Run Kafka using the metadata CLI

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:

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.

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

pip3 install "openmetadata-ingestion[kafka]"

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Kafka.

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

This is a sample config for Kafka:

  type: kafka
  serviceName: local_kafka
      type: Kafka
      bootstrapServers: localhost:9092
      schemaRegistryURL: http://localhost:8081  # Needs to be a URI
      consumerConfig: {}
      schemaRegistryConfig: {}
          - _confluent.*
        # includes:
        #   - topic1
      generateSampleData: true
  type: metadata-rest
  config: {}
  # loggerLevel: DEBUG  # DEBUG, INFO, WARN or ERROR
    hostPort: http://localhost:8585/api
    authProvider: no-auth

Source Configuration - Service Connection

  • bootstrapServers: Kafka bootstrap servers. Add them in comma separated values ex: host1:9092,host2:9092.
  • schemaRegistryURL: Confluent Kafka Schema Registry URL. URI format.
  • consumerConfig: Confluent Kafka Consumer Config.
  • schemaRegistryConfig:Confluent Kafka Schema Registry Config.

Source Configuration - Source Config

The sourceConfig is defined here:

  • generateSampleData: Option to turn on/off generating sample data during metadata extraction.
  • topicFilterPattern: Note that the topicFilterPattern supports regex as include or exclude. E.g.,
    - users
    - type_test

Sink Configuration

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

Workflow Configuration

The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.

For a simple, local installation using our docker containers, this looks like:

    hostPort: http://localhost:8585/api
    authProvider: no-auth

We support different security providers. You can find their definitions here. You can find the different implementation of the ingestion below.

chevron_rightConfigure SSO in the Ingestion Workflows

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

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.

Still have questions?

You can take a look at our Q&A or reach out to us in Slack

Was this page helpful?

editSuggest edits