Summary
The Task Management System (TMS) is designed to facilitate task assignment, tracking, and completion within an organization. It ensures efficient workflow management, accountability, and transparency in task execution. The system provides features such as task creation, prioritization, deadline management, user role-based access, notifications, and reporting. This document outlines the architectural components, technical design, and system interactions to provide a clear understanding of the solution.
1. Introduction
The purpose of this document is to define the architecture of the Task Management System (TMS). It describes the system's design principles, components, and interactions to guide development and ensure alignment with business and technical requirements.
1.1 Document Objectives
Define the architectural framework of the Task Management System.
Provide a structured view of system components and their interactions.
Establish a reference for developers, architects, and stakeholders.
Ensure consistency and scalability in system design.
Support decision-making for implementation and future enhancements.
1.2 Reference Documents
The following documents are referenced in this architecture document:
System Requirements Specification (SRS) for Task Management System
User Experience (UX) Guidelines
Security and Compliance Standards
API Documentation
Database Schema Design Document
2. General Description
2.1 Brief Functional Description
2.1.1 System in Context
The Task Management System (TMS) is designed to facilitate task creation, tracking, and completion across teams and individuals. It operates within an organizational environment where multiple departments require structured workflows to manage assignments, deadlines, and dependencies efficiently. The system integrates with existing enterprise tools, including email, calendar systems, and project management platforms, ensuring seamless collaboration and communication.
Currently, task management is handled through a combination of manual tracking, spreadsheets, and independent tools, leading to inefficiencies, lack of visibility, and inconsistencies in reporting. The TMS will replace fragmented workflows with a centralized platform, ensuring real-time task updates, status tracking, and automated notifications.
2.1.2 High-Level Functional Breakdown
The core functionalities of the TMS include:
Task Creation & Assignment – Users can create tasks, assign them to individuals or teams, and set due dates.
Task Tracking & Status Management – Tasks are monitored throughout their lifecycle, with status updates including "Not Started," "In Progress," "Completed," and "Blocked."
Collaboration & Notifications – Users receive alerts for due dates, task modifications, and dependencies to ensure timely completion.
Reporting & Analytics – Managers can generate reports on task completion rates, overdue tasks, and team productivity.
Integration with External Systems – Synchronization with project management tools, email systems, and calendars for seamless task management.
2.1.3 Design Constraints
The system design is subject to the following constraints:
Use of Specific Technologies – The system must be built using a microservices architecture with Java Spring Boot for the backend and Angular for the frontend.
Database Requirement – PostgreSQL is required for structured task data storage.
Integration with Existing Enterprise Systems – The system must support API-based integration with internal authentication services (e.g., LDAP, SSO) and third-party collaboration tools.
Security & Compliance – The system must adhere to enterprise security policies, including role-based access control (RBAC) and data encryption standards.
2.2 Brief Technical Description
2.2.1 System in Context
The TMS operates within the broader IT infrastructure of the organization. It interacts with:
Authentication Services – Ensuring secure user access and authorization.
Project Management Tools – For seamless data exchange between related systems.
Email & Notification Services – Enabling automated alerts and reminders.
Enterprise Databases – Storing task-related data and historical records.
User Interfaces – Web-based frontend and mobile access for task management.
2.2.2 High-Level Technical Breakdown
Frontend Layer – Built using Angular, it provides an intuitive UI for users to manage tasks efficiently.
Backend Layer – Implemented in Java Spring Boot, it handles business logic, task processing, and API interactions.
Database Layer – PostgreSQL serves as the primary database for task storage and retrieval.
Integration Layer – RESTful APIs enable communication with external services like authentication systems, email servers, and other enterprise applications.
Deployment Environment – The system will be containerized using Docker and orchestrated with Kubernetes, ensuring scalability and resilience.
Security Mechanisms – Implementation of OAuth 2.0, JWT-based authentication, and RBAC for controlled access.
This chapter describes the list of non-functional requirements that the architecture document must fulfill. Each requirement is numbered to ensure traceability, facilitating verification of global coverage.
3.1 Technical Framework and Major Decisions
This section outlines the non-functional requirements that arise from the technical framework, including major orientations and decisions.
3.1.1 Software
The system must utilize pre-defined software components, frameworks, and libraries that align with enterprise standards. Open-source or proprietary software must be evaluated for licensing, security, and maintainability.
3.1.2 Interfacing
The system must be designed to integrate with external systems using APIs, web services, and message queues. Standard protocols such as REST, SOAP, and GraphQL should be supported.
3.2 System Usage Load
3.2.1 Transactional Load
Declared users: The system must support a predefined number of registered users.
Number of concurrent connections: The system must handle a specified number of concurrent sessions without performance degradation.
3.2.2 External Processing Load
Interfaces: The system must process data exchange with external systems efficiently.
Print: The system must support document generation and printing at scale.
Mails: The system must handle email notifications, alerts, and scheduled reports.
3.2.3 Internal Processing Load
In parallel with the transactional load: The system must allow background processing without impacting real-time transactions.
Batch mode processing: Large data processing operations must run in batch mode within predefined time windows.
3.3 Sizing
3.3.1 Data Sizing
The system must accommodate a growing dataset, ensuring efficient storage and retrieval.
3.3.2 File Sizing
Storage requirements must consider the expected volume of uploaded and generated files.
3.3.3 Traffic Sizing
The system must support anticipated data transfer rates, ensuring network bandwidth sufficiency.
3.3.4 Archiving
Old data must be archived based on retention policies while maintaining accessibility for audits.
3.4 Expected Quality of Service
3.4.1 Availability
a. Service Availability
Availability is categorized for user access, batch processing, and maintenance periods.
b. Recovery Time Objective
The system must ensure a maximum recovery time of X minutes following a failure.
c. Recovery Point Objective
Data recovery must guarantee that no more than X minutes of data is lost in case of a disaster.
3.4.2 Expected Response Times
Transactional requests response time: The system must respond within X milliseconds for standard transactions.
Window for night processing (batch mode): Batch processes must complete within the allocated nightly window.
3.5 Security
3.5.1 Data Confidentiality
Access controls and encryption mechanisms must protect sensitive data.
3.5.2 Data Criticality
The system must classify data based on sensitivity and apply appropriate protection measures.
3.5.3 Imposed Security Constraints
Security policies must align with organizational standards and regulatory requirements.
3.5.4 Components Sensitivity to External Attacks
Open-source and proprietary components must undergo security assessment and vulnerability monitoring.
3.5.5 Sustainability
The system must be maintainable and upgradable to accommodate future needs.
3.5.6 Scalability
The architecture must support increased users, transactions, and data volumes.
3.5.7 Forecasted Evolutions
The system must be designed to incorporate technological advancements and business changes.
3.6 Technical Constraints
3.6.1 Compatibility with Operating Systems
The system must be compatible with Windows, Linux, and macOS environments.
3.6.2 Charset/Encoding
Data encoding must adhere to UTF-8 to ensure multilingual support.
3.6.3 Client Workstation
The system must support modern web browsers and comply with accessibility standards.
4. Logical Architecture
4.1. Overall structure
The logical architecture of the Task Management System (TMS) defines the high-level structure and organization of system components, ensuring modularity, scalability, and maintainability. It follows a layered approach to separate concerns and optimize system performance. The architecture consists of the following main layers:
Presentation Layer: The user interface for accessing the task management system via web and mobile platforms.
Application Layer: Business logic and workflow processing.
Integration Layer: Interfaces for connecting external systems, including authentication, reporting, and third-party services.
Data Layer: Database management, storage, and retrieval operations.
This layered approach ensures flexibility, ease of maintenance, and scalability while supporting high availability and performance.
4.2. Components Identification
The Task Management System consists of multiple interacting components that ensure efficient task processing and management. These include:
User Interface Component: Provides a web-based and mobile-friendly interface for users to interact with the system.
Authentication and Authorization: Manages user access and permissions using OAuth2 and role-based access control (RBAC).
Task Management Engine: Core component responsible for task creation, assignment, tracking, and lifecycle management.
Notification Service: Sends email, SMS, or push notifications based on task events and user preferences.
Reporting and Analytics: Generates reports and insights on task performance, workload distribution, and user activity.
API Gateway: Facilitates communication with external systems, enabling integrations with third-party services.
Database System: A relational database (e.g., PostgreSQL or MySQL) for storing task-related information and user data.
4.3. Instances Identification
The Task Management System will be deployed across multiple environments to ensure stability, reliability, and quality assurance before production deployment. The following environments are identified:
Development Environment
Dedicated to development tasks, including feature implementation, bug fixes, and preliminary testing.
Functionally representative of production but with reduced data volume.
No high availability; performance optimization is not a priority.
Integration Environment
Used for deployment testing and integration of new system versions and patches.
Both technically and functionally representative of production but with less data.
No high availability, with reduced performance optimization.
Functional Acceptance Environment
Dedicated to functional testing and validation of new versions before moving to production.
Fully replicates the production environment, including data volume and configurations.
Ensures final quality assurance before deployment.
Pre-Production Environment
Used for final validation of system performance and scalability under real-world conditions.
Includes full production-like configurations and data sets.
Serves as the final test stage before deployment to the production environment.
Production Environment
The live environment used by end-users.
Meets the expected quality of service requirements, including high availability and optimized response times.
Implements backup, disaster recovery, and security monitoring measures.
This structured deployment strategy ensures controlled rollouts, minimizes risk, and optimizes system reliability across different stages of the software development lifecycle.
5. Technical Architecture
5.1. Overall structure
This section presents the high-level technical architecture of the Task Management System. It includes a mapping of technical components within logical blocks, ensuring alignment with the logical architecture described in Chapter 4. The global structure provides a visual representation of how the system components interact and integrate to support system functionality and non-functional requirements.
5.2. Traceability of Non-Functional Requirements
This section details the traceability of non-functional requirements to their corresponding technical components. The purpose is to establish a clear link between system requirements and the implemented technical solutions, ensuring that each requirement is adequately addressed.
| Non-Functional Requirement | Technical Component | Description |
|---|---|---|
| Availability | Load Balancer, Database Replication | Ensures system uptime and redundancy |
| Security | Authentication Module, Encryption | Provides access control and data protection |
| Performance | Caching Mechanism, Optimized Queries | Enhances response times and scalability |
| Scalability | Containerized Deployment, Auto-scaling | Supports growth and system expansion |
| Maintainability | CI/CD Pipelines, Monitoring Tools | Facilitates system updates and issue tracking |
5.3. Description of Technical Components
This section provides a detailed description of each technical component, including its role, mode of operation, and any dependencies on Commercial Off-The-Shelf (COTS) solutions or custom developments.
5.3.1. Component 1 - Application Backend
Mode of Operation: The backend operates as a microservices-based architecture using RESTful APIs. It processes business logic, manages database interactions, and exposes endpoints for frontend consumption. COTS Involved: Spring Boot (Java), PostgreSQL, Redis Developments to be Carried Out: Custom business logic implementation, API development, and integration with authentication services.
5.3.2. Component 2 - User Interface
Mode of Operation: The frontend is a web-based Single Page Application (SPA) that interacts with the backend via APIs. It provides an intuitive user interface for managing tasks. COTS Involved: React.js, Material-UI Developments to be Carried Out: Custom UI/UX design, state management, integration with backend services.
5.3.3. Component 3 - Authentication and Authorization
Mode of Operation: The authentication service validates user credentials and provides role-based access control. COTS Involved: Keycloak, OAuth2, JWT Developments to be Carried Out: Integration with the backend, user role management, and secure session handling.
5.3.4. Component 4 - Database
Mode of Operation: A relational database stores system data, including tasks, users, and permissions. Data integrity and consistency are maintained through ACID transactions. COTS Involved: PostgreSQL, Liquibase (for versioned database migrations) Developments to be Carried Out: Schema design, query optimization, and indexing strategies.
5.3.5. Component 5 - Caching Layer
Mode of Operation: The caching layer reduces database load and improves system performance by storing frequently accessed data in-memory. COTS Involved: Redis Developments to be Carried Out: Implementation of caching strategies, cache invalidation mechanisms.
5.3.6. Component 6 - Logging and Monitoring
Mode of Operation: Centralized logging and monitoring services track system performance, detect anomalies, and enable proactive troubleshooting. COTS Involved: ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, Grafana Developments to be Carried Out: Log aggregation, metric collection, alerting system configuration.
5.4. Frameworks and Development Tools
This section lists the frameworks, tools, and platforms that will be used in the development and deployment of the Task Management System.
| Category | Tools/Frameworks |
| Backend | Spring Boot, Hibernate, REST APIs |
| Frontend | React.js, Material-UI |
| Database | PostgreSQL, Liquibase |
| Caching | Redis |
| Authentication | Keycloak, OAuth2, JWT |
| CI/CD | Jenkins, GitHub Actions, Docker |
| Monitoring | Prometheus, Grafana, ELK Stack |
| Deployment | Kubernetes, Helm, Terraform |
This technical architecture provides a foundation for implementing a scalable, secure, and high-performing Task Management System. Let me know if you need further refinements or additional details.
6. Physical Architecture
This chapter details the physical architecture of the task management system, including the various environments and their sizing requirements.
6.1. Instances Sizing
The system requires multiple environments to support development, integration, testing, and production activities. The following subsections outline the sizing of each environment.
6.1.1. Development Environment
Purpose: Dedicated to development tasks, including new functionality implementation and bug fixes.
Infrastructure: Single instance with reduced performance compared to production.
Data Volume: Minimal test data, not a full production replica.
High-Availability: Not required.
6.1.2. Integration Environment
Purpose: Used for deployment testing and integration of new versions and patches.
Infrastructure: Technically representative of production but with reduced data volume.
High-Availability: Not required.
6.1.3. Business Acceptance Environment
Purpose: Functional validation and acceptance testing before deployment to production.
Infrastructure: Functionally and technically identical to production.
Data Volume: Same as production.
High-Availability: Not required but desirable.
6.1.4. Performance Testing Environment
Purpose: Simulates production load for performance and stress testing.
Infrastructure: Identical to production for accurate testing results.
Data Volume: Partial or full production dataset.
High-Availability: Required for accurate simulation.
6.1.5. Production Environment
Purpose: Dedicated to end-user operations.
Infrastructure: Fully redundant, high-availability setup.
Data Volume: Full production dataset.
High-Availability: Mandatory with failover mechanisms in place.
6.2. Environments Summary
| Environment | Purpose | Number of Machines |
|---|---|---|
| Development | Feature development, bug fixes | X |
| Integration | Deployment and integration testing | X |
| Business Acceptance | Functional validation before production | X |
| Performance Testing | Load and stress testing | X |
| Production | End-user operations, high availability | X |
| TOTAL | - | X |
Each environment is provisioned according to its role, ensuring that development, testing, and production activities are adequately supported while maintaining cost-effectiveness and efficiency.
7. Hardware Infrastructures Definition
This chapter describes the hardware infrastructure required for the Task Management System, including cloud, server, network, and data storage components.
7.1. Cloud Infrastructure
7.1.1. CaaS (Container as a Service)
The Task Management System leverages Kubernetes-based CaaS solutions such as AWS EKS, Azure AKS, or Google GKE. The container orchestration platform ensures scalability, resilience, and simplified deployments. Auto-scaling policies are configured to handle dynamic workloads efficiently.
7.1.2. DBaaS (Database as a Service)
A managed DBaaS solution is used to ensure high availability, automated backups, and scaling. The system supports AWS RDS (PostgreSQL/MySQL), Azure SQL Database, or Google Cloud SQL. The database is deployed across multiple availability zones for redundancy, with read replicas enabled for load balancing.
7.2. Servers Infrastructure
7.2.1. Processing Servers
Processing servers handle application logic and background tasks. The infrastructure consists of:
Instance Type: AWS EC2 (c5.large), Azure VM (D2s v4), or Google Compute Engine (e2-standard-4)
CPU: 4 vCPUs
RAM: 16GB
Scaling: Horizontal auto-scaling enabled
Load Balancing: Traffic distributed using ALB/NLB
7.2.2. Data Servers
Dedicated data servers manage structured and unstructured data. The specifications include:
Storage Type: NVMe SSD for high IOPS performance
Redundancy: RAID-10 configuration for fault tolerance
Backup: Automated snapshots every 24 hours with a 30-day retention policy
7.3. Networking Infrastructure
7.3.1. External Network
The external network ensures secure access through:
Firewalls: Web Application Firewall (WAF) to protect against threats
API Gateway: Used for rate limiting and security enforcement
Secure Access: Enforced via HTTPS and VPN for administrative access
7.3.2. Internal Network
The internal network is designed for secure communication between services:
Private Subnet: Communication restricted to internal components
VPC Peering: Enables inter-service connectivity
Service Mesh: Implements zero-trust networking principles
7.4. Data Storage Infrastructure
7.4.1. Storage Network
A high-speed dedicated storage network ensures optimal read/write performance, utilizing a 10 Gbps fiber network for backend storage.
7.4.2. Storage Internal Architecture
The storage system includes:
Object Storage: AWS S3, Azure Blob, or Google Cloud Storage for unstructured data
Block Storage: AWS EBS, Azure Managed Disks for high-performance storage
File Storage: AWS EFS, Azure Files for shared storage needs
7.4.3. Storage Sizing Report
Estimated Data Growth: 10% annually
Projected Storage Needs: 5TB initially, scaling to 20TB over five years
Backup Policy: Full backups weekly, incremental backups daily
7.5. Hosting & Services
7.5.1. Technical Data for Hosting Equipment
Hosting specifications include:
CPU & Memory:
Compute Nodes: 4 vCPUs, 16GB RAM per node
Database Nodes: 8 vCPUs, 32GB RAM per node
Redundancy & Failover:
Multi-zone deployment for failover support
Load balancers distribute requests across instances
Power & Cooling:
Redundant power supply with battery backup
Cooling managed via precision air conditioning systems
7.5.2. Overall diagram
A high-level architecture diagram illustrating cloud, network, storage, and security layers, including redundancy and failover mechanisms.
7.5.3. Implantation Diagram
A detailed deployment diagram showing:
Server allocation across regions/zones
Network topology with firewalls and security groups
Backup and disaster recovery sites
8. Definition of Software Infrastructure
This chapter defines the software infrastructure required for the Task Management System, including the software stack for processing servers, data servers, and client workstations.
8.1. Processing Servers
8.1.1. Operating System & Images
Operating System: Ubuntu 22.04 LTS / Windows Server 2022
Base Images: Pre-configured images with security hardening and essential packages
Virtualization: Hosted on VMware ESXi or cloud-based images (AWS AMI, Azure VM Image)
8.1.2. Software
Application Server: Apache Tomcat / Nginx
Programming Runtime: Java 17 / Node.js 18
Containerization: Docker & Kubernetes
Monitoring Tools: Prometheus & Grafana
Security Tools: OSSEC, Fail2Ban
8.1.3. Prerequisites
Network Configuration: Static IP assignment with firewall rules
User Access: Role-based access control (RBAC) with LDAP authentication
Logging & Auditing: Centralized logging via ELK stack
8.2. Data Servers
8.2.1. Operating System
OS Options: Ubuntu 22.04 LTS / Red Hat Enterprise Linux 9
Security Hardening: SELinux enabled, automatic updates
8.2.2. Software
Database Engine: PostgreSQL 14 / MySQL 8
Backup & Recovery: Automated daily backups via AWS Backup / Azure Backup
Replication: Read replicas enabled for performance
8.2.3. Prerequisites
Storage Configuration: RAID-10 for data redundancy
Network Access: Internal-only database access via VPC
User Management: Database roles with least privilege principle
8.3. Client Workstation
8.3.1. Operating Systems
Supported OS: Windows 11 / macOS Ventura / Ubuntu 22.04 LTS
8.3.2. Software
Web Browser: Google Chrome (latest), Mozilla Firefox (latest)
Office Suite: Microsoft 365 / LibreOffice
Security Software: Endpoint protection (CrowdStrike / Windows Defender ATP)
8.3.3. Prerequisites
Minimum Hardware Requirements: 8GB RAM, 256GB SSD
Network Configuration: VPN for remote access
Access Control: Multi-Factor Authentication (MFA) required
9. IS Integration
This section describes the integration of the Task Management System with internal and external Information Systems (IS).
9.1. General Integration Diagram
The integration diagram includes internal APIs, external service interactions, and data flow between components. The system supports RESTful APIs, Webhooks, and Message Queues for asynchronous processing.
9.2. External Interfaces Description
9.2.1. Interface XXX
Description: Integration with HR System for employee data synchronization
Protocol: REST API
Authentication: OAuth 2.0
Frequency: Daily sync at midnight UTC
Data Format: JSON
9.2.2. Interface XXX
Description: Integration with Email Service for task notifications
Protocol: SMTP / API
Authentication: API Key-based
Frequency: Real-time event-driven
Data Format: MIME / JSON
9.3. External Interfaces Summary
| External IS | Direction | Description | Protocol | Frequency | Sizing |
|---|---|---|---|---|---|
| HR System | Inbound | Employee data sync | REST API | Daily | ~50MB |
| Email Service | Outbound | Task notifications | SMTP/API | Real-time | ~1MB per event |
| Payment Gateway | Outbound | Subscription payments | REST API | Monthly | ~100MB |
This section ensures seamless integration of the Task Management System with external and internal IS components, maintaining security and efficiency.
10. Security
This chapter outlines the security measures implemented within the Task Management System, ensuring data protection, controlled access, and secure communication across the platform.
10.1. Access Management
10.1.1. DMZ
The system is hosted in a secure environment with a demilitarized zone (DMZ) to manage external access. The DMZ:
Separates external traffic from internal resources.
Utilizes firewalls and intrusion detection systems (IDS) to prevent unauthorized access.
Restricts direct database access from external sources.
10.1.2. Data Access Security
Data access is secured through:
Role-based access control (RBAC) to ensure users access only necessary resources.
Data encryption at rest and in transit.
Periodic access audits to review and restrict unauthorized access.
Multi-factor authentication (MFA) for privileged users.
10.2. Users Authentication
10.2.1. Authentication Phases
The authentication process follows these phases:
User Identification – Users provide login credentials.
Validation – Credentials are verified against a secure directory service.
Authorization – User roles and permissions are evaluated.
Session Management – Secure session tokens are generated.
10.2.2. Identification
User identification is handled through unique credentials linked to corporate directories, including:
Active Directory (AD) for internal users.
OAuth/OpenID Connect for external integrations.
10.2.3. Authorization
Authorization policies enforce:
RBAC to grant access based on user roles.
Attribute-based access control (ABAC) for granular control.
Just-in-time (JIT) permissions for temporary access needs.
10.2.4. Habilitation
Habilitation ensures:
User provisioning and de-provisioning workflows.
Automated role assignment based on job function.
Regular privilege reviews to prevent excessive access.
10.2.5. Single Sign-On (SSO)
The Task Management System integrates Single Sign-On (SSO) for seamless authentication using:
SAML 2.0 for enterprise authentication.
OAuth 2.0/OpenID Connect for third-party integration.
Federated identity management to enable cross-platform authentication.
10.3. Traffic Encryption
10.3.1. Traffic with Client Workstations
Secure communication between client workstations and the system is enforced through:
HTTPS/TLS 1.2+ encryption for all web traffic.
Mutual TLS (mTLS) for sensitive transactions.
End-to-end encryption for API communications.
10.3.2. Traffic with External Systems
Data exchanges with external systems are secured using:
TLS 1.2+ for encrypted connections.
VPN tunnels for secure inter-organization communication.
Message-level encryption for API calls.
Security certificates (X.509) for authentication and integrity verification.
These security measures ensure the Task Management System maintains confidentiality, integrity, and availability across all its components.
11. Methodology
11.1. Performance Measurement
11.1.1. Methodology
Performance measurement is based on key metrics such as response time, throughput, and resource utilization.
A benchmarking approach is used to compare system performance under varying workloads.
Stress testing and load testing are conducted periodically.
11.1.2. Tooling
APM Tools: New Relic, Datadog, or Prometheus for monitoring performance.
Load Testing Tools: JMeter, Gatling, or Locust for evaluating system load capacity.
Log Analysis: ELK Stack (Elasticsearch, Logstash, Kibana) for analyzing system logs.
11.1.3. Phasing
Phase 1: Baseline performance measurement under normal load conditions.
Phase 2: Stress and load testing to determine system limits.
Phase 3: Continuous monitoring and optimization.
11.2. Availability Measurement
11.2.1. Methodology
System uptime is monitored using industry-standard SLAs.
High availability (HA) testing is performed to validate failover mechanisms.
11.2.2. Tooling
Availability Monitoring: AWS CloudWatch, Azure Monitor, or Google Operations Suite.
Incident Management: PagerDuty, Opsgenie for automated alerts.
Synthetic Testing: Selenium, Pingdom for automated uptime testing.
11.2.3. Phasing
Phase 1: Establish uptime baselines and SLAs.
Phase 2: Conduct failover and disaster recovery testing.
Phase 3: Implement real-time monitoring.
11.3. Security Measurement
11.3.1. Methodology
Security audits and penetration testing are conducted periodically.
Compliance checks against security frameworks such as ISO 27001, NIST, and GDPR.
11.3.2. Tooling
Vulnerability Scanning: Qualys, Nessus, or OpenVAS.
Penetration Testing: Metasploit, Burp Suite.
SIEM: Splunk, IBM QRadar for real-time security event monitoring.
11.3.3. Phasing
Phase 1: Initial security audit and vulnerability assessment.
Phase 2: Continuous monitoring and improvement.
Phase 3: Periodic security audits and compliance reporting.
12. Operations
12.1. Deployment
12.1.1. Deployment Policy
Blue-green deployments and canary releases are used to minimize downtime.
CI/CD pipelines ensure automated and controlled deployments.
12.1.2. Deployment Phasing
Phase 1: Development and testing.
Phase 2: Staging environment validation.
Phase 3: Production deployment with rollback strategies.
12.2. Backups
12.2.1. Backup Policy
Daily full backups with incremental backups every hour.
Backups are retained for 30 days and stored in multiple availability zones.
12.2.2. Backup Architecture
Primary Storage: AWS S3, Azure Blob, Google Cloud Storage.
Secondary Storage: Offsite backups for disaster recovery.
12.2.3. Backup Tools
AWS Backup, Azure Backup, Veeam for automated backup scheduling and restoration.
12.3. Purges
12.3.1. Purge Policy
Data retention policy mandates purging inactive records after 7 years.
Logs older than 90 days are archived before purging.
12.3.2. Purge Tooling
Automated scripts using AWS Lambda, Azure Functions, or Google Cloud Functions.
12.4. Supervision
12.4.1. Supervision Policy
Real-time monitoring and alerting system in place.
Incident response plan to address critical failures.
12.4.2. Supervision Architecture
Centralized monitoring dashboard integrating various monitoring tools.
Proactive alerting based on defined thresholds.
12.4.3. Supervision Tooling
Prometheus, Grafana for visualization.
Splunk, ELK for log analytics.
12.4.4. Traces and Logs
Centralized logging using ELK Stack.
Tracing implemented using OpenTelemetry.
12.5. Disaster Recovery Plan
12.5.1. Disaster Recovery Policy
Recovery Time Objective (RTO): 4 hours.
Recovery Point Objective (RPO): 15 minutes.
12.5.2. Disaster Recovery Procedure
Step 1: Identify failure and notify response teams.
Step 2: Restore from the latest available backup.
Step 3: Validate system integrity before resuming operations.
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