How to update your application's S3 endpoint for Quake AI

After migrating your data, update your application code to read and write from Quake AI instead of the previous provider. Because Quake AI is S3-compatible, this is typically a configuration change, not a code rewrite.

What changes#

Setting	Old value (AWS example)	New value (Quake AI)
Endpoint URL	`https://s3.amazonaws.com` (or omitted)	`https://object.us-east-2.rumble.cloud`
Access key	Your AWS access key	Your Quake AI access key
Secret key	Your AWS secret key	Your Quake AI secret key
Region	Varies (`us-east-1`, `eu-west-1`, etc.)	`us-east-1` (required for SigV4 compatibility)
Path style	Virtual-hosted (default on AWS)	Path style recommended

Environment variables#

Many S3 SDKs read credentials and endpoint from environment variables. Set these and your application may require zero code changes:

bash

export AWS_ACCESS_KEY_ID="YOUR_RUMBLE_ACCESS_KEY"
export AWS_SECRET_ACCESS_KEY="YOUR_RUMBLE_SECRET_KEY"
export AWS_ENDPOINT_URL="https://object.us-east-2.rumble.cloud"
export AWS_DEFAULT_REGION="us-east-1"

AWS_ENDPOINT_URL is supported by the AWS CLI (v2.13+), boto3 (v1.29+), and the AWS SDK for JavaScript v3. Other SDKs may require explicit configuration in code.

SDK examples#

Python (boto3)#

Python

import boto3

s3 = boto3.client(
    "s3",
    endpoint_url="https://object.us-east-2.rumble.cloud",
    aws_access_key_id="YOUR_RUMBLE_ACCESS_KEY",
    aws_secret_access_key="YOUR_RUMBLE_SECRET_KEY",
    region_name="us-east-1",
)

response = s3.list_buckets()
for bucket in response["Buckets"]:
    print(bucket["Name"])

For boto3 resource interface:

Python

s3 = boto3.resource(
    "s3",
    endpoint_url="https://object.us-east-2.rumble.cloud",
    aws_access_key_id="YOUR_RUMBLE_ACCESS_KEY",
    aws_secret_access_key="YOUR_RUMBLE_SECRET_KEY",
    region_name="us-east-1",
)

for bucket in s3.buckets.all():
    print(bucket.name)

Node.js (AWS SDK v3)#

JavaScript

import { S3Client, ListBucketsCommand } from "@aws-sdk/client-s3";

const client = new S3Client({
  endpoint: "https://object.us-east-2.rumble.cloud",
  region: "us-east-1",
  credentials: {
    accessKeyId: "YOUR_RUMBLE_ACCESS_KEY",
    secretAccessKey: "YOUR_RUMBLE_SECRET_KEY",
  },
  forcePathStyle: true,
});

const response = await client.send(new ListBucketsCommand({}));
console.log(response.Buckets);

Go (AWS SDK v2)#

package main

import (
	"context"
	"fmt"
	"log"

	"github.com/aws/aws-sdk-go-v2/aws"
	"github.com/aws/aws-sdk-go-v2/config"
	"github.com/aws/aws-sdk-go-v2/credentials"
	"github.com/aws/aws-sdk-go-v2/service/s3"
)

func main() {
	cfg, err := config.LoadDefaultConfig(context.TODO(),
		config.WithRegion("us-east-1"),
		config.WithCredentialsProvider(credentials.NewStaticCredentialsProvider(
			"YOUR_RUMBLE_ACCESS_KEY",
			"YOUR_RUMBLE_SECRET_KEY",
			"",
		)),
	)
	if err != nil {
		log.Fatal(err)
	}

	client := s3.NewFromConfig(cfg, func(o *s3.Options) {
		o.BaseEndpoint = aws.String("https://object.us-east-2.rumble.cloud")
		o.UsePathStyle = true
	})

	result, err := client.ListBuckets(context.TODO(), &s3.ListBucketsInput{})
	if err != nil {
		log.Fatal(err)
	}

	for _, bucket := range result.Buckets {
		fmt.Println(*bucket.Name)
	}
}

Java (AWS SDK v2)#

java

import software.amazon.awssdk.auth.credentials.AwsBasicCredentials;
import software.amazon.awssdk.auth.credentials.StaticCredentialsProvider;
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.s3.S3Client;
import software.amazon.awssdk.services.s3.S3Configuration;

import java.net.URI;

S3Client s3 = S3Client.builder()
    .endpointOverride(URI.create("https://object.us-east-2.rumble.cloud"))
    .region(Region.US_EAST_1)
    .credentialsProvider(StaticCredentialsProvider.create(
        AwsBasicCredentials.create("YOUR_RUMBLE_ACCESS_KEY", "YOUR_RUMBLE_SECRET_KEY")))
    .serviceConfiguration(S3Configuration.builder()
        .pathStyleAccessEnabled(true)
        .build())
    .build();

s3.listBuckets().buckets().forEach(bucket ->
    System.out.println(bucket.name()));

Terraform (S3 backend)#

For storing Terraform/OpenTofu state on Quake AI:

HCL

terraform {
  backend "s3" {
    bucket                      = "my-tf-state"
    key                         = "terraform.tfstate"
    region                      = "us-east-1"
    endpoint                    = "https://object.us-east-2.rumble.cloud"
    access_key                  = "YOUR_RUMBLE_ACCESS_KEY"
    secret_key                  = "YOUR_RUMBLE_SECRET_KEY"
    skip_credentials_validation = true
    skip_metadata_api_check     = true
    skip_region_validation      = true
    force_path_style            = true
  }
}

Feature audit before switching#

Before changing your application's endpoint, verify that your code does not depend on S3 features unavailable on Quake AI:

Check for	How to find it	What to do
Lifecycle policy dependency	Search for `put_bucket_lifecycle_configuration` or `PutBucketLifecycleConfiguration`	Implement retention with external cron jobs
Event notification dependency	Search for `put_bucket_notification_configuration`, SNS ARNs, SQS ARNs, Lambda ARNs	Replace with application-level polling
Bucket policy dependency	Search for `put_bucket_policy` or JSON policy documents	Translate to Swift ACLs
S3 Select usage	Search for `select_object_content`	Download and query locally
Presigned URL generation	Search for `generate_presigned_url` or `getSignedUrl`	Presigned URLs are supported; no changes needed

Gradual cutover with dual-write#

For zero-downtime migration, write to both providers during the transition:

Python

import boto3

old_s3 = boto3.client("s3", region_name="us-east-1")
new_s3 = boto3.client(
    "s3",
    endpoint_url="https://object.us-east-2.rumble.cloud",
    aws_access_key_id="YOUR_RUMBLE_ACCESS_KEY",
    aws_secret_access_key="YOUR_RUMBLE_SECRET_KEY",
    region_name="us-east-1",
)

def upload(bucket, key, body):
    new_s3.put_object(Bucket=bucket, Key=key, Body=body)
    old_s3.put_object(Bucket=bucket, Key=key, Body=body)

def download(bucket, key):
    try:
        return new_s3.get_object(Bucket=bucket, Key=key)["Body"].read()
    except Exception:
        return old_s3.get_object(Bucket=bucket, Key=key)["Body"].read()

Once you confirm the Quake AI endpoint is stable, remove the old provider calls and the fallback logic.

How to Update Your Application's S3 Endpoint for Quake AI

How to update your application's S3 endpoint for Quake AI

What changes#

Environment variables#

SDK examples#

Python (boto3)#

Node.js (AWS SDK v3)#

Go (AWS SDK v2)#

Java (AWS SDK v2)#

Terraform (S3 backend)#

Feature audit before switching#

Gradual cutover with dual-write#

See also#

Usage Guidelines

Quick answers

See Also