LDAP Collector

The LDAP Collector is a Python application based on the ldap3, FastAPI and Uvicorn libraries.

It connects to an LDAP server, retrieves information of users, roles, groups and organizations and generates a JSON object which can be used later by Morph-KGC to generate RDF triples given the appropriate mappings file. An example of this JSON output is available here.

The YARRRML mappings file can be found here, whereas its RML equivalent is here. These mappings have been defined according to the aerOS Continuum Ontology, which diagram is included below:

The LDAP Collector is a neccesary component for integrating LDAP data into the knowledge graph.

The generation and retrieval of the JSON object is requested via a REST API method (HTTP GET /ldap.json) that the collector exposes. A sequence diagram that describes the working principle of the collector is included below:

Current versions:

• LDAP Collector application: 2.0.3 (August 5th, 2024).
• Dockerfile: 2.0.3 (August 5th, 2024).
• Kubernetes manifest file: 2.0.6 (August 5th, 2024).
• Helm Chart: 2.0.6 (August 5th, 2024).

Data Product Pipeline for LDAP

Building the Docker image

The collector is meant to be run as a Docker container, hence a Dockerfile is provided.

A pre-built image of the LDAP Collector is available. You can pull it using this command:

$ sudo docker pull ghcr.io/candil-data-fabric/ldap-collector:latest

If you prefer to build the image yourself, simply run the following command:

$ sudo docker build -t ldap-collector:latest .

NOTE: The collector will serve HTTP GET requests on port 63300 (TCP).

Running the collector

Configuration

The collector is configured using the following environmental variables:

Variable	Description	Default value
LDAP_ORGANIZATION_DN	LDAP DN of the organization to retieve information from.	"dc=example,dc=com"
LDAP_SERVER_ENDPOINT	URI where the LDAP server is listening from incoming connections or requests. FORMAT: ldap(s)://<ip_or_fqdn>:<port>. LDAP (unencrypted) port is 389. LDAPS (encrypted) port is 636.	"ldap://openldap:389"
LDAP_USE_SSL	Whether or not to use SSL for the connection with the server.	"\"False\""
LDAP_USER	LDAP DN of the user for connecting with the server and retrieving information.	"cn=admin,dc=example,dc=com"
LDAP_PASSWORD	Password of the user for connecting with the server and retrieving information.	"aeros"
LDAP_CONN_MAX_RETRIES	Maximum number of retries while trying to establish a connection with the LDAP server.	"5"
LDAP_CONN_TIMEOUT	Time (in seconds) to wait between retries while trying to establish a connection with the LDAP server.	"5"

Docker Compose

If you choose to deploy the collector using Docker Compose, you can define the service using the following directives:

ldap-collector:
    image: ghcr.io/candil-data-fabric/ldap-collector:latest
    hostname: ldap-collector
    container_name: ldap-collector
    ports:
        - "63300:63300"
    environment:
        - LDAP_ORGANIZATION_DN="dc=example,dc=com"
        - LDAP_SERVER_ENDPOINT="ldap://openldap:389"
        - LDAP_USE_SSL="False"
        - LDAP_USER="cn=admin,dc=example,dc=com"
        - LDAP_PASSWORD="aeros"
        - LDAP_CONN_MAX_RETRIES="5"
        - LDAP_CONN_TIMEOUT="5"

Kubernetes manifest file

Should you need to change the configuration, simply edit the values of the environmental variables defined in the manifest file.

To deploy the collector, run the following command at the ./kubernetes directory:

$ kubectl apply -f ldap-collector.yaml

To delete the deployment, run the following command, also at the ./kubernetes directory:

$ kubectl delete -f ldap-collector.yaml

Helm Chart

Should you need to change/override the configuration of the collector, use the values.yaml file as template to create your own and upgrade the Helm installation.

To install the Helm Chart, run the following command at the ./kubernetes directory:

$ helm install ldap-collector ./helm

To uninstall the Helm Chart, run the following command:

$ helm uninstall ldap-collector

Running the data product pipeline testbed

In the data-product-pipeline-testbed subdirectory you can find a Docker Compose scenario that defines a testbed with a data product pipeline for testing the LDAP Collector as well as the integration of LDAP data into the knowledge graph.

Go here to get instructions on how to run and interact with the testbed.