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.
6.5 KiB
Architecture Constraints
Table of Contents
- Architecture Constraints
Technical Constraints
Framework Selection
The choice of FastAPI as the web framework imposes constraints on how the application handles requests, routing, and middleware. FastAPI's asynchronous capabilities must be leveraged appropriately to ensure optimal performance.
Database Technology
The use of PostgreSQL as the primary database system dictates the data modeling, querying capabilities, and transaction management strategies. SQLAlchemy ORM is used for database interactions, which requires adherence to its conventions and limitations.
Frontend Technologies
The decision to use Jinja2 for server-side templating and Chart.js for data visualization influences the structure of the frontend code and the way dynamic content is rendered.
Simulation Logic
The Monte Carlo simulation logic must be designed to efficiently handle large datasets and perform computations within the constraints of the chosen programming language (Python) and its libraries.
Organizational and Political Constraints
Team Expertise
The development team's familiarity with FastAPI, SQLAlchemy, and frontend technologies like Jinja2 and Chart.js influences the architecture choices to ensure maintainability and ease of development.
Development Processes
The adoption of Agile methodologies and CI/CD pipelines (using Gitea Actions) shapes the architecture to support continuous integration, automated testing, and deployment practices.
Collaboration Tools
The use of specific collaboration and version control tools (e.g., Gitea) affects how code is managed, reviewed, and integrated, impacting the overall architecture and development workflow.
Documentation Standards
The requirement for comprehensive documentation (as seen in the docs/ folder) necessitates an architecture that is well-structured and easy to understand for both current and future team members.
Knowledge Sharing
The need for effective knowledge sharing and onboarding processes influences the architecture to ensure that it is accessible and understandable for new team members.
Resource Availability
The availability of hardware, software, and human resources within the organization can impose constraints on the architecture, affecting decisions related to scalability, performance, and feature implementation.
Regulatory Constraints
Data Privacy Compliance
The architecture must ensure compliance with data privacy regulations such as GDPR or CCPA, which may dictate how user data is collected, stored, and processed.
Industry Standards
Adherence to industry-specific standards and best practices may influence the design of data models, security measures, and reporting functionalities.
Auditability
The system may need to incorporate logging and auditing features to meet regulatory requirements, affecting the architecture of data storage and access controls.
Data Retention Policies
Regulatory requirements regarding data retention and deletion may impose constraints on how long certain types of data can be stored, influencing database design and data lifecycle management.
Security Standards
Compliance with security standards (e.g., ISO/IEC 27001) may necessitate the implementation of specific security measures, such as encryption, access controls, and vulnerability management, which impact the overall architecture.
Environmental Constraints
Deployment Environments
The architecture must accommodate various deployment environments (development, testing, production) with differing configurations and resource allocations.
Cloud Provider Limitations
If deployed on a specific cloud provider, the architecture may need to align with the provider's services, limitations, and best practices, such as using managed databases or specific container orchestration tools.
Containerization
The use of Docker for containerization imposes constraints on how the application is packaged, deployed, and scaled, influencing the architecture to ensure compatibility with container orchestration platforms.
Scalability Requirements
The architecture must be designed to scale efficiently based on anticipated load and usage patterns, considering the limitations of the chosen infrastructure.
Performance Constraints
Response Time
The system must ensure that user interactions, such as data retrieval and report generation, occur within acceptable time frames to maintain a positive user experience.
Scalability Needs
The architecture should support scaling to accommodate varying workloads, ensuring consistent performance during peak usage periods without significant degradation.
Conventions
Programming Language
The system is developed using Python, and all code must adhere to PEP 8 style guidelines to ensure consistency and readability across the codebase.
Versioning
Semantic Versioning (SemVer) is used for all releases to clearly communicate changes and compatibility.