> ## Documentation Index
> Fetch the complete documentation index at: https://docs.open-metadata.org/llms.txt
> Use this file to discover all available pages before exploring further.
# Kafka Connector | OpenMetadata Messaging Integration
> Connect Kafka to OpenMetadata effortlessly with our comprehensive connector guide. Set up messaging metadata ingestion, configuration, and monitoring in minutes.
export const MetadataIngestionUi = ({connector, selectServicePath, addNewServicePath, serviceConnectionPath}) => {
return <>
To ingest metadata from your sources, you need to create a service connection.
The service connects your source system with OpenMetadata. Once you create
a service, you can use it to configure your ingestion workflows.
To create a service connection and ingest your metadata, follow the steps below:
-
On the left navigation bar, click Settings.
-
On the next page, click Services, and then select the service.
To add a new service connection, click Add New Service.
Select {connector} as the service type and click Next.
{selectServicePath && 
}
Enter a unique Service Name and Description.
- Service Name: OpenMetadata identifies services by their service name. Enter a name that distinguishes this deployment from other services, including other {connector} services you are ingesting metadata from.
The service name cannot be changed after it is set.
{addNewServicePath && 
}
Set up the connection settings required for {connector} to set up the service and start ingesting metadata from your sources. The right-hand panel displays help documentation for the selected connection type in the product UI.
{serviceConnectionPath && 
}
;
};
export const ConnectorDetailsHeader = ({name, icon, stage, availableFeatures, unavailableFeatures = [], availableFeaturesCollate = []}) => {
const showSubHeading = availableFeatures?.length > 0 || unavailableFeatures?.length > 0 || availableFeaturesCollate?.length > 0;
const totalAvailableFeatures = [...availableFeatures || [], ...availableFeaturesCollate || []];
return
{icon &&
}
{name}
{stage}
{showSubHeading &&
Feature List
{totalAvailableFeatures.map(feature =>
✓ {feature}
)}
{unavailableFeatures.map(feature =>
✕ {feature}
)}
}
;
};
In this section, we provide guides and references to use the Kafka connector.
Configure and schedule Kafka metadata and profiler workflows from the OpenMetadata UI:
* [Requirements](#requirements)
* [Metadata Ingestion](#metadata-ingestion)
* [Enable Security](#securing-kafka-connection-with-ssl-in-openmetadata)
* [Troubleshooting](/v1.12.x/connectors/messaging/kafka/troubleshooting)
## Requirements
Connecting to Kafka does not require any previous configuration.
The ingestion of the Kafka topics' schema is done separately by configuring the **Schema Registry URL**. However, only the **Bootstrap Servers** information is mandatory. Below are the required Permissions for fetching the Metadata:-
* READ TOPIC
* DESCTIBE TOPIC
* READ CLUSTER
## Metadata Ingestion
# Connection Details
When using a **Hybrid Ingestion Runner**, any sensitive credential fields—such as passwords, API keys, or private keys—must reference secrets using the following format:
```
password: secret:/my/database/password
```
This applies **only to fields marked as secrets** in the connection form (these typically mask input and show a visibility toggle icon).
For a complete guide on managing secrets in hybrid setups, see the [Hybrid Ingestion Runner Secret Management Guide](https://docs.getcollate.io/getting-started/day-1/hybrid-saas/hybrid-ingestion-runner#3.-manage-secrets-securely).
* **Bootstrap Servers**: List of brokers as comma separated values of broker `host` or `host:port`. Example: `host1:9092,host2:9092`
* **Schema Registry URL**: URL of the Schema Registry used to ingest the schemas of the topics.
* **SASL Username**: SASL username for use with the PLAIN and SASL-SCRAM mechanisms.
* **SASL Password**: SASL password for use with the PLAIN and SASL-SCRAM mechanisms.
* **SASL Mechanism**: SASL mechanism to use for authentication.
* **Basic Auth User Info**: Schema Registry Client HTTP credentials in the form of `username:password`. By default, user info is extracted from the URL if present.
* **Consumer Config**: The accepted additional values for the consumer configuration can be found in the following [link](https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.mdx).
If you are using Confluent kafka and SSL encryption is enabled you need to add `security.protocol` as key and `SASL_SSL` as value under Consumer Config
* **Schema Registry Config**: The accepted additional values for the Schema Registry configuration can be found in the following [link](https://docs.confluent.io/platform/current/clients/confluent-kafka-python/html/index.html#schemaregistryclient).
To ingest the topic schema `Schema Registry URL` must be passed
Once the credentials have been added, click on *Test Connection* and *Save* the changes.
In this step we will configure the metadata ingestion pipeline,
Please follow the instructions below
#### Metadata Ingestion Options
* **Name**: This field refers to the name of ingestion pipeline, you can customize the name or use the generated name.
* **Topic Filter Pattern (Optional)**: Use it to control whether to include topics as part of metadata ingestion.
* **Include**: Explicitly include topics by adding a list of comma-separated regular expressions to the 'Include' field. OpenMetadata will include all topics with names matching one or more of the supplied regular expressions. All other topics will be excluded.
* **Exclude**: Explicitly exclude topics by adding a list of comma-separated regular expressions to the 'Exclude' field. OpenMetadata will exclude all topics with names matching one or more of the supplied regular expressions. All other topics will be included.
* **Ingest Sample Data (toggle)**: Set the 'Ingest Sample Data' toggle to ingest sample data from the topics.
* **Enable Debug Log (toggle)**: Set the 'Enable Debug Log' toggle to set the default log level to debug.
* **Mark Deleted Topics (toggle):** Set the 'Mark Deleted Topics' toggle to flag topics as soft-deleted if they are not present anymore in the source system.
* **Extract Consumer Groups (toggle):** Set the 'Extract Consumer Groups' toggle to extract active consumer group metadata for each topic, including group state, members, and partition assignments.
Scheduling can be set up at an hourly, daily, weekly, or manual cadence. The
timezone is in UTC. Select a Start Date to schedule for ingestion. It is
optional to add an End Date.
Review your configuration settings. If they match what you intended,
click Deploy to create the service and schedule metadata ingestion.
If something doesn't look right, click the Back button to return to the
appropriate step and change the settings as needed.
After configuring the workflow, you can click on Deploy to create the
pipeline.
Once the workflow has been successfully deployed, you can view the
Ingestion Pipeline running from the Service Page.
If AutoPilot is enabled, workflows like usage tracking, data lineage, and similar tasks will be handled automatically. Users don’t need to set up or manage them - AutoPilot takes care of everything in the system.
## Securing Kafka Connection with SSL in OpenMetadata
To establish secure connections between OpenMetadata and Kafka, navigate to the `Advanced Config` section. Here, you can provide the CA certificate used for SSL validation by specifying the `caCertificate`. Alternatively, if both client and server require mutual authentication, you'll need to use all three parameters: `ssl key`, `ssl cert`, and `caCertificate`. In this case, `ssl_cert` is used for the client’s SSL certificate, `ssl_key` for the private key associated with the SSL certificate, and `caCertificate` for the CA certificate to validate the server’s certificate.
