zwitschi
1af654de1f
- Create .gitignore to exclude specific project files and directories. - Add CONTRIBUTING.md with guidelines for contributing to the project. - Update README.md to reflect changes in usage section and contact information. - Introduce 08_concepts.md outlining cross-cutting concepts in the architecture. - Add 02_data_model.md detailing the data model and relationships. - Implement 03_security.md to describe security measures and practices. - Establish 08_ui_design.md for user interface design principles. - Document quality requirements in 10_quality_requirements.md. - Identify risks and technical debts in 11_technical_risks.md. - Create a glossary in 12_glossary.md for project-specific terms. - Include about-arc42.md to explain the arc42 documentation template. - Define price calculation variables and formula in price_calculation.md. - Introduce ADR template in adr.md for documenting architecture decisions.
247 lines
9.8 KiB
Markdown
247 lines
9.8 KiB
Markdown
# Cross-cutting Concepts
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CalMiner aims to provide a comprehensive platform for mining project scenario analysis, enabling stakeholders to make informed decisions based on data-driven insights. This document outlines the key cross-cutting concepts that underpin the architecture of the CalMiner system.
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## Table of Contents
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- [Cross-cutting Concepts](#cross-cutting-concepts)
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- [Table of Contents](#table-of-contents)
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- [Multitenancy](#multitenancy)
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- [Mandators](#mandators)
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- [Data Isolation](#data-isolation)
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- [Configuration Management](#configuration-management)
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- [Data Model](#data-model)
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- [Security](#security)
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- [Authentication and Authorization](#authentication-and-authorization)
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- [Authentication](#authentication)
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- [Authorization](#authorization)
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- [Session Management](#session-management)
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- [Token Expiration](#token-expiration)
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- [Multi-Factor Authentication (MFA)](#multi-factor-authentication-mfa)
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- [Error Handling and Logging](#error-handling-and-logging)
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- [Centralized Logging](#centralized-logging)
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- [Error Categorization](#error-categorization)
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- [Graceful Degradation](#graceful-degradation)
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- [Alerting and Monitoring](#alerting-and-monitoring)
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- [Log Retention Policies](#log-retention-policies)
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- [Performance Optimization](#performance-optimization)
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- [Caching](#caching)
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- [Asynchronous Processing](#asynchronous-processing)
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- [Database Indexing](#database-indexing)
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- [Load Balancing](#load-balancing)
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- [Scalability Strategies](#scalability-strategies)
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- [Horizontal Scaling](#horizontal-scaling)
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- [Vertical Scaling](#vertical-scaling)
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- [Microservices Architecture](#microservices-architecture)
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- [Load Testing](#load-testing)
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- [User Interface Design Principles](#user-interface-design-principles)
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- [Notification System](#notification-system)
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- [Notification Channels](#notification-channels)
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- [Configurable Preferences](#configurable-preferences)
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- [Event Triggers](#event-triggers)
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- [Delivery Reliability](#delivery-reliability)
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- [Audit Trail](#audit-trail)
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- [Data Integration](#data-integration)
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- [API Integration](#api-integration)
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- [Data Ingestion](#data-ingestion)
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- [Data Transformation](#data-transformation)
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- [Data Synchronization](#data-synchronization)
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- [Error Handling](#error-handling)
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- [Reporting and Analytics](#reporting-and-analytics)
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- [Data Visualization](#data-visualization)
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- [Custom Reports](#custom-reports)
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- [Real-time Analytics](#real-time-analytics)
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- [Historical Analysis](#historical-analysis)
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## Multitenancy
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The Calminer system is designed to support multitenancy, allowing multiple independent users or organizations (tenants) to share the same application instance while maintaining data isolation and security.
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### Mandators
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Each tenant is represented by a Mandator entity, which encapsulates all data and configurations specific to that tenant.
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### Data Isolation
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The architecture ensures that data belonging to different tenants is isolated, preventing unauthorized access between tenants.
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### Configuration Management
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Each tenant can have customized settings and preferences, managed through the Mandator entity.
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## Data Model
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The system employs a relational data model to manage and store information efficiently. The primary entities include Users, Projects, Datasets, and Results. Each entity is represented as a table in the database, with relationships defined through foreign keys.
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A detailed [Data Model](08_concepts/02_data_model.md) documentation is available.
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All data interactions are handled through the [Data Access Layer](05_building_block_view.md#data-access-layer), ensuring consistency and integrity across operations.
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## Security
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The Calminer system incorporates robust security measures to protect sensitive data and ensure compliance with different industry and regulatory standards, such as GDPR or ISO/IEC 27001.
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Within the system, security is enforced through multiple layers, including data encryption, access controls, audit logging, vulnerability management, and compliance monitoring.
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A comprehensive [Security Concept](08_concepts/03_security.md) is being developed as well.
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## Authentication and Authorization
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The system utilizes a secure authentication mechanism to verify user identities and manage access to resources.
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### Authentication
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Users authenticate using secure methods, such as OAuth 2.0 or JWT tokens, to ensure the legitimacy of access requests.
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### Authorization
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Access to resources is controlled through role-based permissions, ensuring users can only access data and functionalities relevant to their roles.
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### Session Management
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User sessions are managed securely, with mechanisms in place to prevent session hijacking and ensure session integrity.
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### Token Expiration
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Access tokens have a limited lifespan and are refreshed periodically to enhance security.
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### Multi-Factor Authentication (MFA)
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The system supports MFA to provide an additional layer of security during user authentication.
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## Error Handling and Logging
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The system implements a comprehensive error handling and logging strategy to ensure reliability and facilitate troubleshooting.
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### Centralized Logging
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All application logs are centralized to a logging service, enabling efficient monitoring and analysis of system behavior.
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### Error Categorization
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Errors are categorized into different types (e.g., client errors, server errors) to facilitate targeted handling and resolution.
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### Graceful Degradation
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The system is designed to handle errors gracefully, providing meaningful feedback to users without exposing sensitive information.
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### Alerting and Monitoring
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The system includes mechanisms for alerting administrators about critical errors and monitoring system health.
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### Log Retention Policies
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Logs are retained for a specified period to comply with regulatory requirements and support forensic analysis.
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## Performance Optimization
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The system is designed with performance optimization strategies to ensure efficient operation and responsiveness.
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### Caching
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Frequently accessed data is cached to reduce database load and improve response times.
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### Asynchronous Processing
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Time-consuming operations are handled asynchronously to prevent blocking user interactions.
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### Database Indexing
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Appropriate indexing strategies are implemented to optimize query performance.
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### Load Balancing
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Traffic is distributed across multiple servers to ensure optimal resource utilization and minimize latency.
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## Scalability Strategies
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The system is architected to scale efficiently in response to varying workloads and user demands.
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### Horizontal Scaling
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The system can add more machines or instances to handle increased load, distributing traffic and processing across multiple nodes.
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### Vertical Scaling
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Individual components can be upgraded with more resources (CPU, memory) to improve performance without changing the overall architecture.
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### Microservices Architecture
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The system is designed as a collection of loosely coupled services, allowing for independent scaling of different components based on demand.
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### Load Testing
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Regular load testing is conducted to identify bottlenecks and ensure the system can handle expected traffic patterns.
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## User Interface Design Principles
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To ensure a consistent and user-friendly experience, the Calminer system adheres to established user interface design principles. A detailed [user interface (UI)](08_concepts/08_ui_design.md) design principles document is available for reference.
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## Notification System
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The system includes a notification mechanism to inform users about important events and updates.
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### Notification Channels
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The system supports multiple channels for notifications, including email, SMS, and in-app alerts.
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### Configurable Preferences
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Users can customize their notification preferences, selecting the types of notifications they wish to receive and the channels through which they are delivered.
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### Event Triggers
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Notifications are triggered by specific events within the system, such as project updates, data processing completions, or system alerts.
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### Delivery Reliability
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The notification system is designed to ensure reliable delivery of messages, with retry mechanisms in place for failed attempts.
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### Audit Trail
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A record of all sent notifications is maintained for auditing purposes and to track user engagement.
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## Data Integration
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The Calminer system is designed to integrate seamlessly with various external data sources and services.
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### API Integration
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The system can connect to external APIs to fetch or send data as needed.
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### Data Ingestion
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Mechanisms are in place to ingest data from various sources, including databases, file systems, and streaming platforms.
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### Data Transformation
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The system can transform data into the required format for processing and analysis.
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### Data Synchronization
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Regular synchronization processes ensure that data remains consistent across all integrated systems.
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### Error Handling
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Robust error handling mechanisms are implemented to manage integration failures and ensure data integrity.
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## Reporting and Analytics
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The Calminer system includes comprehensive reporting and analytics capabilities to support data-driven decision-making.
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### Data Visualization
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The system provides tools for visualizing data through charts, graphs, and dashboards, making it easier to identify trends and insights.
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### Custom Reports
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Users can create custom reports based on specific criteria, allowing for tailored analysis of project performance and resource utilization.
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### Real-time Analytics
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The system supports real-time data processing and analytics, enabling users to access up-to-date information and respond quickly to changing conditions.
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### Historical Analysis
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The system maintains a history of key metrics and events, allowing for retrospective analysis and identification of long-term trends.
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