How Do I Provision an AWS S3 Bucket Lifecycle Configuration?

Introduction

Managing the lifecycle of objects in an AWS S3 bucket is crucial for optimizing storage costs and ensuring efficient data management. By configuring lifecycle rules, you can automate the transition of objects to different storage classes, archive them, or delete them after a specified period. This guide will walk you through the process of setting up an S3 bucket and applying a lifecycle configuration to manage your data effectively.

Step-by-Step Process

1. Create an S3 Bucket: Begin by creating an S3 bucket where your objects will be stored. Ensure that the bucket has a unique name and appropriate access permissions.

2. Define Lifecycle Rules: Set up lifecycle rules for the bucket to manage the transition and expiration of objects. In this example, we will:

   • Transition objects to the Standard-IA storage class 30 days after creation.
   • Further transition objects to the Glacier storage class 90 days after creation.
   • Set objects to expire and be deleted 365 days after creation.

3. Implement the Configuration: Use Pulumi and AWS SDKs to implement the configuration in TypeScript. This involves defining the bucket and lifecycle rules in your code.

4. Export Outputs: Finally, export the bucket name and lifecycle rule ID for reference and verification.

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

// Create an S3 bucket
const myBucket = new aws.s3.BucketV2("my_bucket", {
    bucket: "my-unique-bucket-name",
    acl: "private",
});
// Set up a lifecycle rule for the bucket
const myBucketLifecycle = new aws.s3.BucketLifecycleConfigurationV2("my_bucket_lifecycle", {
    bucket: myBucket.bucket,
    rules: [{
        id: "transition_rule",
        prefix: "",
        status: "Enabled",
        transitions: [
            {
                days: 30,
                storageClass: "STANDARD_IA",
            },
            {
                days: 90,
                storageClass: "GLACIER",
            },
        ],
        expiration: {
            days: 365,
        },
    }],
});
export const bucketName = myBucket.bucket;
export const lifecycleRuleId = myBucketLifecycle.rules.apply(rules => rules[0].id);

Key Points

• Transition to Standard-IA: Objects are moved to the Standard-IA storage class after 30 days, reducing costs for infrequently accessed data.
• Transition to Glacier: After 90 days, objects are archived in the Glacier storage class, which is cost-effective for long-term storage.
• Expiration and Deletion: Objects are automatically deleted after 365 days, freeing up storage space and further optimizing costs.

Conclusion

By configuring lifecycle rules for your AWS S3 bucket, you can automate the management of your data storage, ensuring that objects are transitioned and deleted according to your specified policies. This not only optimizes storage costs but also streamlines data management processes. The example provided demonstrates how to set up these rules using Pulumi and AWS SDKs, offering a practical approach to lifecycle management in AWS S3.