How do I store backend state in S3 using Automation API in Python?

Using the Pulumi Automation API with Python, you can set up backend state storage in an S3 bucket. This solution involves configuring the required settings in your Pulumi.yaml and Pulumi.{stack}.yaml files to point to your S3 bucket. Here is an example of how to do this.

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

// Resource to create an S3 bucket
const pulumiState = new aws.s3.BucketV2("pulumi_state", {
    bucket: "my-pulumi-state-storage",
    acl: "private",
    tags: {
        Name: "PulumiStateStorage",
        Environment: "Dev",
    },
});
// Example resource, such as an EC2 instance (for context)
const example = new aws.ec2.Instance("example", {
    ami: "ami-0c55b159cbfafe1f0",
    instanceType: aws.ec2.InstanceType.T2_Micro,
    tags: {
        Name: "PulumiExampleInstance",
    },
});
export const bucketName = pulumiState.bucket;
export const instanceId = example.id;

In this example, we first set up the AWS provider’s region. Then, we define an S3 bucket resource to store the state files. We also have an example AWS EC2 instance resource for context. The backend storage configuration at the end directs Pulumi to store the state in the specified S3 bucket. The output section outputs the bucket’s name and the EC2 instance ID.

By the end of this guide, you have learned how to configure backend state storage using an S3 bucket and understand how to set up your Pulumi project to utilize this S3 bucket for state management!