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75 lines
2.3 KiB
Markdown
75 lines
2.3 KiB
Markdown
---
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title: Custom OIDC SSO
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slug: /deployment/security/custom-oidc
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---
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# Custom OIDC SSO
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Follow the sections in this guide to set up Custom OIDC SSO.
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{% note %}
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Security requirements for your **production** environment:
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- **DELETE** the admin default account shipped by OM in case you had [Basic Authentication](/deployment/security/basic-auth)
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enabled before configuring the authentication with Custom OIDC SSO.
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- **UPDATE** the Private / Public keys used for the [JWT Tokens](/deployment/security/enable-jwt-tokens). The keys we provide
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by default are aimed only for quickstart and testing purposes. They should NEVER be used in a production installation.
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{% /note %}
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## Create Server Credentials
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- Go to the console of your preferred custom OIDC SSO provider
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- Create an OIDC client application with implicit flow enabled to get a client ID.
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### Create Client ID and Secret Key
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- Navigate to your preferred OIDC provider console and create an OIDC client application.
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- Generate client ID and secret key in JSON format.
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After the applying these steps, you can update the configuration of your deployment:
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{%inlineCalloutContainer%}
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{%inlineCallout
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icon="celebration"
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bold="Docker Security"
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href="/deployment/security/custom-oidc/docker" %}
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Configure Custom OIDC SSO for your Docker Deployment.
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{%/inlineCallout%}
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{%inlineCallout
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icon="storage"
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bold="Bare Metal Security"
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href="/deployment/security/custom-oidc/bare-metal" %}
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Configure Custom OIDC SSO for your Bare Metal Deployment.
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{%/inlineCallout%}
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{%inlineCallout
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icon="fit_screen"
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bold="Kubernetes Security"
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href="/deployment/security/custom-oidc/kubernetes" %}
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Configure Custom OIDC SSO for your Kubernetes Deployment.
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{%/inlineCallout%}
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{%/inlineCalloutContainer%}
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## Configure Ingestion
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After everything has been set up, you will need to configure your workflows if you are running them via the
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`metadata` CLI or with any custom scheduler.
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When setting up the YAML config for the connector, update the `workflowConfig` as follows:
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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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