Microservices & Event-Driven Architecture (EDA) Mastery

Asynchronous Communication: Message Brokers (RabbitMQ/Kafka)

1 Views Updated 5/4/2026

Async Communication: Decoupling

The secret to high availability is Asynchronous Communication. If Service B is down, Service A shouldn't care—it just drops a message in a queue and moves on.

1. RabbitMQ vs Kafka

  • RabbitMQ (Smart Broker): Best for complex routing. It handles the logic of ensuring messages get to the right place. Once read, a message is usually deleted. High reliability for task distribution.
  • Kafka (Smart Client): Best for high-throughput 'Stream Processing'. It's essentially a distributed log. Messages stay in Kafka for days, allowing multiple services to 'Replay' the data. Perfect for analytics and audit trails.

2. MassTransit (The .NET Secret)

Don't call RabbitMQ or Azure Service Bus APIs directly. Use **MassTransit**. It's an abstraction layer that handles retries, poison pill queues (Dead Letter Queues), and the Saga pattern for you. It allows you to switch your broker from RabbitMQ to Kafka with just a config change.

4. Interview Mastery

Q: "What is 'Backpressure' in a messaging system?"

Architect Answer: "Backpressure is when the consumer is slower than the producer. If you send 1,000 messages a second but your DB can only handle 100, the queue will grow until the server crashes. We handle this through **Rate Limiting** on the consumer, or by automatically scaling out more consumer instances (KEDA) to handle the load."

Microservices & Event-Driven Architecture (EDA) Mastery
1. Foundations of Microservices
The Monolith to Microservices transition: When and why? Domain Driven Design (DDD): Bounded Contexts and Aggregates Database Per Service: Managing data consistency Service Discovery and Health Checks in .NET
2. Communication Patterns
Synchronous Communication: HTTP/gRPC and Service Mesh Asynchronous Communication: Message Brokers (RabbitMQ/Kafka) API Gateways: YARP (Yet Another Reverse Proxy) vs Ocelot Protobuf and Shared Contracts: Managing breaking changes
3. Event-Driven Architecture (EDA)
Introduction to EDA: Producers, Consumers, and Topics The Publisher/Subscriber Pattern in .NET Event Sourcing: Capturing every state change CQRS (Command Query Responsibility Segregation) with MediatR
4. Distributed Transactions & Resiliency
The Saga Pattern: Orchestration vs Choreography The Outbox Pattern: Ensuring reliable message delivery Idempotency: Preventing duplicate message processing Distributed Locking with Redis (Redlock)
5. Observability & Monitoring
Distributed Tracing with OpenTelemetry Centralized Logging: ELK Stack (Elasticsearch, Logstash, Kibana) Metrics and Dashboards: Prometheus and Grafana Correlation IDs: Tracking requests across services
6. Security & Identity
Centralized Authentication: IdentityServer4 & Duende Identity OAuth2 and OIDC Flow for Microservices API Key Management and Rate Limiting Mutual TLS (mTLS) for Internal Service-to-Service Security
7. Infrastructure & Deployment
Containerization: Production-grade Dockerfiles Kubernetes for .NET: Pods, Services, and Ingress Helm Charts: Managing complex deployments Blue-Green and Canary Deployments in K8s
8. FAANG Microservices Case Studies
Case Study: Designing a Global Notification Engine (Reliability at Scale) Case Study: Building a High-Performance Logging Pipeline (PB/Day)