1a. Architecture Map: Full
Trucast Architecture Roadmap
Figure 1a:
This diagram illustrates the planned architecture for the Trucast system, showcasing key components and their interactions across different layers of the system.
Exhibit Summary: Trucast Architecture Roadmap
This architectural roadmap outlines the planned structure of the Trucast system, highlighting its key components and their interactions. The architecture is divided into four main sections:
Trucast Context Engine: This user-facing layer includes components for Use Case Templates, Workflow API Deployment, Knowledge Graph Creation, Query Enhancement, and AI-Ready Templates. It serves as the primary interface for users to interact with the system.
Trucast Schema Library: The core of Trucast's functionality, comprising the Use Case Registry, Manifest Templates, Actor-Action Workflows, Schema Validators, and Unique ID Registry. This layer manages the system's schema and workflow definitions.
Data Processing: Handles data-related operations through Smart Schema Selection and Data Retrieval & Validation components, ensuring data integrity and proper schema application.
Integration Layer: Facilitates external integrations and data transformations using OpenAPI Interface, Pydantic Models, Kafka Schema Registry, and Avro Schemas.
additional notes
The system utilizes a PostgreSQL database to store Data Models, Knowledge Graphs, and Use Case Manifests.
Key planned workflows include:
User template selection and API deployment, knowledge graph building and query enhancement, schema validation and data retrieval, and data transformation and schema registration.
The architecture prioritizes logical schemas powered by Pydantic models, OpenAPI-based deployment with unique IDs, and flexible knowledge graph creation from pre-configured or custom templates.
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