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---
title: Run the Redpanda Connector Externally
slug: /connectors/messaging/redpanda/yaml
---
# Run the Redpanda Connector Externally
In this section, we provide guides and references to use the Redpanda connector.
Configure and schedule Redpanda metadata and profiler workflows from the OpenMetadata UI:
- [Requirements](#requirements)
- [Metadata Ingestion](#metadata-ingestion)
{% partial file="/v1.1.2/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 Redpanda ingestion, you will need to install:
```bash
pip3 install "openmetadata-ingestion[redpanda]"
```
## 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/messaging/redpandaConnection.json)
you can find the structure to create a connection to Redpanda.
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 Redpanda:
{% codePreview %}
{% codeInfoContainer %}
#### Source Configuration - Service Connection
{% codeInfo srNumber=1 %}
**bootstrapServers**: List of brokers as comma separated values of broker `host` or `host:port`.
Example: `host1:9092,host2:9092`
{% /codeInfo %}
{% codeInfo srNumber=2 %}
**schemaRegistryURL**: URL of the Schema Registry used to ingest the schemas of the topics.
**NOTE**: For now, the schema will be the last version found for the schema name `{topic-name}-value`. An [issue](https://github.com/open-metadata/OpenMetadata/issues/10399) to improve how it currently works has been opened.
{% /codeInfo %}
{% codeInfo srNumber=3 %}
**saslUsername**: SASL username for use with the PLAIN and SASL-SCRAM mechanisms.
{% /codeInfo %}
{% codeInfo srNumber=4 %}
**saslPassword**: SASL password for use with the PLAIN and SASL-SCRAM mechanisms.
{% /codeInfo %}
{% codeInfo srNumber=5 %}
**saslMechanism**: SASL mechanism to use for authentication.
Supported: _GSSAPI, PLAIN, SCRAM-SHA-256, SCRAM-SHA-512, OAUTHBEARER_.
**NOTE**: Despite the name only one mechanism must be configured.
{% /codeInfo %}
{% codeInfo srNumber=6 %}
**basicAuthUserInfo**: Schema Registry Client HTTP credentials in the form of `username:password`.
By default, user info is extracted from the URL if present.
{% /codeInfo %}
{% codeInfo srNumber=7 %}
**consumerConfig**: The accepted additional values for the consumer configuration can be found in the following
[link](https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md).
{% /codeInfo %}
{% codeInfo srNumber=8 %}
**schemaRegistryConfig**: The accepted additional values for the Schema Registry configuration can be found in the
following [link](https://docs.confluent.io/5.5.1/clients/confluent-kafka-python/index.html#confluent_kafka.schema_registry.SchemaRegistryClient).
**Note:** To ingest the topic schema, `schemaRegistryURL` must be passed.
{% /codeInfo %}
#### Source Configuration - Source Config
{% codeInfo srNumber=9 %}
The sourceConfig is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/messagingServiceMetadataPipeline.json):
**generateSampleData:** Option to turn on/off generating sample data during metadata extraction.
**topicFilterPattern:** Note that the `topicFilterPattern` supports regex as include or exclude.
{% /codeInfo %}
#### Sink Configuration
{% codeInfo srNumber=10 %}
To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
{% /codeInfo %}
{% partial file="/v1.1.2/connectors/workflow-config.md" /%}
{% /codeInfoContainer %}
{% codeBlock fileName="filename.yaml" %}
```yaml
source:
type: redpanda
serviceName: local_redpanda
serviceConnection:
config:
type: Redpanda
```
```yaml {% srNumber=1 %}
bootstrapServers: localhost:9092
```
```yaml {% srNumber=2 %}
schemaRegistryURL: http://localhost:8081 # Needs to be a URI
```
```yaml {% srNumber=3 %}
saslUsername: username
```
```yaml {% srNumber=4 %}
saslPassword: password
```
```yaml {% srNumber=5 %}
saslMechanism: PLAIN
```
```yaml {% srNumber=6 %}
basicAuthUserInfo: username:password
```
```yaml {% srNumber=7 %}
consumerConfig: {}
```
```yaml {% srNumber=8 %}
schemaRegistryConfig: {}
```
```yaml {% srNumber=9 %}
sourceConfig:
config:
type: MessagingMetadata
topicFilterPattern:
excludes:
- _confluent.*
# includes:
# - topic1
# generateSampleData: true
```
```yaml {% srNumber=10 %}
sink:
type: metadata-rest
config: {}
```
{% partial file="/v1.1.2/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.