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)
Microservices & Event-Driven Architecture (EDA) Mastery

The Monolith to Microservices transition: When and why?

1 Views Updated 5/4/2026

Scaling Architecture: The Transition

Microservices are not a "Goal"; they are a Solution to the problems of scale and team velocity. Moving to microservices too early is the #1 reason why startups fail technically.

1. The Monolith's Strengths

A monolith is simple to deploy, easy to debug, and has zero network latency between components. If your team is small (< 10 people) and your user base is growing, stick with a **Modular Monolith**. Only split when the pain of coordinating deployments between 5 teams becomes unbearable.

2. The "Decomposition" Signal

When do you split?

  • **Scale Contention:** One part of the app (e.g., Image Processing) needs 100 servers, while the rest needs 2.
  • **Team Independence:** Team A is waiting for Team B to finish their testing before they can deploy.
  • **Fault Isolation:** If the 'Reporting' module crashes, the 'Payment' module should stay online.

4. Interview Mastery

Q: "What are the biggest 'Costs' of moving to microservices?"

Architect Answer: "The 'Tax' of microservices is **Operational Complexity**. You now have distributed data, network failure points, complex security (JWT/mTLS), and the need for advanced observability (OpenTelemetry). You must invest heavily in DevOps and automation to survive. If you don't have a strong CI/CD and monitoring strategy, microservices will slow you down, not speed you up."

Next Part
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)