> ## Documentation Index
> Fetch the complete documentation index at: https://docs.coreweave.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Manage objects

> Upload, list, delete, and rename objects in AI Object Storage buckets

This guide explains how to manage objects stored in CoreWeave AI Object Storage buckets using S3-compatible tools, including the AWS CLI, s3cmd, Boto3, and s5cmd. For high-performance or bulk transfers, see [Migrate data to AI Object Storage](/products/storage/object-storage/migrate-data#migrate-data-with-s5cmd) for s5cmd (use the [CoreWeave fork](https://github.com/coreweave/s5cmd) for AI Object Storage). Alternatively, you can [use Cyberduck](/products/storage/object-storage/using-object-storage/cyberduck) to manage your buckets and objects in a graphical interface. The Cloud Console doesn't support managing objects.

To manage versioned buckets with rclone, see [Versioned buckets](/products/storage/object-storage/buckets/rclone-versioned-buckets).

## Prerequisites

This guide presumes you have the following:

* An active [CoreWeave account](https://console.coreweave.com).
* A valid [API Access Key and Secret Token key pair](/products/storage/object-storage/auth-access/create-access-tokens).
* Adequate permissions to manage objects in CoreWeave AI Object Storage (for example, `s3:PutObject` and `s3:DeleteObject`). For more information, see [Object Storage S3 Permissions](/products/storage/object-storage/reference/object-storage-s3).
* An [organization access policy](/products/storage/object-storage/auth-access/organization-policies/manage) set.
* A properly configured SDK of your choosing.
* The primary endpoint, `https://cwobject.com`, requires TLS v1.3. Ensure your S3-compatible tools and OpenSSL use TLS v1.3.
* Make sure your S3 configuration uses the [correct endpoint URL](/products/storage/object-storage/using-object-storage/configure-endpoints#set-endpoint-url)
  and [has virtual-hosted addressing enabled](/products/storage/object-storage/using-object-storage/configure-endpoints#set-virtual-addressing-style).

<Accordion title="Configure your endpoint">
  Before running the commands in this guide, make sure your S3 client is configured with:

  * **Virtual-hosted addressing enabled** (`s3.addressing_style = virtual`). Path-style addressing is not supported. See [Set virtual addressing style](/products/storage/object-storage/using-object-storage/configure-endpoints#set-virtual-addressing-style).
  * **The correct endpoint URL**:
    * `http://cwlota.com` when running inside a CoreWeave cluster (LOTA, best performance).
    * `https://cwobject.com` when running outside a CoreWeave cluster.
</Accordion>

## Add objects

Upload objects to a bucket so your data is available for downstream applications, sharing, or processing. Choose the tab that matches the tool you use.

<Tabs>
  <Tab title="AWS CLI">
    Ensure you have [the AWS CLI installed and configured](/products/storage/object-storage/buckets/manage-buckets#install-tools).

    Use the `s3 cp` command to copy a file into a bucket addressed using the `s3://` scheme.

    ```bash title="Example command" theme={"system"}
    aws s3 cp [LOCAL-FILE-PATH] s3://[BUCKET-NAME]
    ```

    ```text title="Example output" theme={"system"}
    upload: ./my-important-file.txt to s3://my-bucket-name/my-important-file.txt
    ```
  </Tab>

  <Tab title="s3cmd">
    Ensure you have [s3cmd installed, configured, and correctly credentialed](/products/storage/object-storage/buckets/manage-buckets#install-tools).

    Use the `put` command to copy an object into the bucket.

    ```bash title="Example command" theme={"system"}
    s3cmd put [LOCAL-FILE-PATH] s3://[BUCKET-NAME]
    ```

    This returns the following output, confirming your object is stored in your bucket:

    ```text title="Example output" theme={"system"}
    upload: 'my-important-file.txt' -> 's3://my-bucket-name/my-important-file.txt'
    ```
  </Tab>

  <Tab title="Boto3">
    1. Set environment variables for your CoreWeave credentials:

       ```bash theme={"system"}
       export ACCESS_KEY_ID="[ACCESS-KEY-ID]"
       export SECRET_ACCESS_KEY="[SECRET-ACCESS-KEY]"
       ```

       Alternatively, configure your CoreWeave credentials to work with the AWS CLI.

       We recommend using a separate profile for CoreWeave AI Object Storage to avoid conflicts with your other AWS profiles and S3-compatible services. If you don't set up this configuration, you might encounter errors when using AI Object Storage.

           <Accordion title="Configure CoreWeave credentials">
             1. Create a new credentials file and profile in your CoreWeave configuration directory.

                ```bash title="Create a new credentials file and profile" theme={"system"}
                AWS_SHARED_CREDENTIALS_FILE=~/.coreweave/cw.credentials aws configure --profile cw
                ```

             2. When prompted, provide the following values:

                * **AWS Access Key ID**: The [Access Key](/products/storage/object-storage/auth-access/manage-access-keys/create-keys) ID of your CoreWeave AI Object Storage Access Key.
                * **AWS Secret Access Key**: The Secret Key of your CoreWeave AI Object Storage Access Key.
                * **Default region name** (Optional): To set a default region, see [CoreWeave Availability Zones](/products/storage/object-storage/buckets/manage-buckets#availability-zones).
                * **Default output format**: Use `json` for JSON output.

             3. Set the default endpoint URL to the appropriate endpoint for your use case:

                * The primary endpoint, `https://cwobject.com`, for use outside a CoreWeave cluster.
                * The LOTA endpoint, `http://cwlota.com`, for use inside a CoreWeave cluster. The LOTA endpoint routes to the LOTA path for best performance.

                ```bash title="Set the primary endpoint for local development" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set endpoint_url https://cwobject.com --profile cw
                ```

             4. Set the S3 `addressing_style` to `virtual`:

                ```bash title="Set virtual addressing style" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set s3.addressing_style virtual --profile cw
                ```
           </Accordion>

    2. Use the following Python script to upload a file to your S3 bucket. Replace the following placeholders with the appropriate values for your request:

       * `[BUCKET-NAME]`: The name of the bucket to upload the file to.
       * `[LOCAL-FILE-PATH]`: The path to the local file to upload.
       * `[OBJECT-NAME]`: The name of the object to upload. This is optional. If you don't set a value, the upload uses the same string as your `[LOCAL-FILE-PATH]`.

       ```python title="Upload a file to a bucket" theme={"system"}
       import os
       import boto3
       from botocore.client import Config

       boto_config = Config(
           region_name='US-EAST-04A',
           s3={'addressing_style': 'virtual'}
       )

       # Create the S3 client
       s3 = boto3.client(
           's3',
           endpoint_url='https://cwobject.com',
           aws_access_key_id=os.environ['ACCESS_KEY_ID'],
           aws_secret_access_key=os.environ['SECRET_ACCESS_KEY'],
           config=boto_config
       )

       # Define your bucket name and the file path
       bucket_name = '[BUCKET-NAME]'
       file_name = '[LOCAL-FILE-PATH]'
       object_name = '[OBJECT-NAME]'  # This is optional. If you don't set a value, the upload uses the same string as your file_name.

       # Upload file
       s3.upload_file(file_name, bucket_name, object_name)

       print(f'File {file_name} uploaded to {bucket_name}/{object_name}')
       ```

    If this succeeds, a confirmation message is printed.

    ```text title="Example output" theme={"system"}
    File /path/to/my-file uploaded to my-bucket-name/my-important-file
    ```
  </Tab>
</Tabs>

### Verify object integrity

CoreWeave AI Object Storage supports checksum algorithms for verifying object integrity on upload and download. For the full list of supported algorithms, see [Checksum algorithms](/products/storage/object-storage/reference/object-storage-s3#checksum-algorithms).

### Quota limit errors

If you try to upload an object to a bucket in an Availability Zone where capacity quota limits have been reached, you receive an error message:

`<Message>The account is write suspended.</Message>`

To resolve this, you can [request a quota increase](/products/storage/object-storage/manage-quotas).

## List buckets and their contents

Listing buckets and their contents helps you confirm which buckets exist in your account and verify which objects are stored in a given bucket. You can list buckets and their contents using S3-compatible tools such as the AWS CLI, s3cmd, or Boto3. If you're working with versioned buckets, you can [use rclone](/products/storage/object-storage/buckets/rclone-versioned-buckets#listing-objects) to list buckets and their contents, including delete markers.

<Tabs>
  <Tab title="AWS CLI">
    If you want to see all of your available buckets, use the `ls` command:

    ```bash theme={"system"}
    aws s3 ls
    ```

    To list all the objects in a bucket, use the `ls` command to target a bucket path.

    ```bash theme={"system"}
    aws s3 ls s3://[BUCKET-NAME]
    ```

    The terminal returns a listing for your selected bucket showing each object, its size, and its last modified date.

    ```yaml title="Example file listing output" theme={"system"}
    2024-10-14 15:35:10 123456 my-first-file.txt
    2024-10-14 16:45:22 234567 another-file-of-mine.txt
    ```
  </Tab>

  <Tab title="s3cmd">
    To list all your available buckets, use the `ls` command:

    ```bash theme={"system"}
    s3cmd ls
    ```

    To see the contents of a specific bucket, target the bucket's path using the `s3://` scheme.

    ```bash title="Example command" theme={"system"}
    s3cmd ls s3://[BUCKET-NAME]/
    ```

    This command outputs a list of file paths including the bucket name and file name. For example:

    ```text title="Example output" theme={"system"}
    2024-10-14 15:35 123456 s3://my-bucket-name/my-first-file.txt
    2024-10-14 16:45 234567 s3://my-bucket-name/another-file-of-mine.txt
    ```
  </Tab>

  <Tab title="Boto3">
    1. Set environment variables for your CoreWeave credentials:

       ```bash theme={"system"}
       export ACCESS_KEY_ID="[ACCESS-KEY-ID]"
       export SECRET_ACCESS_KEY="[SECRET-ACCESS-KEY]"
       ```

       Alternatively, configure your CoreWeave credentials to work with the AWS CLI.

       We recommend using a separate profile for CoreWeave AI Object Storage to avoid conflicts with your other AWS profiles and S3-compatible services. If you don't set up this configuration, you might encounter errors when using AI Object Storage.

           <Accordion title="Configure CoreWeave credentials">
             1. Create a new credentials file and profile in your CoreWeave configuration directory.

                ```bash title="Create a new credentials file and profile" theme={"system"}
                AWS_SHARED_CREDENTIALS_FILE=~/.coreweave/cw.credentials aws configure --profile cw
                ```

             2. When prompted, provide the following values:

                * **AWS Access Key ID**: The [Access Key](/products/storage/object-storage/auth-access/manage-access-keys/create-keys) ID of your CoreWeave AI Object Storage Access Key.
                * **AWS Secret Access Key**: The Secret Key of your CoreWeave AI Object Storage Access Key.
                * **Default region name** (Optional): To set a default region, see [CoreWeave Availability Zones](/products/storage/object-storage/buckets/manage-buckets#availability-zones).
                * **Default output format**: Use `json` for JSON output.

             3. Set the default endpoint URL to the appropriate endpoint for your use case:

                * The primary endpoint, `https://cwobject.com`, for use outside a CoreWeave cluster.
                * The LOTA endpoint, `http://cwlota.com`, for use inside a CoreWeave cluster. The LOTA endpoint routes to the LOTA path for best performance.

                ```bash title="Set the primary endpoint for local development" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set endpoint_url https://cwobject.com --profile cw
                ```

             4. Set the S3 `addressing_style` to `virtual`:

                ```bash title="Set virtual addressing style" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set s3.addressing_style virtual --profile cw
                ```
           </Accordion>

    2. List all your buckets programmatically using the following script:

       ```python title="List all buckets" theme={"system"}
       import os
       import boto3
       from botocore.client import Config

       boto_config = Config(
           region_name='US-EAST-04A',
           s3={'addressing_style': 'virtual'}
       )

       s3 = boto3.client(
           's3',
           endpoint_url='https://cwobject.com',
           aws_access_key_id=os.environ['ACCESS_KEY_ID'],
           aws_secret_access_key=os.environ['SECRET_ACCESS_KEY'],
           config=boto_config
       )

       response = s3.list_buckets()

       print("Existing buckets:")
       for bucket in response['Buckets']:
           print(f'  {bucket["Name"]}')
       ```

    3. To view the contents of a specific bucket, replace `[BUCKET-NAME]` with the name of your bucket:

       ```python title="List objects in a bucket" theme={"system"}
       import os
       import boto3
       from botocore.client import Config

       boto_config = Config(
           region_name='US-EAST-04A',
           s3={'addressing_style': 'virtual'}
       )

       s3 = boto3.client(
           's3',
           endpoint_url='https://cwobject.com',
           aws_access_key_id=os.environ['ACCESS_KEY_ID'],
           aws_secret_access_key=os.environ['SECRET_ACCESS_KEY'],
           config=boto_config
       )

       bucket_name = '[BUCKET-NAME]'

       response = s3.list_objects_v2(Bucket=bucket_name)

       if 'Contents' in response:
           print(f"Objects in {bucket_name}:")
           for obj in response['Contents']:
               print(f'  {obj["Key"]} (Size: {obj["Size"]} bytes)')
       else:
           print(f"No objects found in {bucket_name}.")
       ```

    The resulting output looks similar to the following:

    ```text title="Example output" theme={"system"}
    Objects in my-bucket-name:
    my-first-file.txt (Size: 4500 bytes)
    another-file-of-mine.txt (Size: 5400 bytes)
    ```
  </Tab>
</Tabs>

## Delete an object from a bucket

Delete objects you no longer need to free up capacity and keep your buckets organized. Deletions are permanent on buckets that don't have versioning enabled, so confirm the target object before you run these commands.

<Tabs>
  <Tab title="AWS CLI">
    To delete specific objects from a bucket, use the `rm` command with the AWS CLI.

    ```bash theme={"system"}
    aws s3 rm s3://[BUCKET-NAME]/[OBJECT-NAME]
    ```

    When this succeeds, a confirmation message like this one is printed:

    ```text title="Example output" theme={"system"}
    delete: s3://my-bucket-name/my-important-file.txt
    ```
  </Tab>

  <Tab title="s3cmd">
    To delete an object from a bucket, use the `del` command.

    ```bash title="Example command" theme={"system"}
    s3cmd del s3://[BUCKET-NAME]/[OBJECT-NAME]
    ```

    If this succeeds, a confirmation message is printed:

    ```text title="Example output" theme={"system"}
    Object s3://my-bucket-name/my-important-file.txt deleted
    ```
  </Tab>

  <Tab title="Boto3">
    1. Set environment variables for your CoreWeave credentials:

       ```bash theme={"system"}
       export ACCESS_KEY_ID="[ACCESS-KEY-ID]"
       export SECRET_ACCESS_KEY="[SECRET-ACCESS-KEY]"
       ```

       Alternatively, configure your CoreWeave credentials to work with the AWS CLI.

       We recommend using a separate profile for CoreWeave AI Object Storage to avoid conflicts with your other AWS profiles and S3-compatible services. If you don't set up this configuration, you might encounter errors when using AI Object Storage.

           <Accordion title="Configure CoreWeave credentials">
             1. Create a new credentials file and profile in your CoreWeave configuration directory.

                ```bash title="Create a new credentials file and profile" theme={"system"}
                AWS_SHARED_CREDENTIALS_FILE=~/.coreweave/cw.credentials aws configure --profile cw
                ```

             2. When prompted, provide the following values:

                * **AWS Access Key ID**: The [Access Key](/products/storage/object-storage/auth-access/manage-access-keys/create-keys) ID of your CoreWeave AI Object Storage Access Key.
                * **AWS Secret Access Key**: The Secret Key of your CoreWeave AI Object Storage Access Key.
                * **Default region name** (Optional): To set a default region, see [CoreWeave Availability Zones](/products/storage/object-storage/buckets/manage-buckets#availability-zones).
                * **Default output format**: Use `json` for JSON output.

             3. Set the default endpoint URL to the appropriate endpoint for your use case:

                * The primary endpoint, `https://cwobject.com`, for use outside a CoreWeave cluster.
                * The LOTA endpoint, `http://cwlota.com`, for use inside a CoreWeave cluster. The LOTA endpoint routes to the LOTA path for best performance.

                ```bash title="Set the primary endpoint for local development" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set endpoint_url https://cwobject.com --profile cw
                ```

             4. Set the S3 `addressing_style` to `virtual`:

                ```bash title="Set virtual addressing style" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set s3.addressing_style virtual --profile cw
                ```
           </Accordion>

    2. Use the following script to delete an object from a bucket. Replace `[BUCKET-NAME]` with the name of the bucket and `[OBJECT-NAME]` with the key of the object to delete.

       ```python title="Delete an object from a bucket" theme={"system"}
       import os
       import boto3
       from botocore.client import Config

       boto_config = Config(
           region_name='US-EAST-04A',
           s3={'addressing_style': 'virtual'}
       )

       s3 = boto3.client(
           's3',
           endpoint_url='https://cwobject.com',
           aws_access_key_id=os.environ['ACCESS_KEY_ID'],
           aws_secret_access_key=os.environ['SECRET_ACCESS_KEY'],
           config=boto_config
       )

       bucket_name = '[BUCKET-NAME]'
       object_name = '[OBJECT-NAME]'

       s3.delete_object(Bucket=bucket_name, Key=object_name)

       print(f'Object {object_name} deleted from {bucket_name}')
       ```

    If successful, a success message is printed:

    ```text title="Example output" theme={"system"}
    Object my-important-file deleted from my-bucket-name
    ```
  </Tab>
</Tabs>

<Info>
  For more information about accessing and interacting with the contents of your buckets, see the [official Amazon documentation for S3 buckets](https://docs.aws.amazon.com/AmazonS3/latest/userguide/access-bucket-intro.html).
</Info>

## Rename an object

Rename an object to change its key without re-uploading the underlying data. This is useful when you need to correct a typo, restructure a key prefix, or align object names with a new naming convention.

Make sure you have the following to rename an object:

* `s3:PutObject` and `s3:DeleteObject` permissions.
* A bucket that **does not** have versioning enabled, now or in the past.
* A request scoped to renaming a single object within the same bucket. The source and destination keys must be in the same bucket.

For more information, see [Rename Objects](/products/storage/object-storage/buckets/rename-objects).

<Tabs>
  <Tab title="AWS CLI">
    To rename an object, use the `aws s3api rename-object` command with the AWS CLI.

    Replace the following placeholders with the appropriate values for your request:

    * `[BUCKET-NAME]`: The name of the bucket containing the object.
    * `[SOURCE-OBJECT-NAME]`: The current name of the object.
    * `[DESTINATION-OBJECT-NAME]`: The new name for the object.

    ```bash title="Rename object" theme={"system"}
    aws s3api rename-object \
      --bucket [BUCKET-NAME] \
      --key [DESTINATION-OBJECT-NAME] \
      --rename-source /[BUCKET-NAME]/[SOURCE-OBJECT-NAME]
    ```

    When this succeeds, a confirmation message is printed:

    ```text title="Example output" theme={"system"}
    rename: s3://my-bucket-name/my-important-file.txt -> s3://my-bucket-name/my-new-file.txt
    ```
  </Tab>

  <Tab title="s3cmd">
    To rename an object, use the `mv` command with s3cmd.

    <Warning>
      **Copy and delete operation**

      The s3cmd `mv` command performs a copy and delete operation instead of an atomic rename operation. For atomic rename operations, use the AWS CLI or Boto3 with the `RenameObject` API.
    </Warning>

    <Tip>
      To prevent accidental overwrites when uploading objects, use the `If-None-Match: *` header with `PutObject`. For details, see [Conditional writes](/products/storage/object-storage/reference/object-storage-s3#conditional-writes).
    </Tip>

    Replace the following placeholders with the appropriate values for your request:

    * `[BUCKET-NAME]`: The name of the bucket containing the source object.
    * `[SOURCE-OBJECT-NAME]`: The name of the source object to rename.
    * `[DESTINATION-OBJECT-NAME]`: The new name for the object.

    ```bash title="Rename object" theme={"system"}
    s3cmd mv s3://[BUCKET-NAME]/[SOURCE-OBJECT-NAME] s3://[BUCKET-NAME]/[DESTINATION-OBJECT-NAME]
    ```
  </Tab>

  <Tab title="Boto3">
    1. Set environment variables for your CoreWeave credentials:

       ```bash theme={"system"}
       export ACCESS_KEY_ID="[ACCESS-KEY-ID]"
       export SECRET_ACCESS_KEY="[SECRET-ACCESS-KEY]"
       ```

       Alternatively, configure your CoreWeave credentials to work with the AWS CLI.

       We recommend using a separate profile for CoreWeave AI Object Storage to avoid conflicts with your other AWS profiles and S3-compatible services. If you don't set up this configuration, you might encounter errors when using AI Object Storage.

           <Accordion title="Configure CoreWeave credentials">
             1. Create a new credentials file and profile in your CoreWeave configuration directory.

                ```bash title="Create a new credentials file and profile" theme={"system"}
                AWS_SHARED_CREDENTIALS_FILE=~/.coreweave/cw.credentials aws configure --profile cw
                ```

             2. When prompted, provide the following values:

                * **AWS Access Key ID**: The [Access Key](/products/storage/object-storage/auth-access/manage-access-keys/create-keys) ID of your CoreWeave AI Object Storage Access Key.
                * **AWS Secret Access Key**: The Secret Key of your CoreWeave AI Object Storage Access Key.
                * **Default region name** (Optional): To set a default region, see [CoreWeave Availability Zones](/products/storage/object-storage/buckets/manage-buckets#availability-zones).
                * **Default output format**: Use `json` for JSON output.

             3. Set the default endpoint URL to the appropriate endpoint for your use case:

                * The primary endpoint, `https://cwobject.com`, for use outside a CoreWeave cluster.
                * The LOTA endpoint, `http://cwlota.com`, for use inside a CoreWeave cluster. The LOTA endpoint routes to the LOTA path for best performance.

                ```bash title="Set the primary endpoint for local development" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set endpoint_url https://cwobject.com --profile cw
                ```

             4. Set the S3 `addressing_style` to `virtual`:

                ```bash title="Set virtual addressing style" theme={"system"}
                AWS_CONFIG_FILE=~/.coreweave/cw.config aws configure set s3.addressing_style virtual --profile cw
                ```
           </Accordion>

    2. Use the [`rename_object`](https://docs.aws.amazon.com/boto3/latest/reference/services/s3/client/rename_object.html) method to rename an object. Replace `[BUCKET-NAME]`, `[SOURCE-OBJECT-NAME]`, and `[DESTINATION-OBJECT-NAME]` with the appropriate values for your request.

       ```python title="Rename an object" theme={"system"}
       import os
       import boto3
       from botocore.client import Config

       boto_config = Config(
           region_name='US-EAST-04A',
           s3={'addressing_style': 'virtual'}
       )

       s3 = boto3.client(
           's3',
           endpoint_url='https://cwobject.com',
           aws_access_key_id=os.environ['ACCESS_KEY_ID'],
           aws_secret_access_key=os.environ['SECRET_ACCESS_KEY'],
           config=boto_config
       )

       response = s3.rename_object(
           Bucket='[BUCKET-NAME]',
           Key='[DESTINATION-OBJECT-NAME]',
           RenameSource='/[BUCKET-NAME]/[SOURCE-OBJECT-NAME]'
       )

       print('Object renamed successfully.')
       ```
  </Tab>
</Tabs>