# Cross-cutting Concepts 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. ## Table of Contents - [Cross-cutting Concepts](#cross-cutting-concepts) - [Table of Contents](#table-of-contents) - [Multitenancy](#multitenancy) - [Mandators](#mandators) - [Data Isolation](#data-isolation) - [Configuration Management](#configuration-management) - [Data Model](#data-model) - [Security](#security) - [Authentication and Authorization](#authentication-and-authorization) - [Authentication](#authentication) - [Authorization](#authorization) - [Session Management](#session-management) - [Token Expiration](#token-expiration) - [Multi-Factor Authentication (MFA)](#multi-factor-authentication-mfa) - [Error Handling and Logging](#error-handling-and-logging) - [Centralized Logging](#centralized-logging) - [Error Categorization](#error-categorization) - [Graceful Degradation](#graceful-degradation) - [Alerting and Monitoring](#alerting-and-monitoring) - [Log Retention Policies](#log-retention-policies) - [Performance Optimization](#performance-optimization) - [Caching](#caching) - [Asynchronous Processing](#asynchronous-processing) - [Database Indexing](#database-indexing) - [Load Balancing](#load-balancing) - [Scalability Strategies](#scalability-strategies) - [Horizontal Scaling](#horizontal-scaling) - [Vertical Scaling](#vertical-scaling) - [Microservices Architecture](#microservices-architecture) - [Load Testing](#load-testing) - [User Interface Design Principles](#user-interface-design-principles) - [Notification System](#notification-system) - [Notification Channels](#notification-channels) - [Configurable Preferences](#configurable-preferences) - [Event Triggers](#event-triggers) - [Delivery Reliability](#delivery-reliability) - [Audit Trail](#audit-trail) - [Data Integration](#data-integration) - [API Integration](#api-integration) - [Data Ingestion](#data-ingestion) - [Data Transformation](#data-transformation) - [Data Synchronization](#data-synchronization) - [Error Handling](#error-handling) - [Reporting and Analytics](#reporting-and-analytics) - [Data Visualization](#data-visualization) - [Custom Reports](#custom-reports) - [Real-time Analytics](#real-time-analytics) - [Historical Analysis](#historical-analysis) ## Multitenancy 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. ### Mandators Each tenant is represented by a Mandator entity, which encapsulates all data and configurations specific to that tenant. ### Data Isolation The architecture ensures that data belonging to different tenants is isolated, preventing unauthorized access between tenants. ### Configuration Management Each tenant can have customized settings and preferences, managed through the Mandator entity. ## Data Model 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. A detailed [Data Model](08_concepts/02_data_model.md) documentation is available. Discounted cash-flow metrics (NPV, IRR, Payback) referenced by the economic portion of the data model are described in the [Financial Metrics Specification](../specifications/financial_metrics.md), while stochastic extensions leverage the Monte Carlo engine documented in the [Monte Carlo Simulation Specification](../specifications/monte_carlo_simulation.md). All data interactions are handled through the [Data Access Layer](05_building_block_view.md#data-access-layer), ensuring consistency and integrity across operations. ## Security 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. Within the system, security is enforced through multiple layers, including data encryption, access controls, audit logging, vulnerability management, and compliance monitoring. A comprehensive [Security Concept](08_concepts/03_security.md) is being developed as well. ## Authentication and Authorization The system utilizes a secure authentication mechanism to verify user identities and manage access to resources. ### Authentication Users authenticate using secure methods, such as OAuth 2.0 or JWT tokens, to ensure the legitimacy of access requests. ### Authorization Access to resources is controlled through role-based permissions, ensuring users can only access data and functionalities relevant to their roles. ### Session Management User sessions are managed securely, with mechanisms in place to prevent session hijacking and ensure session integrity. ### Token Expiration Access tokens have a limited lifespan and are refreshed periodically to enhance security. ### Multi-Factor Authentication (MFA) The system supports MFA to provide an additional layer of security during user authentication. ## Error Handling and Logging The system implements a comprehensive error handling and logging strategy to ensure reliability and facilitate troubleshooting. ### Centralized Logging All application logs are centralized to a logging service, enabling efficient monitoring and analysis of system behavior. ### Error Categorization Errors are categorized into different types (e.g., client errors, server errors) to facilitate targeted handling and resolution. ### Graceful Degradation The system is designed to handle errors gracefully, providing meaningful feedback to users without exposing sensitive information. ### Alerting and Monitoring The system includes mechanisms for alerting administrators about critical errors and monitoring system health. ### Log Retention Policies Logs are retained for a specified period to comply with regulatory requirements and support forensic analysis. ## Performance Optimization The system is designed with performance optimization strategies to ensure efficient operation and responsiveness. ### Caching Frequently accessed data is cached to reduce database load and improve response times. ### Asynchronous Processing Time-consuming operations are handled asynchronously to prevent blocking user interactions. ### Database Indexing Appropriate indexing strategies are implemented to optimize query performance. ### Load Balancing Traffic is distributed across multiple servers to ensure optimal resource utilization and minimize latency. ## Scalability Strategies The system is architected to scale efficiently in response to varying workloads and user demands. ### Horizontal Scaling The system can add more machines or instances to handle increased load, distributing traffic and processing across multiple nodes. ### Vertical Scaling Individual components can be upgraded with more resources (CPU, memory) to improve performance without changing the overall architecture. ### Microservices Architecture The system is designed as a collection of loosely coupled services, allowing for independent scaling of different components based on demand. ### Load Testing Regular load testing is conducted to identify bottlenecks and ensure the system can handle expected traffic patterns. ## User Interface Design Principles 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. ## Notification System The system includes a notification mechanism to inform users about important events and updates. ### Notification Channels The system supports multiple channels for notifications, including email, SMS, and in-app alerts. ### Configurable Preferences Users can customize their notification preferences, selecting the types of notifications they wish to receive and the channels through which they are delivered. ### Event Triggers Notifications are triggered by specific events within the system, such as project updates, data processing completions, or system alerts. ### Delivery Reliability The notification system is designed to ensure reliable delivery of messages, with retry mechanisms in place for failed attempts. ### Audit Trail A record of all sent notifications is maintained for auditing purposes and to track user engagement. ## Data Integration The Calminer system is designed to integrate seamlessly with various external data sources and services. ### API Integration The system can connect to external APIs to fetch or send data as needed. ### Data Ingestion Mechanisms are in place to ingest data from various sources, including databases, file systems, and streaming platforms. ### Data Transformation The system can transform data into the required format for processing and analysis. ### Data Synchronization Regular synchronization processes ensure that data remains consistent across all integrated systems. ### Error Handling Robust error handling mechanisms are implemented to manage integration failures and ensure data integrity. ## Reporting and Analytics The Calminer system includes comprehensive reporting and analytics capabilities to support data-driven decision-making. ### Data Visualization The system provides tools for visualizing data through charts, graphs, and dashboards, making it easier to identify trends and insights. ### Custom Reports Users can create custom reports based on specific criteria, allowing for tailored analysis of project performance and resource utilization. ### Real-time Analytics The system supports real-time data processing and analytics, enabling users to access up-to-date information and respond quickly to changing conditions. ### Historical Analysis The system maintains a history of key metrics and events, allowing for retrospective analysis and identification of long-term trends.