This microservice is based upon clm-core and extends the basic functionalities with additional features
This service is utilized for persisting xAPI statements from learners when they submit learning activities through a content provider. It routes the appropriate statements to the associated learning records stores based on group affiliations.
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MariaDB, set up locally. This service leverages a database (DB) as the cornerstone for storing documents persistently. To establish a connection with MariaDB, it is essential that the database is secured through username and password authentication. Therefore, in order to run this service it is required to create a database within the MariaDB and configure it with a username and password for access control
- MariaDB Installation: https://mariadb.com/kb/en/getting-installing-and-upgrading-mariadb/
- For setting up the password of a user: https://mariadb.com/kb/en/set-password/
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Node.js 20.x: https://nodejs.org/en/download
root
├── api-docs # Open API 3.0.0 definition as .yaml file documenting all routes and data models this service offers.
├── docs # Developer documentation of all functions, classes, interfaces, types this service exposes as an npm package.
├── dist # The built TypeScript project transpiled to JavaScript.
└── src # Business-relevant logic for this web server.
The Entity Relationship Model of the Open Core is shown above.
The clm-ext-tracedata module does not utilize resources on its own but leverages various resources from other modules to facilitate the saving and fetching of learning experiences of users.
Users (clm-core)
- The user is required to obtain their group memberships
Groups (clm-core)
- Group membership characteristics such as the roles associated with the group are integrated in the IMS-CC
ServiceProviders (clm-ext-service_providers)
- Necessary for retrieving the user-specific Learning Record Store (LRS) of the user, in order to determine which LRS the data should be saved to.
This service functions as a web microservice that can be orchestrated through a gateway and as an npm package to provide functionalities to other CLM extensions. A microservice can build upon the classes/types/interfaces of this service to extend basic functionalities.
- The service's configuration can be customized by referring to the
.envfile. Within this file, theMARIA_CONFIGvariable should be updated with the appropriate values to reflect the user's specific database settings. Refer to theMARIA_CONFIGvariable in the table below to see which comma seperated value refers to which respective database setting. - npm install
- Copy .env.default to .env and overwrite needed properties
Following table gives an overview of the settings you can change through the environment variables
| Name | Example | Required (Yes/No) | Description |
|---|---|---|---|
| PORT | 3003 | Yes | The port on which the service should be deployed. |
| DEPLOY_URL | HOST_PROTOCOL://HOST_ADDRESS:GATEWAY_PORT/api | Yes | The address where all microservices are to be orchestrated. A /api must be appended. |
| MARIA_CONFIG | `MARIA_HOST_ADDRESS | MARIA_PORT | MARIA_DATABASE |
3.1 npm run dev for development with nodemon
3.2 npm start for deployment
4. Subsequently, the JSON representation of the Open-API specification should be accessible at:
http://localhost:${PORT}/traceData/swagger
To access the API endpoints detailed in the Open-API specification, an API token is required. This token is generated during the initialization of the clm-core module. For further details, please consult the documentation at clm-core.
- Accessible routes for this microservice are available at
http://localhost:PORT/traceData/swaggerafter starting the service. - Ensure to set up a reverse proxy to route traffic to the respective microservices as shown in the table.
The changelog can be found in the CHANGELOG.md file.
Please see the file AUTHORS.md to get in touch with the authors of this project. We will be happy to answer your questions at {[email protected]}
The project is made available under the license in the file license.txt