Audit event generator

The Job utilizes the neo4j mutation data to generate AUDIT events for the Knowlg objects, following the Sunbird Telemetry specification. These AUDIT events are specifically structured and formatted to adhere to the telemetry standards defined by Sunbird.

By generating these AUDIT events, the Job creates a valuable data source that can be consumed by various data analytics jobs. These data analytics jobs leverage the AUDIT events to perform in-depth analysis, monitoring, and reporting on the activities and changes related to the Knowlg objects within the system.

The AUDIT events provide valuable insights into the life-cycle and modifications of Knowlg objects, enabling data analysts to track and understand user interactions, content updates, and other relevant events. This data-driven approach empowers data analytics teams to derive meaningful patterns, trends, and metrics, facilitating data-driven decision-making and continuous improvement of the Knowlg platform.

In summary, the Job leverages neo4j mutation data to generate AUDIT events that align with Sunbird Telemetry specifications. These events serve as a valuable data source for data analytics jobs, enabling detailed analysis and monitoring of Knowlg objects and supporting data-driven insights to enhance the platform's performance and user experience.

Code:

Configuration:

During the deployment process, the configuration for all knowledge-platform-jobs is sourced from the sunbird-learning-platform repository. On the other hand, for local setups, the configuration is taken from the respective job folders within the knowledge-platform-jobs repository.

Kafka Topic:

kafka {
      input.topic = "{{ env_name }}.learning.graph.events"
      groupId = "{{ env_name }}-audit-event-generator-group"
      output.topic = "{{ env_name }}.telemetry.raw"
}

Job configuration variables:

Sample Kafka event:

{
  "ets": 1649228985316,
  "channel": "01269878797503692810",
  "transactionData": {
    "properties": {
      "childNodes": {
        "ov": [
          "do_213509990427254784111670",
          "do_21351048342788505611737",
          "do_21351048359284736011739"
        ],
        "nv": [
          "do_213509990427254784111670",
          "do_21351048342788505611737",
          "do_21351048359284736011739",
          "do_2134250082225192961958"
        ]
      },
      "lastUpdatedOn": {
        "ov": "2022-04-06T07:09:14.653+0000",
        "nv": "2022-04-06T07:09:45.288+0000"
      },
      "versionKey": {
        "ov": "1649228954653",
        "nv": "1649228985288"
      }
    }
  },
  "mid": "1f33cab7-a8ba-4245-87cb-a11ab648d9c8",
  "label": "Timer Course",
  "nodeType": "DATA_NODE",
  "userId": "ANONYMOUS",
  "createdOn": "2022-04-06T07:09:45.316+0000",
  "objectType": "Collection",
  "nodeUniqueId": "do_21351048259398041611736",
  "requestId": null,
  "operationType": "UPDATE",
  "nodeGraphId": 1149046,
  "graphId": "domain"
}

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