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Run Redpanda Connector using the CLI | /connectors/messaging/redpanda/cli |
Run Redpanda using the metadata CLI
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
{%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 Redpanda ingestion, you will need to install:
pip3 install "openmetadata-ingestion[redpanda]"
Metadata Ingestion
All connectors are defined as JSON Schemas. Here 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
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 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.
{% /codeInfo %}
{% codeInfo srNumber=8 %}
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.
{% /codeInfo %}
Source Configuration - Source Config
{% codeInfo srNumber=9 %}
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.
{% /codeInfo %}
Sink Configuration
{% codeInfo srNumber=10 %}
To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest
.
{% /codeInfo %}
{% partial file="workflow-config.md" /%}
{% /codeInfoContainer %}
{% codeBlock fileName="filename.yaml" %}
source:
type: redpanda
serviceName: local_redpanda
serviceConnection:
config:
type: Redpanda
bootstrapServers: localhost:9092
schemaRegistryURL: http://localhost:8081 # Needs to be a URI
saslUsername: username
saslPassword: password
saslMechanism: PLAIN
basicAuthUserInfo: username:password
consumerConfig: {}
schemaRegistryConfig: {}
sourceConfig:
config:
type: MessagingMetadata
topicFilterPattern:
excludes:
- _confluent.*
# includes:
# - topic1
# generateSampleData: true
sink:
type: metadata-rest
config: {}
{% partial file="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:
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.