Microservices & Event-Driven Architecture (EDA) Mastery

Kubernetes for .NET: Pods, Services, and Ingress

1 Views Updated 5/4/2026

Architecting for Kubernetes

Kubernetes (K8s) is the "Operating System" for microservices. It handles Scheduling, Healing, and Scaling so you don't have to.

1. The Pod Lifecycle

A Pod is the smallest unit in K8s. It can contain one or more containers. In .NET development, we usually have the app container and a 'Sidecar' for logging or service mesh. **Architect Rule:** Never deploy a bare Pod; always use a **Deployment** to ensure K8s replaces the pod if it crashes.

2. Services and Ingress

  • Service (ClusterIP): Provides a stable DNS name for internal communication between pods.
  • Ingress: The 'Door' to the cluster. It manages external HTTP traffic and handles SSL termination.

3. Resource Quotas

Always define **Requests** and **Limits** for CPU and Memory in your YAML. Without them, one 'Greedy' microservice can consume all the resources on a node, causing other services to be evicted and triggering a cluster-wide failure.

4. Interview Mastery

Q: "How does K8s handle 'Zero-Downtime' deployments?"

Architect Answer: "Through **Rolling Updates**. K8s starts a new V2 pod, waits for its 'Readiness Probe' to pass, and only then does it stop an old V1 pod. It repeats this until all pods are V2. This ensures that there is always a healthy pod available to handle user traffic during the transition."

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)