
Epic FHIR
BETAIn this section, we provide guides and references to use the Epic FHIR connector.
Configure and schedule Epic metadata workflows from the OpenMetadata UI:
Ingestion Deployment
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 you want to install it manually in an already existing Airflow host, you can follow this guide.
If you don't want to use the OpenMetadata Ingestion container to configure the workflows via the UI, then you can check the following docs to run the Ingestion Framework in any orchestrator externally.
Run Connectors from the OpenMetadata UI
Learn how to manage your deployment to run connectors from the UIRun the Connector Externally
Get the YAML to run the ingestion externallyExternal Schedulers
Get more information about running the Ingestion Framework ExternallyHow 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
To run the Epic ingestion, install the Python package:
Metadata Ingestion
All connectors are defined as JSON Schemas.
Here you can find the structure to create a connection to Epic.
The ingestion workflow itself follows the general workflow schema.
1. Define the YAML Config
This is a minimal sample config for Epic:
Source Configuration - Service Connection
fhirServerUrl: Base URL of the Epic FHIR server.
fhirVersion: FHIR specification version supported (R4
, STU3
, or DSTU2
).
databaseName: Optional name for the database in OpenMetadata. Defaults to epic
.
schemaFilterPattern / tableFilterPattern: Regex filters to limit which FHIR resource categories (schemas) or resource types (tables) are ingested.
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.