Architecture Showcase
Microservices Architecture Showcase
A conceptual, end-to-end microservices reference architecture — gateway, services, messaging, caching, and orchestration.
- ASP.NET Core
- RabbitMQ
- Redis
- Docker
- Kubernetes
- SQL Server
- JWT
Transparency note: This is explicitly an architecture showcase — a conceptual reference design, not a claimed production deployment. Its purpose is to demonstrate distributed systems thinking beyond CRUD applications.
Overview
An engineering showcase rather than a product: a reference architecture demonstrating how I design distributed .NET systems. It maps the full request lifecycle — from an API gateway through authenticated services to asynchronous messaging and polyglot persistence — using the infrastructure I work with: RabbitMQ, Redis, Docker, Kubernetes, and SQL Server.
The problem
Monoliths are simple until they aren't: one codebase, one database, and one deployment mean every team, feature, and scaling concern is coupled. Distributed architecture solves this — but only when service boundaries, communication patterns, and failure modes are designed deliberately.
The solution
A reference design where an API gateway fronts independently deployable ASP.NET Core services, synchronous calls are reserved for queries, state changes flow through RabbitMQ events, Redis absorbs read pressure, and each service owns its data. Docker and Kubernetes handle packaging, scaling, and self-healing.
System architecture
API Gateway
Single entry point — routing, rate limits, auth handoff
Authentication Service
Issues and validates JWT tokens
User Service
Profile domain, owns its own database
Order / Business Service
Core domain logic, publishes events
SQL Server (per service)
Database-per-service ownership
Architecture
Gateway-fronted microservices with JWT-based auth, event-driven messaging over RabbitMQ, Redis caching, database-per-service on SQL Server, and Docker/Kubernetes for orchestration.
Key features
- API Gateway as the single entry point — routing, auth handoff, rate limiting
- Authentication service issuing JWT tokens consumed by all services
- Domain services (User, Order/Business) with database-per-service ownership
- Event-driven communication over RabbitMQ for state changes
- Redis distributed caching for hot read paths
- Containerized services orchestrated by Kubernetes
- Independent scaling and deployment per service
My contribution
- Designed the reference architecture and service boundaries
- Defined synchronous vs. event-driven communication rules
- Specified the caching and cache-invalidation strategy
- Mapped the containerization and orchestration approach
Technical challenges
Where to draw service boundaries
Too fine-grained and every operation becomes a distributed transaction; too coarse and you've rebuilt the monolith. Boundaries follow business capabilities — each service owns one domain and its data outright.
Consistency without shared databases
With database-per-service, cross-service consistency is eventual by design. Domain events over RabbitMQ propagate changes, and consumers are built idempotent so redelivery is safe.
Cache correctness
Redis accelerates reads only if invalidation is right. The design pairs cache-aside reads with event-driven invalidation: the same events that sync services also evict stale cache entries.
Outcome
A complete architectural narrative demonstrating distributed systems design: deliberate boundaries, asynchronous messaging, caching strategy, and operational thinking with Docker and Kubernetes.