The ML Survey Service is constructed using MongoDB, Kafka, and cloud storage technologies. Additionally, it seamlessly collaborates with vital services like ML Project Service, ML Core Service, and Learner Services. This Microservice comprises ten pivotal Modules, each playing a crucial role.
In charge of acquiring data for reports.
Tasked with creating surveys using solutions and templates.
Handles the submission of surveys and sends data to Kafka for analytical purposes.
Responsible for validating assessments of criteria and questions in observations and surveys.
Offers available solutions within the Manage Learn system.
Generates observations from solutions for users engaged in observations.
Manages the submission of observations and forwards data to Kafka for analytical purposes.
This module will be used by observations that involve rubric-based scoring.
Storing user details and program-related information for program designers and managers.
Supplies a list of available programs within Manage Learn.
These ten modules synergize as the backbone of the ML Survey Service, empowering users to enhance and optimize Observation and Survey capabilities within the broader SunbirdEd ecosystem on the App platform.