--- title: Configuration --- # Configuring Looker & LookML Connector Now that you have created a DataHub-specific API key with the relevant access in [the prior step](setup.md), it's time to set up a connection via the DataHub UI. ## Configure Secrets You must create two secrets to configure a connection with Looker or LookerML. - `LOOKER_CLIENT_ID` - `LOOKER_CLIENT_SECRET` On your DataHub instance, navigate to the **Ingestion** tab in your screen's top right corner.

Navigate to the "Ingestion Tab"

:::note If you do not see the Ingestion tab, please get in touch with your DataHub admin to grant you the correct permissions. ::: Navigate to the **Secrets** tab and click **Create new secret**.

Secrets Tab

First, create a secret for the **Client Id**. The value should be the **Client Id** of the API key created in the [prior step](http://localhost:3000/docs/next/quick-ingestion-guides/looker/setup#create-an-api-key).

API Key Client ID

Then, create a secret for the **Client Secret**. The value should be the **Client Secret** of the API key created in the [prior step](http://localhost:3000/docs/next/quick-ingestion-guides/looker/setup#create-an-api-key).

API Key client secret

## Configure Looker Ingestion ### Configure Recipe Navigate to the **Sources** tab and click **Create new source**.

Click "Create new source"

Choose `Looker`.

Select Looker from the options

Enter the details into the Looker Recipe. - **Base URL:** This is your looker instance URL. (i.e. `https://.cloud.looker.com`) - **Client ID:** Use the secret LOOKER_CLIENT_ID with the format `${LOOKER_CLIENT_ID}`. - **Client Secret:** Use the secret LOOKER_CLIENT_SECRET with the format `${LOOKER_CLIENT_SECRET}`. Optionally, use the `dashboard_pattern` and `chart_pattern` fields to filter for specific dashboard and chart. config: ... dashboard_pattern: allow: - "2" chart_pattern: allow: - "258829b1-82b1-4bdb-b9fb-6722c718bbd3" Your recipe should look something like this:

Looker Recipe

After completing the recipe, click **Next**. ### Schedule Execution Now, it's time to schedule a recurring ingestion pipeline to extract metadata from your Looker instance regularly. Decide how regularly you want this ingestion to run-- day, month, year, hour, minute, etc. Select from the dropdown.

schedule selector

Ensure you've configured your correct timezone.

timezone_selector

Finally, click **Next** when you are done. ### Finish Up Name your ingestion source, then click **Save and Run**.

Name your ingestion

You will now find your new ingestion source running.

ingestion_running

## Configure LookML Connector Now that you have created a DataHub-specific API key and Deploy Key with the relevant access in [the prior step](setup.md), it's time to set up a connection via the DataHub UI. ### Configure Recipe Navigate to the **Sources** tab and click **Create new source**.

Click "Create new source"

Choose `LooML`.

Select Looker from the options

Enter the details into the Looker Recipe. You need to set a minimum 5 fields in the recipe for this quick ingestion guide: - **GitHub Repository:** This is your GitHub repository where LookML models are stored. You can provide the full URL (example: https://gitlab.com/gitlab-org/gitlab) or organization/repo; in this case, the connector assume it is a GitHub repo - **GitHub Deploy Key:** Copy the content of `looker_datahub_deploy_key` and paste into this filed. - **Looker Base URL:** This is your looker instance URL. (i.e. https://abc.cloud.looker.com) - **Looker Client ID:** Use the secret LOOKER_CLIENT_ID with the format `${LOOKER_CLIENT_ID}`. - **Looker Client Secret:** Use the secret LOOKER_CLIENT_SECRET with the format `${LOOKER_CLIENT_SECRET}`. Your recipe should look something like this:

LookML Recipe

After completing the recipe, click **Next**. ### Schedule Execution Now, it's time to schedule a recurring ingestion pipeline to extract metadata from your Looker instance regularly. Decide how regularly you want this ingestion to run-- day, month, year, hour, minute, etc. Select from the dropdown.

schedule selector

Ensure you've configured your correct timezone.

timezone_selector

Click **Next** when you are done. ### Finish Up Name your ingestion source, then click **Save and Run**.

Name your ingestion

You will now find your new ingestion source running.

ingestion_running

## Validate Ingestion Runs View the latest status of ingestion runs on the Ingestion page.

ingestion succeeded

Click the `+` sign to expand the complete list of historical runs and outcomes; click **Details** to see the results of a specific run.

ingestion_details

From the Ingestion Run Details page, pick **View All** to see which entities were ingested.

ingestion_details_view_all

Pick an entity from the list to manually validate if it contains the detail you expected.

ingestion_details_view_all

**Congratulations!** You've successfully set up Looker & LookML as an ingestion source for DataHub!