OpenMetadata/openmetadata-docs/content/v1.2.x-SNAPSHOT/connectors/pipeline/airbyte/yaml.md

---
title: Run the Airbyte Connector Externally
slug: /connectors/pipeline/airbyte/yaml
---

# Run the Airbyte Connector Externally

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

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

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

{% partial file="/v1.2/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 %}



### Python Requirements

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

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

## 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/airbyteConnection.json)
you can find the structure to create a connection to Airbyte.

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 Airbyte:

{% codePreview %}

{% codeInfoContainer %}

#### Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

**hostPort**: Pipeline Service Management UI URL


{% /codeInfo %}


#### Source Configuration - Source Config

{% codeInfo srNumber=2 %}

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=3 %}

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

{% /codeInfo %}

{% partial file="/v1.2/connectors/workflow-config.md" /%}

{% /codeInfoContainer %}

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


```yaml
source:
  type: airbyte
  serviceName: airbyte_source
  serviceConnection:
    config:
      type: Airbyte
```
```yaml {% srNumber=1 %}
      hostPort: http://localhost:8000
```
```yaml {% srNumber=2 %}
  sourceConfig:
    config:
      type: PipelineMetadata
      # markDeletedPipelines: True
      # includeTags: True
      # includeLineage: true
      # pipelineFilterPattern:
      #   includes:
      #     - pipeline1
      #     - pipeline2
      #   excludes:
      #     - pipeline3
      #     - pipeline4
```
```yaml {% srNumber=3 %}
sink:
  type: metadata-rest
  config: {}
```

{% partial file="/v1.2/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.