In this section, we provide guides and references to use the Salesforce connector.
Configure and schedule Salesforce metadata and profiler workflows from the OpenMetadata UI:
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.
Requirements
Following are the permissions you will require to fetch the metadata from Salesforce.
API Access: You must have the API Enabled permission in your Salesforce organization.
Object Permissions: You must have read access to the Salesforce objects that you want to ingest.
Python Requirements
We have support for Python versions 3.9-3.11
To run the Salesforce ingestion, you will need to install:
pip3 install "openmetadata-ingestion[salesforce]"
All connectors are defined as JSON Schemas.
Here
you can find the structure to create a connection to Salesforce.
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 Salesforce:
2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
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.
To establish secure connections between OpenMetadata and Salesforce, navigate to the Advanced Config section. Here, you can provide the CA certificate used for SSL validation by specifying the caCertificate. Alternatively, if both client and server require mutual authentication, you’ll need to use all three parameters: ssl_key, ssl_cert, and ssl_ca. In this case, ssl_cert is used for the client’s SSL certificate, ssl_key for the private key associated with the SSL certificate, and ssl_ca for the CA certificate to validate the server’s certificate.
sslConfig:
caCertificate: "/path/to/ca_certificate"
sslCertificate: "/path/to/your/ssl_cert"
sslKey: "/path/to/your/ssl_key"