OpenMetadata/openmetadata-docs/content/connectors/dashboard/quicksight/cli.md

---
title: Run QuickSight Connector using the CLI
slug: /connectors/dashboard/quicksight/cli
---

# Run QuickSight using the metadata CLI

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

Configure and schedule QuickSight 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%}

AWS QuickSight Permissions
To execute metadata extraction and usage workflow successfully the IAM User should have enough access to fetch required data. Following table describes the minimum required permissions

| # | AWS QuickSight Permission |
| :---------- | :---------- |
| 1 | DescribeDashboard |
| 2 | ListAnalyses |
| 3 | ListDataSources |
| 4 | ListDashboards |
| 5 | DescribeAnalysis |
| 6 | DescribeDataSet |
| 7 | ListDataSets |
| 8 | DescribeDataSource |

Here is how to add Permissions to an IAM user.

- Navigate to the IAM console in the AWS Management Console.

- Choose the IAM user or group to which you want to attach the policy, and click on the "Permissions" tab.

- Click on the "Add permissions" button and select "Attach existing policies directly".

- Search for the policy by name or by filtering the available policies, and select the one you want to attach.

- Review the policy and click on "Add permissions" to complete the process.

```json
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "quicksight:DescribeDashboard",
                "quicksight:ListAnalyses",
                "quicksight:ListDataSources",
                "quicksight:ListDashboards",
                "quicksight:DescribeAnalysis",
                "quicksight:DescribeDataSet",
                "quicksight:ListDataSets",
                "quicksight:DescribeDataSource"
            ],
            "Resource": "*"
        }
    ]
}
```


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 QuickSight ingestion, you will need to install:

```bash
pip3 install "openmetadata-ingestion[quicksight]"
```

## 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/quickSightConnection.json)
you can find the structure to create a connection to QuickSight.

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 QuickSightled 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

This is a sample config for QuickSight:

```yaml
source:
  type: QuickSight
  serviceName: local_QuickSight
  serviceConnection:
    config:
      type: QuickSight
      awsConfig:
        awsAccessKeyId: key
        awsSecretAccessKey: secret
        awsRegion: ap-south-1
        awsSessionToken: token
      awsAccountId: account-id
      identityType: identityType
  sourceConfig:
    config:
      type: DashboardMetadata
      includeOwner: True
      markDeletedDashboards: True
      includeTags: True
      # dbServiceNames:
      #   - service1
      #   - service2
      # dashboardFilterPattern:
      #   includes:
      #     - dashboard1
      #     - dashboard2
      #   excludes:
      #     - dashboard3
      #     - dashboard4
      # chartFilterPattern:
      #   includes:
      #     - chart1
      #     - chart2
      #   excludes:
      #     - chart3
      #     - chart4
sink:
  type: metadata-rest
  config: {}
workflowConfig:
  # loggerLevel: DEBUG  # DEBUG, INFO, WARN or ERROR
  openMetadataServerConfig:
    hostPort: <OpenMetadata host and port>
    authProvider: <OpenMetadata auth provider>
```

#### Source Configuration - Service Connection

- **awsConfig**
  - **AWS Access Key ID**: Enter your secure access key ID for your Glue connection. The specified key ID should be authorized to read all databases you want to include in the metadata ingestion workflow.
  - **AWS Secret Access Key**: Enter the Secret Access Key (the passcode key pair to the key ID from above).
  - **AWS Region**: Enter the location of the amazon cluster that your data and account are associated with.
  - **AWS Session Token (optional)**: The AWS session token is an optional parameter. If you want, enter the details of your temporary session token.
  - **Endpoint URL (optional)**: Your Glue connector will automatically determine the AWS QuickSight endpoint URL based on the region. You may override this behavior by entering a value to the endpoint URL.

- **identityType**: The authentication method that the user uses to sign in.
- **awsAccountId**: QuickSight account ID is required to manage QuickSight users, data sources, and reports.
- **namespace**: The Amazon QuickSight namespace that contains the dashboard IDs in this request ( To be provided when identityType is `ANONYMOUS` )
#### Source Configuration - Source Config

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 all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
- `includeTags`: Set the 'Include Tags' toggle to control whether 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.

```yaml
dashboardFilterPattern:
  includes:
    - users
    - type_test
```

#### 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:

```yaml
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](https://github.com/open-metadata/OpenMetadata/tree/main/openmetadata-spec/src/main/resources/json/schema/security/client).
You can find the different implementation of the ingestion below.

<Collapse title="Configure SSO in the Ingestion Workflows">

### Openmetadata JWT Auth

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

### Auth0 SSO

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

### Azure SSO

```yaml
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

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

### Google SSO

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

### Okta SSO

```yaml
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](https://docs.open-metadata.org/deployment/security/enable-jwt-tokens)

```yaml
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

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

### KeyCloak SSO

Which uses Custom OIDC for the ingestion

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

</Collapse>


### 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 <path-to-yaml>
```

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.