, such as:

• Deployments
• ReplicaSets
• ConfigMaps
• Secrets
• Jobs etc.

Kubernetes API Version Support

The pulumi-kubernetes SDK closely tracks the latest upstream release, and provides access to the full API surface, including deprecated endpoints. The SDK API is 100% compatible with the Kubernetes API, and is schematically identical to what Kubernetes users expect.

At a minimum, we support the current Kubernetes version and the previous two versions. Older versions will likely work as well, but are not officially supported.

See the CHANGELOG for details on supported versions of Kubernetes for each version of the pulumi-kubernetes package.

How does API support for Kubernetes work?

Pulumi’s Kubernetes SDK is manufactured by automatically wrapping our library functionality around the Kubernetes resource OpenAPI spec as soon as a new version is released! Ultimately, this means that Pulumi users do not have to learn a new Kubernetes API model, nor wait long to work with the latest available versions.

Note: Pulumi also supports alpha and beta APIs.

Visit the FAQ for more details.

References

• Reference Documentation
• API Documentation
  • Node.js API
  • Python API
• All Examples
• Tutorials

Prerequisites

See the quickstart for complete documentation.

1. Install Pulumi
2. Install a language runtime such as Node.js or Python.
3. Install a package manager
   • For Node.js, use NPM or Yarn.
   • For Python, use pip.
4. Have access to a running Kubernetes cluster
   • If kubectl already works for your running cluster, Pulumi respects and uses this configuration.
   • If you do not have a cluster already running and available, we encourage you to explore Pulumi's SDKs for AWS EKS, Azure AKS, and GCP GKE. Visit the reference docs for more details.
5. Install kubectl.

Installing

This package is available in JavaScript/TypeScript for use with Node.js, as well as in Python.

For Node.js use either npm or yarn:

npm:

npm install @pulumi/kubernetes

yarn:

yarn add @pulumi/kubernetes

For Python use pip:

pip install pulumi-kubernetes

Quick Examples

The following examples demonstrate how to work with pulumi-kubernetes in a couple of ways.

Examples may include the creation of an AWS EKS cluster, although an EKS cluster is not required to use pulumi/kubernetes. It is simply used to ensure we have access to a running Kubernetes cluster to deploy resources and workloads into.

Deploying a YAML Manifest

This example deploys resources from a YAML manifest file path, using the transient, default kubeconfig credentials on the local machine, just as kubectl does.

Note: This capabality is primarily targeted for experimentation and transitioning to Pulumi. Pulumi's desired state model greatly benefits from having resources be directly defined in your Pulumi program as demonstrated in the workload example.

import * as k8s as "@pulumi/kubernetes";

const myApp = new k8s.yaml.ConfigFile("app", {
    file: "app.yaml"
});

Deploying a Helm Chart

This example creates an EKS cluster with pulumi/eks, and then deploys a Helm chart from the stable repo using the kubeconfig credentials from the cluster's Pulumi provider.

Note: This capabality is primarily targeted for experimentation and transitioning to Pulumi. Pulumi's desired state model greatly benefits from having resources be directly defined in your Pulumi program as demonstrated in the workload example.

import * as eks from "@pulumi/eks";
import * as k8s from "@pulumi/kubernetes";

// Create an EKS cluster.
const cluster = new eks.Cluster("my-cluster");

// Deploy Wordpress into our cluster.
const wordpress = new k8s.helm.v2.Chart("wordpress", {
    repo: "stable",
    chart: "wordpress",
    values: {
        wordpressBlogName: "My Cool Kubernetes Blog!",
    },
}, { providers: { "kubernetes": cluster.provider } });

// Export the cluster's kubeconfig.
export const kubeconfig = cluster.kubeconfig;

Deploying a Workload using the Resource API

This example creates a EKS cluster with pulumi/eks, and then deploys an NGINX Deployment and Service using the SDK resource API, and the kubeconfig credentials from the cluster's Pulumi provider.

import * as eks from "@pulumi/eks";
import * as k8s from "@pulumi/kubernetes";

// Create an EKS cluster with the default configuration.
const cluster = new eks.Cluster("my-cluster");

// Create a NGINX Deployment and Service.
const appName = "my-app";
const appLabels = { appClass: appName };
const deployment = new k8s.apps.v1.Deployment(`${appName}-dep`, {
    metadata: { labels: appLabels },
    spec: {
        replicas: 2,
        selector: { matchLabels: appLabels },
        template: {
            metadata: { labels: appLabels },
            spec: {
                containers: [{
                    name: appName,
                    image: "nginx",
                    ports: [{ name: "http", containerPort: 80 }]
                }],
            }
        }
    },
}, { provider: cluster.provider });

const service = new k8s.core.v1.Service(`${appName}-svc`, {
    metadata: { labels: appLabels },
    spec: {
        type: "LoadBalancer",
        ports: [{ port: 80, targetPort: "http" }],
        selector: appLabels,
    },
}, { provider: cluster.provider });

// Export the URL for the load balanced service.
export const url = service.status.loadBalancer.ingress[0].hostname;

// Export the cluster's kubeconfig.
export const kubeconfig = cluster.kubeconfig;

Contributing

If you are interested in contributing, please see the contributing docs.

Code of Conduct

You can read the code of conduct here.