--- title: Run Redash Connector using the CLI slug: /connectors/dashboard/redash/cli --- # Run Redash using the metadata CLI | Stage | PROD | |------------|------------------------------| | Dashboards | {% icon iconName="check" /%} | | Charts | {% icon iconName="check" /%} | | Owners | {% icon iconName="cross" /%} | | Tags | {% icon iconName="cross" /%} | | Lineage | {% icon iconName="check" /%} | In this section, we provide guides and references to use the Redash connector. Configure and schedule Redash metadata and profiler workflows from the OpenMetadata UI: - [Requirements](#requirements) - [Metadata Ingestion](#metadata-ingestion) ## 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 Redash ingestion, you will need to install: ```bash pip3 install "openmetadata-ingestion[redash]" ``` ## 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/dashboard/redashConnection.json) you can find the structure to create a connection to Redash. 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 {% codePreview %} {% codeInfoContainer %} #### Source Configuration - Service Connection {% codeInfo srNumber=1 %} **hostPort**: URL to the Redash instance. {% /codeInfo %} {% codeInfo srNumber=2 %} **username**: Specify the User to connect to Redash. It should have enough privileges to read all the metadata. {% /codeInfo %} {% codeInfo srNumber=3 %} **apiKey**: API key of the redash instance to access. {% /codeInfo %} {% codeInfo srNumber=4 %} **Redash Version**: (Default: 10.0.0) Redash version of your redash instance. Enter the numerical value from the [Redash Releases](https://github.com/getredash/redash/releases) page. {% /codeInfo %} #### Source Configuration - Source Config {% codeInfo srNumber=5 %} The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json): **dbServiceNames**: Database Service Name for the creation of lineage, if the source supports it. **dashboardFilterPattern**, **chartFilterPattern**: Note that the they support regex as include or exclude. E.g., **includeTags**: Set the Include tags toggle to control whether or not to include tags as part of metadata ingestion. **markDeletedDashboards**: Set the Mark Deleted Dashboards toggle to flag dashboards as soft-deleted if they are not present anymore in the source system. {% /codeInfo %} #### Sink Configuration {% codeInfo srNumber=6 %} To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`. {% /codeInfo %} #### Workflow Configuration {% codeInfo srNumber=7 %} 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: {% /codeInfo %} {% /codeInfoContainer %} {% codeBlock fileName="filename.yaml" %} ```yaml source: type: redash serviceName: local_redash serviceConnection: config: type: Redash ``` ```yaml {% srNumber=1 %} hostPort: http://localhost:5000 ``` ```yaml {% srNumber=2 %} username: random ``` ```yaml {% srNumber=3 %} apiKey: api_key ``` ```yaml {% srNumber=4 %} redashVersion: 10.0.0 ``` ```yaml {% srNumber=5 %} sourceConfig: config: type: DashboardMetadata # dbServiceNames: # - service1 # - service2 # dashboardFilterPattern: # includes: # - dashboard1 # - dashboard2 # excludes: # - dashboard3 # - dashboard4 # chartFilterPattern: # includes: # - chart1 # - chart2 # excludes: # - chart3 # - chart4 ``` ```yaml {% srNumber=6 %} sink: type: metadata-rest config: {} ``` ```yaml {% srNumber=7 %} workflowConfig: openMetadataServerConfig: hostPort: "http://localhost:8585/api" authProvider: openmetadata securityConfig: jwtToken: "{bot_jwt_token}" ``` {% /codeBlock %} {% /codePreview %} ### Workflow Configs for Security Provider We support different security providers. You can find their definitions [here](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client). ## Openmetadata JWT Auth - JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details [here](/deployment/security/enable-jwt-tokens). ```yaml workflowConfig: openMetadataServerConfig: hostPort: "http://localhost:8585/api" authProvider: openmetadata securityConfig: jwtToken: "{bot_jwt_token}" ``` - You can refer to the JWT Troubleshooting section [link](/deployment/security/jwt-troubleshooting) for any issues in your JWT configuration. If you need information on configuring the ingestion with other security providers in your bots, you can follow this doc [link](/deployment/security/workflow-config-auth). ### 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 ``` 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.