S3-compatible API

Use Runpod’s S3-compatible API to access and manage your network volumes.

Runpod provides an S3-protocol compatible API for direct access to your network volumes. This allows you to manage files on your network volumes without launching a Pod, reducing cost and operational friction.

Using the S3-compatible API does not affect pricing. Network volumes are billed hourly at $0.07/GB/month for the first 1TB, and $0.05/GB/month for additional storage.

Datacenter availability

The S3-compatible API is available for network volumes in select datacenters. Each datacenter has a unique endpoint URL that you’ll use when calling the API:

Datacenter	Endpoint URL
EUR-IS-1	https://s3api-eur-is-1.runpod.io/
EU-RO-1	https://s3api-eu-ro-1.runpod.io/
EU-CZ-1	https://s3api-eu-cz-1.runpod.io/
US-KS-2	https://s3api-us-ks-2.runpod.io/

Create your network volume in a supported datacenter to use the S3-compatible API.

Setup and authentication

1. Create a network volume

   First, create a network volume in a supported datacenter. See Network volumes -> Create a network volume for detailed instructions.

2. Create an S3 API key

   Next, you’ll need to generate a new key called an “S3 API key” (this is separate from your Runpod API key).

   1. Go to the Settings page in the Runpod console.
   2. Expand S3 API Keys and select Create an S3 API key.
   3. Name your key and select Create.
   4. Save the access key (e.g., user_***...) and secret (e.g., rps_***...) to use in the next step.

   For security, Runpod will show your API key secret only once, so you may wish to save it elsewhere (e.g., in your password manager, or in a GitHub secret). Treat your API key secret like a password and don’t share it with anyone.

3. Configure AWS CLI

   To use the S3-compatible API with your Runpod network volumes, you must configure your AWS CLI with the Runpod S3 API key you created.

   1. If you haven’t already, install the AWS CLI on your local machine.
   2. Run the command aws configure in your terminal.
   3. Provide the following when prompted:
      • AWS Access Key ID: Enter your Runpod user ID. You can find this in the Secrets section of the Runpod console, in the description of your S3 API key. By default, the description will look similar to: Shared Secret for user_2f21CfO73Mm2Uq2lEGFiEF24IPw 1749176107073. user_2f21CfO73Mm2Uq2lEGFiEF24IPw is the user ID (yours will be different).
      • AWS Secret Access Key: Enter your Runpod S3 API key’s secret access key.
      • Default Region name: You can leave this blank.
      • Default output format: You can leave this blank or set it to json.

   This will configure the AWS CLI to use your Runpod S3 API key by storing these details in your AWS credentials file (typically at ~/.aws/credentials).

Using the S3-compatible API

You can use the S3-compatible API to interact with your Runpod network volumes using standard S3 tools:

• AWS s3 CLI.
• AWS s3api CLI.
• The Boto3 Python library.

Core AWS CLI operations such as ls, cp, mv, rm, and sync function as expected.

s3 CLI examples

When using aws s3 commands, you must pass in the endpoint URL for your network volume using the --endpoint-url flag and the datacenter ID using the --region flag.

The --region flag is case-sensitive. For instance, --region EU-RO-1 is a valid input, whereas --region eu-ro-1 will be rejected.

Unlike traditional S3 key-value stores, object names in the Runpod S3-compatible API correspond to actual file paths on your network volume. Object names containing special characters (e.g., #) may need to be URL-encoded to ensure proper processing.

List objects

Use ls to list objects in a network volume directory:

aws s3 ls --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \ 
    s3://[NETWORK_VOLUME_ID]/[REMOTE_DIR]

Unlike standard S3 buckets, ls and ListObjects operations will list empty directories.

ls operations may take a long time when used on a directory containing many files (over 10,000) or large amounts of data (over 10GB), or when used recursively on a network volume containing either.

Transfer files

Use cp to copy a file to a network volume:

aws s3 cp --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \
    [LOCAL_FILE] \
    s3://[NETWORK_VOLUME_ID]

Use cp to copy a file from a network volume to a local directory:

aws s3 cp --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \
    s3://[NETWORK_VOLUME_ID]/remote-file.txt ./[LOCAL_DIR]

Use rm to remove a file from a network volume:

aws s3 rm --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \
    s3://[NETWORK_VOLUME_ID]/remote-file.txt

If you encounter a 502 “bad gateway” error during file transfer, try increasing AWS_MAX_ATTEMPTS to 10 or more:

export AWS_RETRY_MODE=standard
export AWS_MAX_ATTEMPTS=10

Sync directories

This command syncs a local directory (source) to a network volume directory (destination):

aws s3 sync --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \
    ./[LOCAL_DIR] \
    s3://[NETWORK_VOLUME_ID]/[REMOTE_DIR]

s3api CLI example

You can also use aws s3api commands (instead of aws s3) to interact with the S3-compatible API.

For example, here’s how you could use aws s3api get-object to download an object from a network volume:

aws s3api get-object --bucket [NETWORK_VOLUME_ID] \
    --key [REMOTE_FILE] \
    --region [DATACENTER] \
    --endpoint-url https://s3api-[DATACENTER].runpod.io/ \
    [LOCAL_FILE]

Replace [LOCAL_FILE] with the desired path and name of the file after download—for example: ~/local-dir/my-file.txt.

For a list of available s3api commands, see the AWS s3api reference.

Boto3 Python example

You can also use the Boto3 library to interact with the S3-compatible API, using it to transfer files to and from a Runpod network volume.

The script below demonstrates how to upload a file to a Runpod network volume using the Boto3 library. It takes command-line arguments for the network volume ID (as an S3 bucket), the datacenter-specific S3 endpoint URL, the local file path, the desired object (file path on the network volume), and the AWS Region (which corresponds to the Runpod datacenter ID).

Your Runpod S3 API key credentials must be set as environment variables using the values from the Setup and authentication step:

• AWS_ACCESS_KEY_ID: Should be set to your Runpod S3 API key access key (e.g., user_***...).
• AWS_SECRET_ACCESS_KEY: Should be set to your Runpod S3 API key’s secret (e.g., rps_***...).

#!/usr/bin/env python3

import os
import argparse
import boto3 # AWS SDK for Python, used to interact with Runpod S3-compatible APIs

def create_s3_client(region: str, endpoint_url: str):

    # Creates and returns an S3 client configured for Runpod network volume S3-compatible API.
    #
    # Args:
    #   region (str): The Runpod datacenter ID, used as the AWS region
    #                 (e.g., 'ca-qc-1').
    #   endpoint_url (str): The S3 endpoint URL for the specific Runpod datacenter
    #                       (e.g., 'https://ca-qc-1-s3api.runpod.io/').

    # Returns:
    #   boto3.client: An S3 client object, configured for the Runpod S3 API.

    # Retrieve Runpod S3 API key credentials from environment variables.
    aws_access_key_id = os.environ.get("AWS_ACCESS_KEY_ID")
    aws_secret_access_key = os.environ.get("AWS_SECRET_ACCESS_KEY")

    # Ensure necessary S3 API key credentials are set in the environment
    if not aws_access_key_id or not aws_secret_access_key:
        raise EnvironmentError(
            "Please set AWS_ACCESS_KEY_ID (with S3 API Key Access Key) and "
            "AWS_SECRET_ACCESS_KEY (with S3 API Key Secret Access Key) environment variables. "
            "These are obtained from 'S3 API Keys' in the Runpod console settings."
        )

    # Initialize and return the S3 client for Runpod's S3-compatible API
    return boto3.client(
        "s3",
        aws_access_key_id=aws_access_key_id,
        aws_secret_access_key=aws_secret_access_key,
        region_name=region, # Corresponds to the Runpod datacenter ID
        endpoint_url=endpoint_url, # Datacenter-specific S3 API endpoint
    )

def put_object(s3_client, bucket_name: str, object_name: str, file_path: str):

    # Uploads a local file to the specified Runpod network volume.
    #
    # Args:
    #   s3_client: The S3 client object (e.g., returned by create_s3_client).
    #   bucket_name (str): The ID of the target Runpod network volume.
    #   object_name (str): The desired file path for the object on the network volume.
    #   file_path (str): The local path to the file (including the filename) that will be uploaded.

    try:
        # Attempt to upload the file to the Runpod network volume.
        s3_client.upload_file(file_path, bucket_name, object_name)
        print(f"Successfully uploaded '{file_path}' to Network Volume '{bucket_name}' as '{object_name}'")
    except Exception as e:
        # Catch any exception during upload, print an error, and re-raise
        print(f"Error uploading file '{file_path}' to Network Volume '{bucket_name}' as '{object_name}': {e}")
        raise

def main():

    # Parses command-line arguments and orchestrates the file upload process
    # to a Runpod network volume.

    # Set up command-line argument parsing
    parser = argparse.ArgumentParser(
        description="Upload a file to a Runpod Network Volume using its S3-compatible API. "
                    "Requires AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY env vars to be set "
                    "with your Runpod S3 API key credentials."
    )
    parser.add_argument(
        "-b", "--bucket",
        required=True,
        help="The ID of your Runpod Network Volume (acts as the S3 bucket name)."
    )
    parser.add_argument(
        "-e", "--endpoint",
        required=True,
        help="The S3 endpoint URL for your Runpod datacenter (e.g., 'https://s3api-[DATACENTER].runpod.io/')."
    )
    parser.add_argument(
        "-f", "--file",
        required=True,
        help="The local path to the file to be uploaded."
    )
    parser.add_argument(
        "-o", "--object",
        required=True,
        help="The S3 object key (i.e., the desired file path on the Network Volume)."
    )
    parser.add_argument(
        "-r", "--region",
        required=True,
        help="The Runpod datacenter ID, used as the AWS region (e.g., 'ca-qc-1'). Find this in the Runpod console's Storage section or endpoint URL."
    )

    args = parser.parse_args()

    # Create the S3 client using the parsed arguments, configured for Runpod.
    client = create_s3_client(args.region, args.endpoint)

    # Upload the object to the specified network volume.
    put_object(client, args.bucket, args.object, args.file)

if __name__ == "__main__":
    main()

When uploading files with Boto3, you must specify the complete file path (including the filename) for both source and destination files.

For example, for the put_objects method above, you must specify these arguments:

• file_path: The local source file (e.g., local_directory/file.txt).
• object_name: The remote destination file to be created on the network volume (e.g., remote_directory/file.txt).

With that in mind, here’s an example of how to run the script above using command-line arguments:

./s3_example_put.py --endpoint https://s3api-eur-is-1.runpod.io/ \
    --region 'EUR-IS-1' \
    --bucket 'network_volume_id' \
    --object 'remote_directory/file.txt' \
    --file 'local_directory/file.txt'

Uploading very large files

You can upload large files to network volumes using S3 multipart upload operations (see the compatibility reference below). You can also download this helper script, which dramatically improves reliability when uploading very large files (10GB+) by handling timeouts and retries automatically.

Click here to download the script on GitHub.

Here’s an example of how to run the script using command line arguments:

./upload_large_file.py --file /path/to/large/file.mp4 \
     --bucket NETWORK_VOLUME_ID \
     --access_key YOUR_ACCESS_KEY_ID \
     --secret_key YOUR_SECRET_ACCESS_KEY \
     --endpoint https://s3api-eur-is-1.runpod.io/ \
     --region EUR-IS-1

S3 API compatibility reference

The tables below show which S3 API operations and AWS CLI commands are currently supported. Use the tables below to understand what functionality is available and plan your development workflows accordingly.

For detailed information on these operations, refer to the AWS S3 API documentation.

If a function is not listed below, that means it’s not currently implemented. We are continuously expanding the S3-compatible API based on customer needs and usage patterns.

Core operations

Operation	Supported	CLI Command	Notes
CopyObject	✅	aws s3 cp, aws s3api copy-object	Copy objects between locations
DeleteObject	✅	aws s3 rm, aws s3api delete-object	Remove individual objects
GetObject	✅	aws s3 cp, aws s3api get-object	Download objects
HeadBucket	✅	aws s3 ls, aws s3api head-bucket	Verify bucket exists and permissions
HeadObject	✅	aws s3api head-object	Retrieve object metadata
ListBuckets	✅	aws s3 ls, aws s3api list-buckets	List available network volumes
ListObjects	✅	aws s3 ls, aws s3api list-objects	List objects in a bucket (includes empty directories)
ListObjectsV2	✅	aws s3 ls, aws s3api list-objects-v2	Enhanced version of ListObjects
PutObject	✅	aws s3 cp, aws s3api put-object	Upload objects (<500MB)
DeleteObjects	❌	aws s3api delete-objects	Planned
RestoreObject	❌	aws s3api restore-object	Not supported

Multipart upload operations

Files larger than 500MB must be uploaded using multipart uploads. The AWS CLI performs multipart uploads automatically.

Operation	Supported	CLI Command	Notes
CreateMultipartUpload	✅	aws s3api create-multipart-upload	Start multipart upload for large files
UploadPart	✅	aws s3api upload-part	Upload individual parts
CompleteMultipartUpload	✅	aws s3api complete-multipart-upload	Finish multipart upload
AbortMultipartUpload	✅	aws s3api abort-multipart-upload	Cancel multipart upload
ListMultipartUploads	✅	aws s3api list-multipart-uploads	View in-progress uploads
ListParts	✅	aws s3api list-parts	List parts of a multipart upload

Bucket management operations

Operation	Supported	CLI Command	Notes
CreateBucket	❌	aws s3api create-bucket	Use the Runpod console to create network volumes
DeleteBucket	❌	aws s3api delete-bucket	Use the Runpod console to delete network volumes
GetBucketLocation	❌	aws s3api get-bucket-location	Datacenter info available in the Runpod console
GetBucketVersioning	❌	aws s3api get-bucket-versioning	Versioning is not supported
PutBucketVersioning	❌	aws s3api put-bucket-versioning	Versioning is not supported
GeneratePresignedURL	❌	aws s3 presign	Pre-signed URLs are not supported

Access control and permissions

Operation	Supported	CLI Command	Notes
GetBucketAcl	❌	N/A	ACLs are not supported
PutBucketAcl	❌	N/A	ACLs are not supported
GetObjectAcl	❌	N/A	ACLs are not supported
PutObjectAcl	❌	N/A	ACLs are not supported
GetBucketPolicy	❌	N/A	Bucket policies are not supported
PutBucketPolicy	❌	N/A	Bucket policies are not supported

Object metadata and tagging

Operation	Supported	CLI Command	Notes
GetObjectTagging	❌	N/A	Object tagging is not supported
PutObjectTagging	❌	N/A	Object tagging is not supported
DeleteObjectTagging	❌	N/A	Object tagging is not supported

Encryption and security

Operation	Supported	CLI Command	Notes
GetBucketEncryption	❌	N/A	Encryption is not supported
PutBucketEncryption	❌	N/A	Encryption is not supported
GetObjectLockConfiguration	❌	N/A	Object locking is not supported
PutObjectLockConfiguration	❌	N/A	Object locking is not supported

ListObjects operations may take a long time when used on a directory containing many files (over 10,000) or large amounts of data (over 10GB), or when used recursively on a network volume containing either.

Known issues and limitations

ListObjects runs slowly or fails with “same next token” error

When running aws s3 ls or ListObjects on a directory with many files or large amounts of data (typically >10,000 files or >10 GB of data) for the first time, it may run very slowly, or you may encounter the following error:

"fatal error: Error during pagination: The same next token was received twice: ..."

This occurs because Runpod must compute and cache the MD5 checksum (i.e., ETag) for files created without the S3-compatible API. This computation can take several minutes for large directories or files, as the ListObjects request must wait until the checksum is ready.

Workarounds:

• The operation will typically complete successfully if you wait for the process to finish.
• If the client aborts with a pagination error, retry the operation after a brief pause.

Storage and time synchronization

• Storage capacity: Network volumes have a fixed storage capacity, unlike the virtually unlimited storage of standard S3 buckets. The CopyObject and UploadPart actions do not check for available free space beforehand and may fail if the volume runs out of space.
• Maximum file size: 4TB (the maximum size of a network volume).
• Object names: Unlike traditional S3 key-value stores, object names in the Runpod S3-compatible API correspond to actual file paths on your network volume. Object names containing special characters (e.g., #) may need to be URL encoded to ensure proper processing.
• Time synchronization: Requests that are out of time sync by 1 hour will be rejected. This is more lenient than the 15-minute window specified by the AWS SigV4 authentication specification.

Multipart uploads

• The maximum size for a single part of a multipart upload is 500MB.
• The AWS S3 minimum part size of 5MB is not enforced.
• Multipart upload parts and metadata are stored in a hidden .s3compat_uploads/ folder. This folder and its contents are automatically cleaned up when you call CompleteMultipartUpload or AbortMultipartUpload.

Timeout configuration for large files

When uploading large files (10GB+), you may encounter timeout errors during the CompleteMultipartUpload operation. To resolve this, we recommend using the multipart upload helper script.

Or you can try increasing the timeout settings in your AWS tools:

AWS CLI

For aws s3 and aws s3api, use the --cli-read-timeout parameter:

# Sets the timeout to 7200 seconds (2 hours)
aws s3 cp large-file.zip s3://your-volume-name/ --cli-read-timeout 7200 --endpoint-url https://storage.datacenter.runpod.io

Or, configure timeout in ~/.aws/config:

[default]
cli_read_timeout = 7200

Reference documentation

For comprehensive documentation on AWS S3 commands and libraries, refer to:

• AWS CLI S3 reference.
• AWS S3 API reference.
• Boto3 S3 reference.