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)
## Requirements
{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%}
To deploy OpenMetadata, check the Deployment guides.
{% /inlineCallout %}
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
custom Airflow plugins to handle the workflow deployment.
### Python Requirements
To run the Airflow ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[airflow]"
```
Note that this installs the same Airflow version that we ship in the Ingestion Container, which is
Airflow `2.3.3` from Release `0.12`.
The ingestion using Airflow version 2.3.3 as a source package has been tested against Airflow 2.3.3 and Airflow 2.2.5.
**Note:** we only support officially supported Airflow versions. You can check the version list [here](https://airflow.apache.org/docs/apache-airflow/stable/installation/supported-versions.html).
**connection**: Airflow metadata database connection. See
these [docs](https://airflow.apache.org/docs/apache-airflow/stable/howto/set-up-database.html)
for supported backends.
In terms of `connection` we support the following selections:
-`backend`: Should not be used from the UI. This is only applicable when ingesting Airflow metadata locally by running
the ingestion from a DAG. It will use the current Airflow SQLAlchemy connection to extract the data.
-`MySQL`, `Postgres`, `MSSQL` and `SQLite`: Pass the required credentials to reach out each of these services. We will
create a connection to the pointed database and read Airflow data from there.
**hostPort**: URL to the Airflow instance.
{% /codeInfo %}
{% codeInfo srNumber=1 %}
**numberOfStatus**: Number of status we want to look back to in every ingestion (e.g., Past executions from a DAG).
{% /codeInfo %}
{% codeInfo srNumber=1 %}
**connection**: Airflow metadata database connection. See
these [docs](https://airflow.apache.org/docs/apache-airflow/stable/howto/set-up-database.html)
for supported backends.
In terms of `connection` we support the following selections:
-`backend`: Should not be used from the UI. This is only applicable when ingesting Airflow metadata locally by running
the ingestion from a DAG. It will use the current Airflow SQLAlchemy connection to extract the data.
-`MySQL`, `Postgres`, `MSSQL` and `SQLite`: Pass the required credentials to reach out each of these services. We will
create a connection to the pointed database and read Airflow data from there.
{% /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.
**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`.