Using Amazon Bedrock Data Automation CLI

The Amazon Bedrock Data Automation (BDA) feature provides a streamlined CLI workflow for processing your data. For all modalities, this workflow consists of three main steps: creating a project, creating Blueprints for custom output, and processing documents. This guide walks you through the key CLI commands for working with BDA.

Create your first Data Automation project

To begin working with BDA, first create a project using the create-data-automation-project command.

Consider this sample passport that we'll process:

When creating a project, you must define your configuration settings for the type of file you intend to process. The following command represents a minimal working example for creating an image processing project:

aws bedrock-data-automation create-data-automation-project \
    --project-name "ImageProcessingProject" \
    --standard-output-configuration '{
        "image": {
            "extraction": {
                "category": {
                    "state": "ENABLED",
                    "types": ["TEXT_DETECTION"]
                },
                "boundingBox": {
                    "state": "ENABLED"
                }
            },
            "generativeField": {
                "state": "ENABLED"
            }
        }
    }'

The command validates the input configuration and creates a new project with a unique ARN. A response would include the project ARN and stage:

{
    "projectArn": "Amazon Resource Name (ARN)",
    "projectStage": "DEVELOPMENT",
    "status": "IN_PROGRESS"
}

If a project is created with no parameters, the default settings will apply. For example, when processing images, image summarization and text detection will be enabled by default.

Complete parameter reference

The following table shows all available parameters for the create-data-automation-project command:

Parameters for create-data-automation-project

Parameter	Required	Default	Description
--project-name	Yes	N/A	Name for the Data Automation project
--project-stage	No	LIVE	Stage for the project (DEVELOPMENT or LIVE)
--standard-output-configuration	Yes	N/A	JSON configuration for standard output processing
--custom-output-configuration	No	N/A	JSON configuration for custom output processing
--encryption-configuration	No	N/A	Encryption settings for the project
--client-token	No	Auto-generated	Unique identifier for request idempotency

Creating a Blueprint

After creating a project, you can create a Blueprint to define the structure of your data processing using the create-blueprint command.

Here's a minimal working example for creating a Blueprint tailored to passport processing:

aws bedrock-data-automation create-blueprint \
    --blueprint-name "passport-blueprint" \
    --type "IMAGE" \
    --blueprint-stage "DEVELOPMENT" \
    --schema '{
        "class": "Passport",
        "description": "Blueprint for processing passport images",
        "properties": {
            "passport_number": {
                "type": "string",
                "inferenceType": "explicit",
                "instruction": "The passport identification number"
            },
            "full_name": {
                "type": "string",
                "inferenceType": "explicit",
                "instruction": "The full name of the passport holder"
            }
        }
    }'

The command creates a new Blueprint with the specified schema. You can then use this Blueprint when processing documents to extract structured data according to your defined schema.

Using your Blueprint

Adding a Blueprint to a project

To add a Blueprint to your project, use the update-data-automation-project command:

aws bedrock-data-automation update-data-automation-project \
    --project-arn "Amazon Resource Name (ARN)" \
    --standard-output-configuration '{
        "image": {
            "extraction": {
                "category": {
                    "state": "ENABLED",
                    "types": ["TEXT_DETECTION"]
                },
                "boundingBox": {
                    "state": "ENABLED"
                }
            },
            "generativeField": {
                "state": "ENABLED",
                "types": ["IMAGE_SUMMARY"]
            }
        }
    }' \
    --custom-output-configuration '{
        "blueprints": [
            {
                "blueprintArn": "Amazon Resource Name (ARN)",
                "blueprintVersion": "1",
                "blueprintStage": "LIVE"
            }
        ]
    }'

Verifying Blueprint integration

You can verify the Blueprint integration using the get-data-automation-project command:

aws bedrock-data-automation get-data-automation-project \
    --project-arn "Amazon Resource Name (ARN)"

Managing multiple Blueprints

Use the list-blueprints command to view all of your Blueprints:

aws bedrock-data-automation list-blueprints

Process Documents

Once you have a project set up, you can process documents using the invoke-data-automation-async command:

aws bedrock-data-automation-runtime invoke-data-automation-async \
    --input-configuration '{
        "s3Uri": "s3://my-bda-documents/invoices/invoice-123.pdf"
    }' \
    --output-configuration '{
        "s3Uri": "s3://my-bda-documents/output/"
    }' \
    --data-automation-configuration '{
        "dataAutomationProjectArn": "Amazon Resource Name (ARN)",
        "stage": "LIVE"
    }' \
    --data-automation-profile-arn "Amazon Resource Name (ARN)"

The command returns an invocation ARN that you can use to check the processing status:

{
    "invocationArn": "Amazon Resource Name (ARN)"
}

Check Processing Status

To check the status of your processing job, use the get-data-automation-status command:

aws bedrock-data-automation-runtime get-data-automation-status \
    --invocation-arn "Amazon Resource Name (ARN)"

The command returns the current status of the processing job:

{
    "status": "COMPLETED",
    "creationTime": "2025-07-09T12:34:56.789Z",
    "lastModifiedTime": "2025-07-09T12:45:12.345Z",
    "outputLocation": "s3://my-bda-documents/output/efgh5678/"
}

Possible status values include:

• IN_PROGRESS: The processing job is currently running.

• COMPLETED: The processing job has successfully completed.

• FAILED: The processing job has failed. Check the response for error details.

• STOPPED: The processing job was manually stopped.

Retrieve Results

Once processing is complete, you can list the output files in your S3 bucket:

aws s3 ls s3://my-bda-documents/output/efgh5678/

To download the results to your local machine:

aws s3 cp s3://my-bda-documents/output/efgh5678/ ~/Downloads/bda-results/ --recursive

The output includes structured data based on your project configuration and any Blueprints you've applied.