Microservices Mastery

Kubernetes Architecture: Pods, Services, and Deployments

1 Views Updated 5/4/2026

Kubernetes (K8s) Architecture

While Docker runs containers, Kubernetes orchestrates them. It is the "Operating System" for the cloud. K8s handles scaling, self-healing (restarting crashed containers), and load balancing across a cluster of servers.

1. Core Concepts

  • Pod: The smallest unit in K8s. It contains one or more containers (usually just your .NET API).
  • Deployment: Defines the "State" you want. If you say "I want 3 replicas," and a server dies, K8s will automatically start a new Pod on a healthy server to maintain that number.
  • Service: An internal load balancer. It provides a single stable IP/DNS for a group of Pods.
  • Ingress: The "Gatekeeper" that allows external traffic from the internet into your cluster.

2. Self-Healing Magic

If your .NET process hangs or runs out of memory, K8s detects it via a Liveness Probe and physically kills/restarts the container for you. This allows for "Zero-Downtime" 2 AM recoveries.

4. Interview Mastery

Q: "Why can't we just give a Pod a static IP address?"

Architect Answer: "Pods in Kubernetes are **Ephemeral** (Temp). They are born and they die constantly during scaling or updates. Every time a Pod restarts, it gets a brand new IP address. If your API tried to talk to 'Pod-123' via IP, it would break within minutes. This is why we use **Services**. A Service has a static IP that never changes; it acts as a permanent proxy that routes traffic to whichever Pods happen to be alive at that moment."

Microservices Mastery
1. Distributed Systems Fundamentals
Monolith vs Microservices: When to migrate? The 12-Factor App Methodology for Cloud-Native Apps Database Per Service: Handling distributed data consistency
2. Containerization & Orchestration
Docker Essentials: Building efficient .NET images Docker Compose: Orchestrating a multi-service environment Kubernetes Architecture: Pods, Services, and Deployments K8s ConfigMaps & Secrets: Managing environment variables Helm Charts: Packaging your microservices for K8s
3. Service Communication
Synchronous vs Asynchronous Communication: Pros and Cons REST APIs in a Microservices World: Best Practices Mastering gRPC: High-performance binary communication API Gateways: Implementing Ocelot for single-entry access BFF Pattern: Backend-for-Frontend (Mobile vs Web)
4. Event-Driven Architecture
Message Brokers: Introduction to RabbitMQ & Azure Service Bus Pub/Sub Pattern: Implementing MassTransit for .NET The Outbox Pattern: Ensuring 100% data consistency Dead Letter Queues: Handling message failure gracefully Distributed Transactions: The Saga Pattern (State Machines)
5. Resilience & Scalability
Distributed Caching with Redis: Optimizing global state Service Discovery: IdentityServer4 & Consul Load Balancing: Nginx vs Ingress Controllers The Sidecar Pattern: Offloading cross-cutting concerns
6. Observability & Security
Distributed Logging with Serilog & SEQ Distributed Tracing: OpenTelemetry & Jaeger Health Checks: Monitoring system vitals in real-time OAuth2 & OpenID Connect: Centralized Identity (AuthN/AuthZ) Rate Limiting & Throttling: Protecting your services
7. Advanced Cloud Topics
Infrastructure as Code (IaC): Introduction to Terraform CI/CD Pipelines for Microservices (GitHub Actions/Azure DevOps) C# Architect Interview: Microservices & System Design Focus