Gretel Connectors

Integrate Gretel with your existing data services using Workflows.

With Gretel Workflows, you can train and run one or more Gretel Models by connecting directly to your data sources and destinations. We support the following integrations for data inputs and outputs.

Supported Connectors

Object Storage

Relational Databases

Data Warehouses

Managing Connections

Connections are used to authenticate Workflow Actions. Each action is compatible with a specific type of connection. For example, the s3_source action requires a s3 connection.

When creating a connection, you must select a project for the connection to reside in. The connection will inherit all the project permissions and user memberships.

Project Permission

Connection Permissions

Read

Users can list and view connection metadata.

Write

Users can access connections in a Workflow.

Administrator

Users can create, edit and delete connections.

Owner

Full control.

Connections can be reused across Workflows, actions, and projects.

Creating Connections

Navigate to the Connections page using the menu item in the left sidebar.
Click the New Connection button in the top right corner.
Select the Connector Type.
Select the project where the connection will be stored.
Next, fill in your credentials and select Add Connection. The example below shows the flow for creating an Amazon S3 connection. All connections follow the same pattern.
The connection can now be used in a workflow.

Data sources also can be configured during a blueprint flow. Go to the Dashboard or Blueprints page and select a use case, for example "Generate synthetic data". This will start a guided flow to help you create a workflow.
Select the option to connect to an external data source, and choose the connection you created above, or create a new one.

from gretel_client import create_or_get_unique_project
from gretel_client.config import get_session_config
from gretel_client.rest_v1.api.connections_api import ConnectionsApi
from gretel_client.rest_v1.models import (
    CreateConnectionRequest,
    UpdateConnectionRequest,
)

session = get_session_config()
connection_api = session.get_v1_api(ConnectionsApi)

project = create_or_get_unique_project(name="workflow-testing")

connection = connection_api.create_connection(
    CreateConnectionRequest(
        name="my-s3-conn",
        project_id=project.project_guid,
        type="s3",
        # note: best practice is to read in credentials from a file
        # or secret instead of directly embedding sensitive values
        # in python code.
        config={
            "access_key_id": "...",
        },
        credentials={
            "secret_access_key": "...",
        },
    )
)

Updating Connections

Connection types cannot be changed once a connection is created.

Navigate to the Connections page using the menu item in the left sidebar.
Go to the Connection you'd like to update and click the three vertical dots (aka overflow actions).
Select Update Connection.
Modify the name and/or credentials and select Save. All workflows that use this connection will automatically use the new information.

If you only want to edit the connection name, leave the credentials fields as they are.

Expanding on the example from Creating Connections

connection = connection_api.update_connection(
    connection_id=connection.id,
    update_connection_request=UpdateConnectionRequest(
        name="my-s3-conn",
        config={
            "access_key_id": "...",
        },
        credentials={
            "secret_access_key": "...",
        },
    )
)

Deleting Connections

On the Connections list page, select the three dots (aka overflow actions) to the right of the connection you want to delete.
Select Delete

Expanding on the example from Creating Connections

connection_api.delete_connection(connection_id=connection.id)

PreviousInputs and Outputs NextObject Storage

Last updated 2 months ago

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