1. Overall Architecture
Our platform follows a modular, service-oriented architecture with a clear separation between presentation, application, and data layers. A web client communicates with backend services via REST/JSON APIs over HTTPS. Stateless application services are deployed behind a load balancer and scale horizontally. Shared infrastructure components (authentication, logging, monitoring, and messaging) are provided as common services used by all modules.

2. Core Application Modules

• Authentication & Identity – Handles user registration, login, session management, and token issuance (JWT or OAuth2). Integrates with external identity providers when required.
• Domain Logic / Business Services – Encapsulates core business rules, validation, and workflows. Each bounded context (e.g., accounts, billing, reporting) is implemented as a separate service or module with its own data model.
• Orchestration & Workflow – Coordinates multi-step operations across services, using either synchronous API calls or asynchronous events on a message bus.

3. Public & Internal APIs
The system exposes a versioned REST API gateway that fronts all public endpoints. The gateway performs request routing, rate limiting, authentication, and basic input validation. Internal services communicate primarily via REST over HTTP, with well-defined contracts and DTOs. For high-throughput or decoupled interactions (e.g., event notifications, background processing), services publish and consume messages on a queue or streaming platform.

4. Data Storage Layer
The primary system of record is a relational database (e.g., PostgreSQL or MySQL) used for transactional data and enforcing integrity constraints. Read-heavy use cases are optimized via read replicas and carefully designed indexes. For semi-structured or high-volume data (logs, metrics, documents), we use specialized stores such as a document database or time-series engine. Caching (e.g., Redis) is used to reduce latency for frequently accessed data and to offload the primary database.

5. External Integrations
The platform integrates with third-party services such as payment gateways, email/SMS providers, and analytics platforms. Integrations are encapsulated behind dedicated adapter services that normalize external APIs into internal interfaces. All outbound calls are wrapped with retry, timeout, and circuit-breaker policies to improve resilience and isolate failures.

6. Data Flows & Component Interaction
Typical request flow starts at the client, which calls the API gateway. The gateway authenticates the request and forwards it to the appropriate backend service. The service executes domain logic, reads or writes data through a repository layer, and may publish domain events for downstream consumers. Responses are returned as JSON with consistent error handling and correlation IDs for tracing. Background jobs and scheduled tasks are executed by worker services that consume messages from queues and interact with the same domain and data layers.

7. Key Technologies & Operational Concerns
Backend services are implemented using a modern web framework (e.g., Node.js/Express, Java/Spring Boot, or .NET) and are containerized for deployment on an orchestration platform such as Kubernetes. Configuration is externalized and managed per environment. Centralized logging, metrics, and distributed tracing provide observability across services. Automated CI/CD pipelines build, test, and deploy services, ensuring consistent, repeatable releases and enabling engineers to evolve the architecture safely over time.

Supported Platforms & Environments

• Web: Modern browsers (Chrome, Firefox, Edge, Safari) with ES2019+ and CSS3 support.
• Server OS: Linux (Ubuntu LTS, RHEL), optional Windows Server 2019+ for .NET deployments.
• Containerization: Docker-compatible runtime; Kubernetes 1.24+ for orchestration.
• Cloud: AWS, Azure, or GCP with managed PostgreSQL/SQL Server and object storage.
• Runtime: Node.js 18+ or .NET 6+ for backend services, depending on deployment profile.

Technology Stack

• Frontend: React or Vue SPA, TypeScript, REST/JSON and optional GraphQL API integration.
• Backend: Microservice-ready architecture using HTTP/REST, background workers, and message queues.
• Data: PostgreSQL 13+ (primary), Redis for caching and ephemeral data.
• Messaging: RabbitMQ or Kafka for asynchronous processing and event streaming.
• Observability: Centralized logging (ELK/EFK), metrics via Prometheus, dashboards in Grafana.

Performance & Scalability Targets

• Baseline throughput: 500–1,000 requests/second per service under nominal load.
• Average API latency: < 200 ms for 95th percentile on core read operations.
• Horizontal scaling via stateless services and auto-scaling groups.
• Database tuned for > 10,000 concurrent connections via connection pooling.
• Background jobs processed within 1–5 minutes of enqueue under peak load.

Security & Compliance

• Transport security: TLS 1.2+ for all external and inter-service communication.
• Authentication: OAuth2/OIDC with JWT access tokens and refresh token rotation.
• Authorization: Role-based access control (RBAC) with fine-grained permissions.
• Data protection: At-rest encryption for databases and object storage.
• Compliance-ready: Logging, audit trails, and data retention policies to support ISO 27001/GDPR-aligned deployments.

Network, Hardware & Dependencies

• Network: Stable IPv4/IPv6, HTTP/HTTPS ports 80/443, optional VPN or private peering.
• Bandwidth: Minimum 10 Mbps per application node; higher for media-heavy workloads.
• Hardware (per node): 4 vCPU, 8–16 GB RAM, SSD storage with 5000+ IOPS recommended.
• Third-party services: SMTP provider, optional SSO (Azure AD/Okta), and object storage (S3-compatible).
• Optional integrations: Webhooks to external systems, REST APIs to CRM/ERP platforms.