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			271 lines
		
	
	
		
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			Markdown
		
	
	
	
	
	
			
		
		
	
	
			271 lines
		
	
	
		
			7.2 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
| ---
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| title: Run Metabase Connector using the CLI
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| slug: /connectors/dashboard/metabase/cli
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| ---
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| 
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| # Run Metabase using the metadata CLI
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| 
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| In this section, we provide guides and references to use the Metabase connector.
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| 
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| Configure and schedule Metabase metadata and profiler workflows from the OpenMetadata UI:
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| - [Requirements](#requirements)
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| - [Metadata Ingestion](#metadata-ingestion)
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| 
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| ## Requirements
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| 
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| <InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.12 or later" href="/deployment">
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| To deploy OpenMetadata, check the <a href="/deployment">Deployment</a> guides.
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| </InlineCallout>
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| 
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| To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with
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| custom Airflow plugins to handle the workflow deployment.
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| 
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| We have tested Metabase with Versions `0.42.4` and `0.43.4`.
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| 
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| ### Python Requirements
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| 
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| To run the Metabase ingestion, you will need to install:
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| 
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| ```bash
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| pip3 install "openmetadata-ingestion[metabase]"
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| ```
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| 
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| ## Metadata Ingestion
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| 
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| All connectors are defined as JSON Schemas.
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| [Here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/entity/services/connections/dashboard/metabaseConnection.json)
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| you can find the structure to create a connection to Metabase.
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| 
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| In order to create and run a Metadata Ingestion workflow, we will follow
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| the steps to create a YAML configuration able to connect to the source,
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| process the Entities if needed, and reach the OpenMetadata server.
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| 
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| The workflow is modeled around the following
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| [JSON Schema](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/workflow.json)
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| 
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| ### 1. Define the YAML Config
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| 
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| This is a sample config for Metabase:
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| 
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| ```yaml
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| source:
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|   type: metabase
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|   serviceName: <service name>
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|   serviceConnection:
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|     config:
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|       type: Metabase
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|       username: <username>
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|       password: <password>
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|       hostPort: <hostPort>
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|   sourceConfig:
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|     config:
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|       type: DashboardMetadata
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|       # dbServiceNames:
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|       #   - service1
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|       #   - service2
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|       # dashboardFilterPattern:
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|       #   includes:
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|       #     - dashboard1
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|       #     - dashboard2
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|       #   excludes:
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|       #     - dashboard3
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|       #     - dashboard4
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|       # chartFilterPattern:
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|       #   includes:
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|       #     - chart1
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|       #     - chart2
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|       #   excludes:
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|       #     - chart3
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|       #     - chart4
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| sink:
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|   type: metadata-rest
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|   config: {}
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| workflowConfig:
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|   # loggerLevel: DEBUG  # DEBUG, INFO, WARN or ERROR
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|   openMetadataServerConfig:
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|     hostPort: <OpenMetadata host and port>
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|     authProvider: <OpenMetadata auth provider>
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| ```
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| 
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| #### Source Configuration - Service Connection
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| 
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| - **hostPort**: URL to the Metabase instance.
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| - **username**: Specify the User to connect to Metabase. It should have enough privileges to read all the metadata.
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| - **password**: Password for Metabase.
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| 
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| #### Source Configuration - Source Config
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| 
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| The `sourceConfig` is defined [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/dashboardServiceMetadataPipeline.json):
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| 
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| - `dbServiceName`: Database Service Name for the creation of lineage, if the source supports it.
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| - `dashboardFilterPattern` and `chartFilterPattern`: Note that the `dashboardFilterPattern` and `chartFilterPattern` both support regex as include or exclude. E.g.,
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| 
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| ```yaml
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| dashboardFilterPattern:
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|   includes:
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|     - users
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|     - type_test
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| ```
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| 
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| #### Sink Configuration
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| 
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| To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
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| 
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| #### Workflow Configuration
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| 
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| The main property here is the `openMetadataServerConfig`, where you can define the host and security provider of your OpenMetadata installation.
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| 
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| For a simple, local installation using our docker containers, this looks like:
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: openmetadata
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|     securityConfig:
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|       jwtToken: '{bot_jwt_token}'
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| ```
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| 
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| 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).
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| You can find the different implementation of the ingestion below.
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| 
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| <Collapse title="Configure SSO in the Ingestion Workflows">
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| 
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| ### Openmetadata JWT Auth
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: openmetadata
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|     securityConfig:
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|       jwtToken: '{bot_jwt_token}'
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| ```
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| 
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| ### Auth0 SSO
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: auth0
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|     securityConfig:
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|       clientId: '{your_client_id}'
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|       secretKey: '{your_client_secret}'
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|       domain: '{your_domain}'
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| ```
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| 
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| ### Azure SSO
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: azure
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|     securityConfig:
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|       clientSecret: '{your_client_secret}'
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|       authority: '{your_authority_url}'
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|       clientId: '{your_client_id}'
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|       scopes:
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|         - your_scopes
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| ```
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| 
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| ### Custom OIDC SSO
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: custom-oidc
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|     securityConfig:
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|       clientId: '{your_client_id}'
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|       secretKey: '{your_client_secret}'
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|       domain: '{your_domain}'
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| ```
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| 
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| ### Google SSO
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: google
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|     securityConfig:
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|       secretKey: '{path-to-json-creds}'
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| ```
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| 
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| ### Okta SSO
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: http://localhost:8585/api
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|     authProvider: okta
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|     securityConfig:
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|       clientId: "{CLIENT_ID - SPA APP}"
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|       orgURL: "{ISSUER_URL}/v1/token"
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|       privateKey: "{public/private keypair}"
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|       email: "{email}"
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|       scopes:
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|         - token
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| ```
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| 
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| ### Amazon Cognito SSO
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| 
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| The ingestion can be configured by [Enabling JWT Tokens](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens)
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: auth0
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|     securityConfig:
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|       clientId: '{your_client_id}'
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|       secretKey: '{your_client_secret}'
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|       domain: '{your_domain}'
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| ```
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| 
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| ### OneLogin SSO
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| 
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| Which uses Custom OIDC for the ingestion
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: custom-oidc
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|     securityConfig:
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|       clientId: '{your_client_id}'
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|       secretKey: '{your_client_secret}'
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|       domain: '{your_domain}'
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| ```
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| 
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| ### KeyCloak SSO
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| 
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| Which uses Custom OIDC for the ingestion
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| 
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| ```yaml
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| workflowConfig:
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|   openMetadataServerConfig:
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|     hostPort: 'http://localhost:8585/api'
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|     authProvider: custom-oidc
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|     securityConfig:
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|       clientId: '{your_client_id}'
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|       secretKey: '{your_client_secret}'
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|       domain: '{your_domain}'
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| ```
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| 
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| </Collapse>
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| 
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| 
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| ### 2. Run with the CLI
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| 
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| First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
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| 
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| ```bash
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| metadata ingest -c <path-to-yaml>
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| ```
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| 
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| Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration,
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| you will be able to extract metadata from different sources.
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