Lightdash

PROD

Available In

Feature List

Dashboards

Charts

Owners

Datamodels

Lineage

How to Run the Connector Externally

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.

If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

External Schedulers

Get more information about running the Ingestion Framework Externally

Requirements

To integrate Lightdash, ensure you are using OpenMetadata version 1.2.x or higher.

Python Requirements

We have support for Python versions 3.9-3.11

To run the Lightdash ingestion, you will need to install:

Metadata Ingestion

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

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 Lightdash:

Source Configuration - Service Connection

Host and Port: Specify the network location where your Lightdash instance is accessible, combining both hostname and port in a URI format: either http://hostname:port or https://hostname:port, based on your security needs. Example: For a local setup, use http://localhost:8080; for a server deployment, it might be https://lightdash.example.com:3000. Ensure the specified port is open and accessible through network firewall settings.

API Key: This key authenticates requests to your Lightdash instance. Keep the API Key secure, sharing it only with authorized applications or users.

Project UUID: This unique identifier links API requests or configurations to a specific project in Lightdash.

Space UUID: Identifies a specific "Space" in Lightdash, used to organize dashboards, charts, and assets.

Proxy Authentication: If your Lightdash instance requires authentication through a proxy server, provide proxy credentials. Proxy authentication controls access to external resources and Lightdash.

Source Configuration - Source Config

The sourceConfig is defined here:

dbServiceNames: Database Service Names for ingesting lineage if the source supports it.
dashboardFilterPattern, chartFilterPattern, dataModelFilterPattern: Note that all of them support regex as include or exclude. E.g., "My dashboard, My dash.*, .*Dashboard".
projectFilterPattern: Filter the dashboards, charts and data sources by projects. Note that all of them support regex as include or exclude. E.g., "My project, My proj.*, .*Project".
includeOwners: Set the 'Include Owners' toggle to control whether to include owners to the ingested entity if the owner email matches with a user stored in the OM server as part of metadata ingestion. If the ingested entity already exists and has an owner, the owner will not be overwritten.
includeTags: Set the 'Include Tags' toggle to control whether to include tags in metadata ingestion.
includeDataModels: Set the 'Include Data Models' 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.
Include Draft Dashboard (toogle): Set the 'Include Draft Dashboard' toggle to include draft dashboards. By default it will include draft dashboards.
dataModelFilterPattern: Regex exclude or include data models that matches the pattern.
includeOwners:Enabling a flag will replace the current owner with a new owner from the source during metadata ingestion, if the current owner is null. It is recommended to keep the flag enabled to obtain the owner information during the first metadata ingestion.includeOwners supports boolean value either true or false.
markDeletedDashboards: Optional configuration to soft delete dashboards in OpenMetadata if the source dashboards are deleted. Also, if the dashboard is deleted, all the associated entities like lineage, etc., with that dashboard will be deleted.markDeletedDashboards supports boolean value either true or false.
markDeletedDataModels: Optional configuration to soft delete data models in OpenMetadata if the source data models are deleted. Also, if the data models is deleted, all the associated entities like lineage, etc., with that data models will be deleted.includeOwners supports boolean value either true or false.
includeTags:Optional configuration to toggle the tags ingestion.markDeletedDataModels supports boolean value either true or false.
includeDataModels: Optional configuration to toggle the ingestion of data models.includeDataModels supports boolean value either true or false.
includeDraftDashboard: Optional Configuration to include/exclude draft dashboards. By default it will include draft dashboards.includeDraftDashboard supports boolean value either true or false.
overrideMetadata: Set the 'Override Metadata' toggle to control whether to override the existing metadata in the OpenMetadata server with the metadata fetched from the source. If the toggle is set to true, the metadata fetched from the source will override the existing metadata in the OpenMetadata server. If the toggle is set to false, the metadata fetched from the source will not override the existing metadata in the OpenMetadata server. This is applicable for fields like description, tags, owner and displayName.overrideMetadata supports boolean value either true or false.
overrideLineage: Set the 'Override Lineage' toggle to control whether to override the existing lineage.overrideLineage supports boolean value either true or false.

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.

Logger Level

You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.

JWT Token

JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.

You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

Store Service Connection

If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.

If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.

SSL Configuration

If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.

Find more information on how to troubleshoot SSL issues here.

ingestionPipelineFQN

Fully qualified name of ingestion pipeline, used to identify the current ingestion pipeline.

filename.yaml

2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

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.