zwitschi
ad56c3c610
Add architecture documentation and functional requirements for Calminer project - Created Building Block View (05_building_block_view.md) detailing system architecture and component interactions. - Developed Runtime View (06_runtime_view.md) outlining key user scenarios and interactions within the system. - Established Deployment View (07_deployment_view.md) describing the infrastructure and mapping of building blocks to deployment components. - Added README.md for architecture documentation structure. - Introduced functional requirements (FR-001 to FR-010) covering scenario management, data import/export, reporting, user management, and collaboration features. - Included templates for documenting requirements to ensure consistency across the project.
3.7 KiB
Solution Strategy
Table of Contents
- Solution Strategy
Technology Decisions
Programming Language
Python as the primary programming language for its simplicity, readability, and extensive libraries that support rapid development and data analysis.
Web Framework
FastAPI as the web framework due to its high performance, ease of use, and support for asynchronous programming, which is essential for handling multiple concurrent requests efficiently.
Database
PostgreSQL as the database system for its robustness, scalability, and strong support for complex queries, which are necessary for managing the application's data effectively.
Frontend Technologies
Jinja2 for server-side templating to dynamically generate HTML pages, and Chart.js for data visualization to provide interactive charts and graphs for users.
Architectural Patterns
Layered Architecture
The system follows a layered architecture pattern, separating concerns into distinct layers: presentation, business logic, and data access. This separation enhances maintainability, scalability, and testability of the application.
Client-Server Pattern
The application is designed using the client-server pattern, where the client (frontend) interacts with the server (backend) through RESTful APIs. This separation allows for independent development and scaling of the client and server components.
Containerization
The application is containerized using Docker or podman to ensure consistency across different deployment environments, facilitate scalability, and simplify the deployment process.
Quality Goals Achievement
Comprehensive Scenario Analysis
The system employs efficient data processing algorithms and leverages PostgreSQL's capabilities to handle large datasets, enabling users to create and analyze multiple project scenarios effectively.
Data-Driven Decision Making
Stakeholders have access to real-time data and analytics to inform their decisions.
User-Friendly Interface
The platform is designed with an intuitive interface that requires minimal training for new users.
Security
Sensitive data is protected through robust security measures, including encryption and access controls.
Scalability
The system is designed to scale horizontally by adding more instances of services as needed. This is facilitated by the use of containerization and orchestration tools like Kubernetes, which manage the deployment and scaling of containerized applications.
Organizational Decisions
Development Process
The development team follows an Agile methodology, allowing for iterative development, continuous feedback, and adaptability to changing requirements. This approach enhances collaboration among team members and stakeholders, ensuring that the final product meets user needs effectively.