OpenMetadata/openmetadata-docs/content/v1.1.x/connectors/pipeline/fivetran/yaml.md

---
title: Run the Fivetran Connector Externally
slug: /connectors/pipeline/fivetran/yaml
---

# Run the Fivetran Connector Externally

In this section, we provide guides and references to use the Fivetran connector.

Configure and schedule Fivetran metadata and profiler workflows from the OpenMetadata UI:

- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)

{% partial file="/v1.1/connectors/external-ingestion-deployment.md" /%}

## Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{% /inlineCallout %}



To access Fivetran APIs, a Fivetran account on a Standard, Enterprise, or Business Critical plan is required.

### Python Requirements

To run the Fivetran ingestion, you will need to install:

```bash
pip3 install "openmetadata-ingestion[fivetran]"
```

## Metadata Ingestion

All connectors are defined as JSON Schemas.
[Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/pipeline/fivetranConnection.json)
you can find the structure to create a connection to Fivetran.

In order to create and run a Metadata Ingestion workflow, we will follow
the steps to create a YAML configuration able to connect to the source,
process the Entities if needed, and reach the OpenMetadata server.

The workflow is modeled around the following
[JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)

### 1. Define the YAML Config

This is a sample config for Fivetran:

{% codePreview %}

{% codeInfoContainer %}

#### Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

**apiKey**: Fivetran API Key.

Follow the steps mentioned below to generate the Fivetran API key and API secret:
- Click your user name in your Fivetran dashboard.
- Click API Key.
- Click Generate API key. (If you already have an API key, then the button text is Generate new API key.)
- Make a note of the key and secret as they won't be displayed once you close the page or navigate away.

For more detailed documentation visit [here](https://fivetran.com/docs/rest-api/getting-started).

{% /codeInfo %}

{% codeInfo srNumber=2 %}

**apiSecret**: Fivetran API Secret.

From the above step where the API key is generated copy the the API secret

{% /codeInfo %}

{% codeInfo srNumber=3 %}

**hostPort**: HostPort of the Fivetran instance.

Hostport of the Fivetran instance that the connection will be made to
By default OpenMetadata will use `https://api.fivetran.com` to connect to the Fivetran APIs.

{% /codeInfo %}

{% codeInfo srNumber=4 %}

**limit**: Fivetran API Limit For Pagination.

This refers to the maximum number of records that can be returned in a single page of results when using Fivetran's API for pagination.

{% /codeInfo %}


#### Source Configuration - Source Config

{% codeInfo srNumber=5 %}

The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/pipelineServiceMetadataPipeline.json):

**dbServiceNames**: Database Service Name for the creation of lineage, if the source supports it.

**includeTags**: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.

**markDeletedPipelines**: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

**pipelineFilterPattern** and **chartFilterPattern**: Note that the `pipelineFilterPattern` and `chartFilterPattern` both support regex as include or exclude.

{% /codeInfo %}


#### Sink Configuration

{% codeInfo srNumber=6 %}

To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.

{% /codeInfo %}

{% partial file="/v1.1/connectors/workflow-config.md" /%}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

```yaml
source:
  type: fivetran
  serviceName: local_fivetran
  serviceConnection:
    config:
      type: Fivetran
```
```yaml {% srNumber=1 %}
      apiKey: <fivetran api key>
```
```yaml {% srNumber=2 %}
      apiSecret: <fivetran api secret>
```
```yaml {% srNumber=3 %}
      # hostPort: https://api.fivetran.com (default)
```
```yaml {% srNumber=4 %}
      # limit: 1000 (default)
```
```yaml {% srNumber=5 %}
  sourceConfig:
    config:
      type: PipelineMetadata
      # markDeletedPipelines: True
      # includeTags: True
      # includeLineage: true
      # pipelineFilterPattern:
      #   includes:
      #     - pipeline1
      #     - pipeline2
      #   excludes:
      #     - pipeline3
      #     - pipeline4
```
```yaml {% srNumber=6 %}
sink:
  type: metadata-rest
  config: {}
```

{% partial file="/v1.1/connectors/workflow-config-yaml.md" /%}

{% /codeBlock %}

{% /codePreview %}

### 2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

```bash
metadata ingest -c <path-to-yaml>
```

Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
you will be able to extract metadata from different sources.