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Feature Inventory & Architectural Traces
Core Subsystems Overview
| Feature ID | Feature Name | Primary Module References | Description |
|---|---|---|---|
| F1 | Distributed Authentication & RBAC | 01-authentication/, 07-security/ | Dual JWT access/refresh token rotation, role/permission authorization, token blacklists. |
| F2 | Real-Time WebSockets & Event Mesh | 05-realtime-communication/ | Socket.IO room multiplexing, Redis pub/sub backplane, user presence tracking. |
| F3 | Caching, Queues & Background Workers | 08-caching/, 09-jobs-queues/ | Redis cache-aside caching, BullMQ asynchronous job queues with exponential backoff. |
| F4 | Cryptography & FinTech Ledger Patterns | 18-cryptography/, 19-payments-fintech/ | Double-entry accounting ledger, AES-256 data encryption, idempotency key locking. |
| F5 | Multi-Tenant SaaS & Observability Mesh | 10-observability/, 30-saas-multitenancy/ | Scoped tenant database routing, Pino structured logging, Prometheus metrics endpoints. |
F1: Distributed Authentication & RBAC
Implements secure user onboarding, password hashing with bcrypt, stateless JWT issuance, refresh token rotation, and fine-grained permission enforcement.
Say It Out Loud
"In
01-authentication, I implemented enterprise authentication. It utilizes a dual-token strategy: a short-lived 15-minute JWT access token sent in the Authorization header, and an httpOnly, SameSite refresh token cookie. To support instant revocation without sacrificing statelessness, logged-out tokens are stored in Redis with a TTL matching the token lifetime, ensuring compromised sessions are revoked immediately."
F2: Real-Time WebSockets & Event Mesh
Bi-directional real-time communication layer supporting horizontal scaling across multiple Node.js instances via Redis pub/sub.
Say It Out Loud
"In
05-realtime-communication, I built a horizontally scalable WebSocket mesh using Socket.IO and the Redis adapter. When a message is sent in a chat room, the local server publishes the event to Redis, which broadcasts it across all Node instances in the cluster so clients connected to any server receive the event instantly."
F3: Caching, Queues & Background Workers
High-throughput caching and job processing layer mitigating database strain under heavy loads.
Say It Out Loud
"In
08-cachingand09-jobs-queues, I implemented a resilient caching and background processing architecture. Reads query Redis using the cache-aside pattern, while heavy asynchronous workloads—like invoice generation and email dispatch—are pushed to BullMQ queues with exponential backoff and dead-letter queues."
F4: Cryptography & FinTech Ledger Patterns
Double-entry general ledger architecture guaranteeing zero money creation bugs.
Say It Out Loud
"In
19-payments-fintech, I engineered a double-entry financial ledger. Every fund movement generates two atomic ledger entries—a debit and a credit. Balances are derived from immutable journal entries, preventing race-condition overdrafts and ensuring full financial auditability."
F5: Multi-Tenant SaaS & Observability Mesh
Dynamic database connection management for multi-tenant SaaS paired with structured logging and Prometheus metrics.
Say It Out Loud
"In
30-saas-multitenancyand10-observability, I built a multi-tenant SaaS architecture with dynamic connection pooling. Queries are strictly scoped to the authenticated tenant, while Pino and Prometheus record request durations, error rates, and active database connection metrics."