> For the complete documentation index, see [llms.txt](https://ed.sunbird.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ed.sunbird.org/use/source-code/manage-learn/ml-core-service/component-diagram.md). # Component Diagram

ML Core Service Component Diagram

The ML Core Service is constructed using a MongoDB, Kafka, and cloud storage technologies. Additionally, it seamlessly collaborates with vital services like [ML Project Service](/use/source-code/manage-learn/ml-project-service.md), [ML Survey Service](/use/source-code/manage-learn/ml-survey-service.md), and [Learner Services](https://lern.sunbird.org/learn/readme). This Microservice is composed of ten pivotal Modules, each playing a crucial role. #### User Role This module stores essential user role information. #### Cloud Service It facilitates communication between ML Core and the Cloud Service for data storage and retrieval. #### Admin Providing administrative services within the Manage Learn Building block. #### Users Serving user-centric functions, including targeted programs and resources. #### Solution Responsible for solution creation and management. #### Certificate Base Templates Creating foundational certificate templates used by certificate templates and providing certificate URLs. #### Certificate Template Mapping certificates with solutions and associated criteria. #### Program Users Managing user enrollment and consent statuses. #### Program: Creating and managing programs. #### User Extension Storing user details and program-related information for program designers and managers. These ten modules synergize as the backbone of the [ML Core Service](/use/source-code/manage-learn/ml-core-service.md), empowering users to enhance and optimize program capabilities within the broader SunbirdEd ecosystem on the App platform. #### Video on ML core services {% embed url="" %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://ed.sunbird.org/use/source-code/manage-learn/ml-core-service/component-diagram.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.