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* Fix: atlas test connection * Fix: docs changes * Fix: docs changes * Fix: python checkstyle * Fix: python test
247 lines
6.7 KiB
Markdown
247 lines
6.7 KiB
Markdown
---
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title: Run Atlas Connector using the CLI
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slug: /connectors/metadata/atlas/cli
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---
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# Run Atlas using the metadata CLI
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In this section, we provide guides and references to use the Atlas connector.
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Configure and schedule Atlas 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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## Requirements
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Before this, you must ingest the database / messaging service you want to get metadata for.
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For more details click [here](/connectors/metadata/atlas#create-database-service)
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<InlineCallout color="violet-70" icon="description" bold="OpenMetadata 0.13 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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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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### Python Requirements
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To run the Atlas ingestion, you will need to install:
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```bash
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pip3 install "openmetadata-ingestion[atlas]"
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```
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## Metadata Ingestion
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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/metadata/atlasConnection.json)
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you can find the structure to create a connection to Atlas.
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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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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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### 1. Define the YAML Config
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This is a sample config for Atlas:
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```yaml
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source:
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type: Atlas
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serviceName: local_atlas
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serviceConnection:
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config:
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type: Atlas
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hostPort: http://localhost:10000
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username: username
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password: password
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databaseServiceName: ["local_hive"] # pass database service here
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messagingServiceName: [] # pass messaging service here
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entity_type: Table # this entity must be present on atlas
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sourceConfig:
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config:
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type: DatabaseMetadata
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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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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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#### Source Configuration - Service Connection
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- **Host and Port**: Host and port of the Atlas service.
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- **Username**: username to connect to the Atlas. This user should have privileges to read all the metadata in Atlas.
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- **Password**: password to connect to the Atlas.
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- **databaseServiceName**: source database of the data source(Database service that you created from UI. example- local_hive)
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- **messagingServiceName**: messaging service source of the data source.
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- **entity_type**: Name of the entity type in Atlas.
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#### Sink Configuration
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To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
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#### Workflow Configuration
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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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For a simple, local installation using our docker containers, this looks like:
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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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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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<Collapse title="Configure SSO in the Ingestion Workflows">
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### Openmetadata JWT Auth
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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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### Auth0 SSO
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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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### Azure SSO
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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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### Custom OIDC SSO
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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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### Google SSO
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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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### Okta SSO
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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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### Amazon Cognito SSO
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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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```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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### OneLogin SSO
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Which uses Custom OIDC for the ingestion
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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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### KeyCloak SSO
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Which uses Custom OIDC for the ingestion
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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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</Collapse>
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### 2. Run with the CLI
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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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```bash
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metadata ingest -c <path-to-yaml>
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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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