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* Fix: atlas test connection

* Fix: docs changes

* Fix: docs changes

* Fix: python checkstyle

* Fix: python test

2023-01-18 20:16:07 +05:30

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title	slug
Run Atlas Connector using the CLI	/connectors/metadata/atlas/cli

Run Atlas using the metadata CLI

In this section, we provide guides and references to use the Atlas connector.

Configure and schedule Atlas metadata and profiler workflows from the OpenMetadata UI:

Requirements
Metadata Ingestion

Requirements

Before this, you must ingest the database / messaging service you want to get metadata for. For more details click here

To deploy OpenMetadata, check the Deployment guides.

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 Atlas ingestion, you will need to install:

pip3 install "openmetadata-ingestion[atlas]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Atlas.

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 Atlas:

source:
  type: Atlas
  serviceName: local_atlas
  serviceConnection:
    config:
      type: Atlas
      hostPort: http://localhost:10000
      username: username
      password: password
      databaseServiceName: ["local_hive"] # pass database service here
      messagingServiceName: [] # pass messaging service here
      entity_type: Table # this entity must be present on atlas
  sourceConfig:
    config:
      type: DatabaseMetadata
sink: 
  type: metadata-rest
  config: {}
workflowConfig:
  openMetadataServerConfig:
    hostPort: "<OpenMetadata host and port>"
    authProvider: "<OpenMetadata auth provider>"

Source Configuration - Service Connection

Host and Port: Host and port of the Atlas service.
Username: username to connect to the Atlas. This user should have privileges to read all the metadata in Atlas.
Password: password to connect to the Atlas.
databaseServiceName: source database of the data source(Database service that you created from UI. example- local_hive)
messagingServiceName: messaging service source of the data source.
entity_type: Name of the entity type in Atlas.

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.

For a simple, local installation using our docker containers, this looks like:

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: openmetadata
    securityConfig:
      jwtToken: '{bot_jwt_token}'

We support different security providers. You can find their definitions here. You can find the different implementation of the ingestion below.

Openmetadata JWT Auth

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: openmetadata
    securityConfig:
      jwtToken: '{bot_jwt_token}'

Auth0 SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: auth0
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

Azure SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: azure
    securityConfig:
      clientSecret: '{your_client_secret}'
      authority: '{your_authority_url}'
      clientId: '{your_client_id}'
      scopes:
        - your_scopes

Custom OIDC SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

Google SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: google
    securityConfig:
      secretKey: '{path-to-json-creds}'

Okta SSO

workflowConfig:
  openMetadataServerConfig:
    hostPort: http://localhost:8585/api
    authProvider: okta
    securityConfig:
      clientId: "{CLIENT_ID - SPA APP}"
      orgURL: "{ISSUER_URL}/v1/token"
      privateKey: "{public/private keypair}"
      email: "{email}"
      scopes:
        - token

Amazon Cognito SSO

The ingestion can be configured by Enabling JWT Tokens

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: auth0
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

OneLogin SSO

Which uses Custom OIDC for the ingestion

workflowConfig:
  openMetadataServerConfig:
    hostPort: 'http://localhost:8585/api'
    authProvider: custom-oidc
    securityConfig:
      clientId: '{your_client_id}'
      secretKey: '{your_client_secret}'
      domain: '{your_domain}'

KeyCloak SSO