REST APIs Archives

A Comprehensive Technical Guide for Enterprise Architects

Executive Summary

Deploying .NET Core microservices on Azure Kubernetes Service (AKS) has become the enterprise standard for building scalable, resilient, cloud-native applications within the Microsoft ecosystem.

For senior .NET developers and architects, mastering this architecture unlocks high-impact cloud engineering roles, where organizations expect deep expertise in:

Containerization
Kubernetes orchestration
Distributed systems design
Infrastructure as Code (IaC)

AKS brings together:

ASP.NET Core high-performance runtime
Kubernetes self-healing orchestration
Microsoft Azure managed cloud services

The result is a platform capable of automatic scaling, rolling deployments, service discovery, distributed tracing, and workload isolation—all essential for modern enterprise systems.

Core Architecture: Internal Mechanics & Patterns

The Microservices Foundation on AKS

AKS provides a managed Kubernetes control plane, removing the operational burden of managing masters while preserving full control over worker nodes and workloads.

A production-grade AKS microservices architecture typically includes:

Containerized services
Each microservice runs as a Docker container inside Kubernetes Pods.
Azure CNI with Cilium
Pods receive VNet IPs, enabling native network policies, observability, and zero-trust networking.
Ingress + API Gateway pattern
A centralized ingress exposes HTTP/HTTPS entry points.
Externalized state
Stateless services persist data to Azure SQL, Cosmos DB, Redis, or Service Bus.

API Gateway & Request Routing

The Ingress Controller acts as the edge gateway, handling:

Request routing
SSL/TLS termination
Authentication & authorization
Rate limiting and IP filtering
Request aggregation

For large enterprises, multiple ingress controllers are often deployed per cluster to isolate environments, tenants, or workloads.

Namespace Strategy & Service Organization

Namespaces should align with bounded contexts (DDD):

order-fulfillment
payments
inventory
platform-observability

This provides:

Clear RBAC boundaries
Resource quotas per domain
Improved operational clarity

Communication Patterns

A hybrid communication model is recommended:

Synchronous (REST / HTTP)

Read-heavy operations
Immediate responses

Asynchronous (Messaging)

State changes
Long-running workflows

Technologies like RabbitMQ + MassTransit enable loose coupling and fault tolerance while avoiding cascading failures.

Service Discovery & Health Management

Kubernetes Services provide stable DNS-based discovery
Liveness probes restart failed containers
Readiness probes control traffic flow
ASP.NET Core Health Checks integrate natively with Kubernetes

Technical Implementation: Modern .NET Practices

Health Checks (ASP.NET Core)

builder.Services.AddHealthChecks()
    .AddCheck("self", () => HealthCheckResult.Healthy());

Kubernetes Deployment (Production-Ready)

apiVersion: apps/v1
kind: Deployment
metadata:
  name: order-service
  namespace: order-fulfillment
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
  selector:
    matchLabels:
      app: order-service
  template:
    metadata:
      labels:
        app: order-service
    spec:
      containers:
        - name: order-service
          image: myregistry.azurecr.io/order-service:1.0.0
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: "250m"
              memory: "256Mi"
            limits:
              cpu: "500m"
              memory: "512Mi"
          readinessProbe:
            httpGet:
              path: /health/ready
              port: 8080
          livenessProbe:
            httpGet:
              path: /health/live
              port: 8080

Distributed Tracing (Application Insights + OpenTelemetry)

builder.Services.AddApplicationInsightsTelemetry();

builder.Services.AddOpenTelemetry()
    .WithTracing(tracing =>
    {
        tracing
            .AddAspNetCoreInstrumentation()
            .AddHttpClientInstrumentation()
            .AddAzureMonitorTraceExporter();
    });

This enables end-to-end request tracing across microservices.

Resilient Service-to-Service Calls (Polly)

builder.Services.AddHttpClient<IOrderClient, OrderClient>()
    .AddTransientHttpErrorPolicy(p =>
        p.WaitAndRetryAsync(3, retry =>
            TimeSpan.FromSeconds(Math.Pow(2, retry))))
    .AddTransientHttpErrorPolicy(p =>
        p.CircuitBreakerAsync(5, TimeSpan.FromSeconds(30)));

Event-Driven Architecture (MassTransit + RabbitMQ)

builder.Services.AddMassTransit(x =>
{
    x.AddConsumer<OrderCreatedConsumer>();

    x.UsingRabbitMq((context, cfg) =>
    {
        cfg.Host("rabbitmq://rabbitmq");
        cfg.ConfigureEndpoints(context);
    });
});

public class OrderCreatedConsumer : IConsumer<OrderCreatedEvent>
{
    public async Task Consume(ConsumeContext<OrderCreatedEvent> context)
    {
        // Persist order and publish downstream events
    }
}

Distributed Caching (Redis – Cache-Aside)

builder.Services.AddStackExchangeRedisCache(options =>
{
    options.Configuration =
        builder.Configuration.GetConnectionString("Redis");
});

Scaling & Performance

Horizontal Pod Autoscaler (HPA)

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
spec:
  minReplicas: 3
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70

Common Pitfalls (From Real Systems)

Shared databases across services
Long synchronous REST chains
No observability or tracing
Poor CPU/memory limits
Ignoring network policies

Optimization Tricks Used in Production

Spot node pools for non-critical workloads (~70% cost savings)
Pod Disruption Budgets
Vertical Pod Autoscaler
Docker layer caching
Fine-tuned readiness vs liveness probes
GitOps with Terraform + Argo CD

When AKS Microservices Make Sense

Scenario	Recommendation
10+ services	✅ AKS
High traffic	✅ AKS
Multiple teams	✅ AKS
Small MVP	❌ Monolith
Strong ACID needs	❌ Microservices

Final Takeaway

AKS + .NET Core is a power tool—not a starter kit.

When used correctly, it delivers scalability, resilience, and deployment velocity unmatched by traditional architectures. When misused, it introduces unnecessary complexity.

For enterprise systems with multiple teams, frequent releases, and global scale, this architecture is absolutely worth the investment.