Functional and Non-Functional Requirements for a CRM Project

Functional Requirements

1. Authentication Service

• User registration with email-password authentication
• JWT-based authentication with token refresh
• OAuth2 integration (Google, Facebook, etc.)
• Multi-Factor Authentication (MFA) via QR code or OTP
• Password reset and account recovery

2. User Service

• Manage user roles (Admin, Representative)
• Assign permissions based on roles
• Profile management (update name, email, password, etc.)
• User activity logging

3. Notification Service

• Send real-time notifications via email, push, and possibly SMS
• WebSocket support for real-time notifications
• Template-based notification system
• Subscription and preferences management (e.g., opt-in/out of specific notifications)

4. Lead Service

• Create, update, and delete leads
• Manage lead data (contact info, preferences, history)
• Automatic conversion of leads to customers based on predefined conditions
• Lead status tracking (e.g., new, contacted, qualified)
• Activity tracking (interactions, notes, follow-ups)
• Lead assignment to representatives

5. Customer Service

• Create, update, and delete customer
• Manage customer data (contact info, preferences, history)
• Track customer interactions and engagement
• Maintain a history of previous leads that converted into customers
• Relationship tracking (e.g., linked accounts, referrals)

6. Product Service

• Manage product catalog (name, description, price, availability)
• Assign products to customers or leads (e.g., products they’re interested in)
• Track product-related interactions (e.g., inquiries, orders)

7. Communication & API Gateway

• API Gateway routes requests to the respective microservices
• Implement authentication and rate limiting at the API Gateway level
• Event-driven architecture with RabbitMQ for inter-service communication

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Non-Functional Requirements

1. Security

• Role-Based Access Control (RBAC) for authorization
• Data encryption (AES for sensitive data, TLS for data in transit)
• Secure storage of credentials (hashed passwords using bcrypt/argon2)
• API rate limiting to prevent abuse
• Audit logging and monitoring for security events
• Compliance with GDPR and other relevant regulations

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2. Performance & Scalability

• Horizontal scaling for handling high traffic loads
• Asynchronous processing (RabbitMQ for event-driven architecture)
• Caching for frequently accessed data (Redis)
• Database indexing and query optimization
• Load balancing to distribute API traffic efficiently

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3. Reliability & Availability

• Service discovery and health checks (Consul/Eureka)
• Auto-scaling and failover mechanisms
• Distributed logging and monitoring (ELK stack, Prometheus + Grafana)
• Graceful degradation (fallback mechanisms if a service is down)
• Data backup and recovery strategies

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4. Maintainability & Observability

• Structured logging for debugging and tracing (e.g., OpenTelemetry, Logstash)
• Centralized monitoring for system health (Prometheus, Grafana)
• CI/CD pipelines for automated deployments (GitHub Actions, Jenkins)
• Versioning strategy for APIs (v1, v2, etc.)
• Unit and integration testing with coverage tracking

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5. Usability & UX

• API documentation with OpenAPI (Swagger)
• Standardized error handling with meaningful responses
• Efficient pagination and filtering in API responses

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6. Compliance & Auditing

• User activity logging for compliance audits
• Role-based restrictions on data access and modifications
• Data retention policies for compliance with regulations

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Technical Requirements

1. Authentication & Security Enhancements

• Zero Trust Architecture (ZTA) – Implement strict access control with least privilege principles.
• Rate Limiting & Throttling – Prevent brute force and DoS attacks at API Gateway (e.g., Nginx, Kong, or AWS API Gateway).
• OAuth2 Token Introspection & Revocation – Ensure active session validation instead of blindly accepting tokens.
• Harden MFA – Implement FIDO2/WebAuthn for passwordless authentication.
• Security Headers & CSP – Prevent XSS, CSRF, and Clickjacking attacks.

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2. Service Resilience & Fault Tolerance

• Circuit Breaker Pattern (Resilience4j/Hystrix) – Prevent cascading failures in case of a service crash.
• Retry & Backoff Strategy – Implement exponential backoff for transient failures.
• Bulkhead Pattern – Isolate failures within a single service to prevent global impact.
• Dead Letter Queue (DLQ) in RabbitMQ – Prevent message loss and handle failed events.
• Rate Limiting in RabbitMQ – Prevent flooding of messages by controlling event flow.

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3. Observability & Monitoring

• Distributed Tracing (Jaeger, OpenTelemetry) – Track requests across multiple services.
• Centralized Logging (ELK Stack or Loki + Grafana) – Aggregate logs from all microservices.
• Metrics & Alerts (Prometheus + Grafana) – Real-time monitoring of system health.
• Health Checks & Readiness Probes (Kubernetes/Liveness Probes) – Auto-restart unhealthy services.

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4. Data Management & Consistency

• Event Sourcing & CQRS – Separate read/write concerns for performance gains.
• Outbox Pattern – Ensure reliable event publishing to RabbitMQ.
• Database Partitioning & Sharding – Scale horizontally with distributed databases.
• Soft Deletes & Versioning – Prevent accidental data loss by using logical deletions.
• Immutable Audit Logs – Track changes securely with an append-only log structure.

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5. API & Client Interaction Enhancements

• GraphQL for Flexible Queries – Optimize data fetching for frontends.
• gRPC for High-Performance Internal APIs – Faster inter-service communication than REST.
• WebSockets for Instant Updates – Enhance real-time notifications.
• API Versioning Strategy – Ensure backward compatibility for future updates.

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6. Deployment & Scalability

• Kubernetes & Service Mesh (Istio, Linkerd) – Automate deployments and traffic management.
• Blue-Green & Canary Deployments – Minimize downtime during releases.
• Auto-Scaling (HPA + KEDA for RabbitMQ) – Dynamically scale microservices based on demand.
• Infrastructure as Code (Terraform, Pulumi) – Automate provisioning of cloud resources.
• Chaos Engineering (Gremlin, Litmus) – Proactively test system failure resilience.

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7. Compliance & Security Best Practices

• GDPR & Data Encryption (AES-256, TLS 1.3) – Ensure compliance with global security standards.
• API Security (OAuth2, mTLS, JWT Expiry Management) – Secure service-to-service communication.
• Secrets Management (Vault, AWS Secrets Manager) – Prevent credentials leakage.

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Services and Packages

Authentication & Security Enhancements

• JWT & OAuth2 → jsonwebtoken, passport, passport-jwt, passport-google-oauth20, oidc-client-ts (OIDC support)
• Rate Limiting → express-rate-limit, rate-limiter-flexible
• CSRF Protection → lusca, csurf
• CORS Management → cors
• Security Headers → helmet
• MFA & OTP → otplib (TOTP-based MFA), qrcode (QR code generation)
• Secrets Management → HashiCorp Vault, AWS Secrets Manager, Doppler
• Password Hashing → argon2 (recommended) or bcrypt
• API Gateway Security → Kong, AWS API Gateway, Traefik

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Service Resilience & Fault Tolerance

• Circuit Breaker → opossum (Node.js circuit breaker implementation)
• Retry & Backoff → p-retry, axios-retry
• Bulkhead Pattern → Kubernetes Pod Resource Limits
• Dead Letter Queue (DLQ) → RabbitMQ with amqplib or bullmq (Redis-based job queues)
• Rate Limiting for RabbitMQ → RabbitMQ policies, rabbitmq-queue-throttler

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Observability & Monitoring

• Logging → pino (fast structured logging), winston, morgan
• Distributed Tracing → opentelemetry-js, Jaeger, Honeycomb
• Metrics & Monitoring → prom-client (Prometheus metrics for Node.js), OpenTelemetry
• Centralized Logging → ELK Stack (Elasticsearch, Logstash, Kibana), Loki + Grafana
• Health Checks → terminus, Kubernetes liveness/readiness probes

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Data Management & Consistency

• Event Sourcing & CQRS → eventstore, nestjs/cqrs, Kafka
• Outbox Pattern → typeorm-outbox, Debezium for Change Data Capture (CDC)
• Database Sharding & Partitioning → PostgreSQL with Citus, CockroachDB
• Soft Deletes & Versioning → mongoose-delete (MongoDB soft delete), sequelize-soft-delete
• Immutable Audit Logs → PostgreSQL with pgaudit, winston for structured logging

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API & Client Interaction Enhancements

• WebSockets for Real-Time Updates → socket.io, ws, nats.js (for scalable event-driven messaging)
• API Versioning → express-version-route, Kong API Gateway

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Deployment & Scalability

• Kubernetes Orchestration → Kubernetes (K8s), Helm Charts
• Service Mesh → Istio, Linkerd, Cilium
• Auto-Scaling → Kubernetes HPA, KEDA (event-driven scaling)
• Infrastructure as Code → Terraform, Pulumi, Crossplane
• Blue-Green & Canary Deployments → ArgoCD, Flagger

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Compliance & Security Best Practices

• Data Encryption → crypto, AWS KMS, node-forge
• API Security (mTLS, OAuth2, JWT) → node-tls, passport, keycloak
• Secrets Management → HashiCorp Vault, AWS Secrets Manager, Doppler
• Audit Logs & Compliance → winston, PostgreSQL pgaudit, OpenTelemetry

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