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:
How to Run the Connector Externally
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.
If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.
Requirements
Python Requirements
We have support for Python versions 3.8-3.11
To run the Kafka ingestion, you will need to install:
Metadata Ingestion
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
1. Define the YAML Config
This is a sample config for Kafka:
Source Configuration - Service Connection
bootstrapServers: List of brokers as comma separated values of broker host or host:port.
Example: host1:9092,host2:9092
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 to improve how it currently works has been opened.
saslUsername: SASL username for use with the PLAIN and SASL-SCRAM mechanisms.
saslPassword: SASL password for use with the PLAIN and SASL-SCRAM mechanisms.
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.
basicAuthUserInfo: Schema Registry Client HTTP credentials in the form of username:password.
By default, user info is extracted from the URL if present.
consumerConfig: The accepted additional values for the consumer configuration can be found in the following link.
schemaRegistryConfig: The accepted additional values for the Schema Registry configuration can be found in the following link.
Note: To ingest the topic schema, schemaRegistryURL must be passed.
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.
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.
Logger Level
You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.
JWT Token
JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.
You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
SSL Configuration
If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.
Find more information on how to troubleshoot SSL issues here.
Securing Kafka Connection with SSL in OpenMetadata
To establish secure connections between OpenMetadata and Kafka, in the YAML 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.
2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
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.