In this section, we provide guides and references to use the Mulesoft connector.
Configure and schedule Mulesoft metadata workflows from the Collate 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
Python Requirements
We have support for Python versions 3.9-3.11
To run the Mulesoft ingestion, you will need to install:
pip3 install "collate-ingestion[mulesoft]"
All connectors are defined as JSON Schemas.
Here
you can find the structure to create a connection to Mulesoft.
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 Collate server.
The workflow is modeled around the following
JSON Schema
1. Define the YAML Config
This is a sample config for Mulesoft:
Authentication Examples
Basic Authentication Configuration
source:
type: mulesoft
serviceName: mulesoft_anypoint
serviceConnection:
config:
type: Mulesoft
hostPort: https://anypoint.mulesoft.com
authentication:
username: [email protected]
password: your_secure_password
organizationId: abc123-def456-ghi789
OAuth 2.0 Connected App Configuration
source:
type: mulesoft
serviceName: mulesoft_anypoint
serviceConnection:
config:
type: Mulesoft
hostPort: https://anypoint.mulesoft.com
authentication:
clientId: your_connected_app_client_id
clientSecret: your_connected_app_client_secret
organizationId: abc123-def456-ghi789
environmentId: production-env-id
EU Cloud Configuration
source:
type: mulesoft
serviceName: mulesoft_eu
serviceConnection:
config:
type: Mulesoft
hostPort: https://eu1.anypoint.mulesoft.com
authentication:
username: [email protected]
password: your_secure_password
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.