Implementing Microservices with .NET Core and Angular

 Using (CQRS • Saga • Azure Service Bus • Circuit Breaker • Adapter • Patterns & Best Practices) 

TL;DR (What you'll build)

A cloud-ready microservices system where each microservice:

• Is a .NET Core Web API (REST) exposing bounded-capability endpoints.

• Uses CQRS: separate read model and write model (commands vs queries).

• Coordinates complex business workflows using SAGA (via Azure Service Bus).

• Communicates async via Azure Service Bus (topics/subscriptions or queues).

• Uses Circuit Breaker (Polly) + retry/backoff to improve resilience.

• Uses Adapter pattern for external systems and for infrastructure abstraction.

• Front-end is an Angular SPA calling an API Gateway (or BFF) that routes to microservices.

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Architecture overview (high level)

1. API Gateway / BFF (optional): Single public endpoint, routing, auth, aggregation.

2. Microservices (multiple): each with its own database (DB-per-service), own bounded context.

   • Example services: Orders, Payments, Inventory, Customers, Shipping.

3. Azure Service Bus: topics for publish/subscribe events, queues for commands/tasks.

4. CQRS: Commands handled by write-side; queries served by optimized read DB (e.g., read replica or denormalized store like CosmosDB/SQL).

5. Sagas: Orchestrate long-running transactions (compensations) via events/messages.

6. Polly: Circuit Breaker + Retry + Timeout for outbound HTTP/Bus calls.

7. Monitoring & Logging: Application Insights, centralized logs (ELK/Serilog sink).

8. CI/CD & Hosting: Build pipeline -> container images -> AKS / App Service.

Diagram (textual):

Angular SPA -> API Gateway -> Microservice A (Commands) -> Azure Service Bus topic
                                        -> Microservice B subscribes (Updates read DB)
Microservice A -> publishes events -> Azure Service Bus -> Saga Orchestrator -> other services

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Core design principles

• Single Responsibility & Bounded Contexts — keep microservices small and focused.

• DB-per-service — avoid shared DB to reduce coupling.

• Event-driven — communicate asynchronously where eventual consistency is acceptable.

• Idempotency — message handlers must be idempotent.

• Id-based correlation — include correlation IDs in messages for tracing.

• Resilience — use bulkheads, circuit breakers, retries, timeouts.

• Observability — structured logs, distributed tracing (W3C TraceContext).

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Key patterns & how to apply them

1. CQRS (Command Query Responsibility Segregation)

• Write side: handles commands (POST /orders → CreateOrderCommand). Validations and state changes happen here.

• Read side: optimized projection used for queries (GET /orders/123). Read DB is updated by event subscribers.

• Implementation:

  • Commands go to controllers → Command Handlers (MediatR is common).

  • After state change, publish domain event (to Azure Service Bus).

  • Event consumers update read model (denormalized tables or NoSQL).

Example files/folders:

/OrdersService
  /Commands
    CreateOrderCommand.cs
    CreateOrderCommandHandler.cs
  /Domain
    Order.cs
    OrderAggregate.cs
  /Events
    OrderCreatedEvent.cs
  /ReadModel
    OrderReadModel.cs
    OrderProjectionHandler.cs

2. Saga (long-running transactions)

• Use Saga to coordinate multi-step flows (e.g., order -> reserve inventory -> charge payment -> ship).

• Two approaches:

  • Choreography: each service reacts to events. Simple but can be hard to reason about for complex flows.

  • Orchestration: Saga Orchestrator service sends commands to participants and listens for replies/events. Easier to visualize and control compensations.

• Implementation with Azure Service Bus:

  • Orchestrator publishes ReserveInventoryCommand to a queue.

  • Inventory service replies InventoryReservedEvent or InventoryReserveFailedEvent.

  • Orchestrator then issues ChargePaymentCommand or CompensateOrderCommand.

• Always plan for compensation (rollback-like steps) when a later step fails.

3. Azure Service Bus (Messaging)

• Use Topics + Subscriptions for publish/subscribe; Queues for point-to-point commands.

• Message schema:

  • MessageId, CorrelationId, CausationId, MessageType, Payload.

• Use dead-letter queues for poison messages and implement retries & DLQ handling.

4. Circuit Breaker & Resilience (Polly)

• Wrap all outbound network calls (HTTP, DB, Service Bus operations) with retry + jittered backoff + circuit breaker.

• Typical policy: Retry (3 attempts, exponential backoff) + Circuit Breaker (open after 5 failures for 30s) + Timeout (5s).

• Example: use HttpClientFactory with Polly policies.

5. Adapter Pattern

• Use adapters to isolate external/specific client libs (e.g., Azure Service Bus SDK, Payment Gateway SDK) from your domain.

• Define an interface (e.g., IPaymentGateway) and implement StripeAdapter/DummyAdapter. This supports testability and swapping providers.

6. Repository + Unit of Work (when needed)

• Use repository for aggregate persistence; Unit of Work if multiple repositories within same DB transaction (but prefer small transactions).

7. Anti-Corruption Layer

• When integrating with legacy systems, use an adapter/anti-corruption layer to map incompatible models.

---

Concrete implementation steps

1. Set up projects

Solution example:

/MyEshop
  /src
    /ApiGateway (aspnet core)
    /Services
      /Orders.Api
      /Inventory.Api
      /Payments.Api
      /Saga.Orchestrator
    /Shared
      /Messaging (contracts)
      /Common (logging, exceptions)
  /ui
    /angular-spa

2. Shared contracts & DTOs

Create a Shared/Messaging project with message types (events/commands) used across services. Strongly-typed messages reduce coupling.

Example OrderCreatedEvent:

public record OrderCreatedEvent(Guid OrderId, Guid CustomerId, decimal Total, IEnumerable<OrderLineDto> Lines);

3. Implement CQRS in a service (Orders example)

• Use MediatR for intra-service command/handler pattern.

• Controller:

[HttpPost]
public async Task<IActionResult> Create([FromBody] CreateOrderRequest req)
{
    var cmd = new CreateOrderCommand(req.CustomerId, req.Lines);
    var result = await _mediator.Send(cmd);
    return CreatedAtAction(..., result.OrderId);
}

• CommandHandler:

public class CreateOrderCommandHandler : IRequestHandler<CreateOrderCommand, CreateOrderResult>
{
    private readonly IOrderRepository _repo;
    private readonly IMessageBus _bus; // adapter over Azure Service Bus

    public async Task<CreateOrderResult> Handle(CreateOrderCommand request, CancellationToken token)
    {
        var order = Order.Create(request.CustomerId, request.Lines);
        await _repo.AddAsync(order);
        await _repo.UnitOfWork.SaveChangesAsync();

        // publish event to bus
        await _bus.Publish(new OrderCreatedEvent(order.Id, order.CustomerId, order.Total, order.Lines));

        return new CreateOrderResult(order.Id);
    }
}

4. Publish/Subscribe (Azure Service Bus)

• Implement IMessageBus adapter that wraps Azure Service Bus ServiceBusClient.

• For publishing events:

public async Task Publish<T>(T @event) where T : class
{
    var message = JsonSerializer.Serialize(@event);
    await _sender.SendMessageAsync(new ServiceBusMessage(message) { MessageId = Guid.NewGuid().ToString() });
}

• For subscriptions, create background services (hosted services) to process messages and project read model.

5. Saga Orchestration (example flow)

• Orders publishes OrderCreatedEvent.

• Saga.Orchestrator subscribes. On OrderCreated:

  1. Send ReserveInventoryCommand to Inventory queue.

  2. Wait for InventoryReservedEvent or InventoryReserveFailedEvent.

  3. If reserved, send ChargePaymentCommand to Payments.

  4. If payment succeeds, send ShipOrderCommand to Shipping.

  5. If any step fails, run compensating actions (e.g., ReleaseInventoryCommand, RefundPaymentCommand) and mark order Failed.

Orchestrator pattern: implement state persistence for saga instances (e.g., in CosmosDB/SQL). Store Saga state keyed by CorrelationId.

6. Circuit Breaker with HttpClientFactory + Polly

Register in Program.cs:

services.AddHttpClient("payments", client => { client.BaseAddress = new Uri(config["Payments:BaseUrl"]); })
  .AddPolicyHandler(GetRetryPolicy())
  .AddPolicyHandler(GetCircuitBreakerPolicy());

IAsyncPolicy<HttpResponseMessage> GetRetryPolicy() =>
  HttpPolicyExtensions.HandleTransientHttpError()
    .WaitAndRetryAsync(3, retryAttempt => TimeSpan.FromSeconds(Math.Pow(2, retryAttempt)));

IAsyncPolicy<HttpResponseMessage> GetCircuitBreakerPolicy() =>
  HttpPolicyExtensions.HandleTransientHttpError()
    .CircuitBreakerAsync(5, TimeSpan.FromSeconds(30));

7. Angular front-end (simple BFF pattern)

• Angular calls API Gateway/BFF endpoints which route to microservices.

• Use typed services, interceptors for auth (JWT) and correlation headers.

Example Angular service:

@Injectable({ providedIn: 'root' })
export class OrdersService {
  constructor(private http: HttpClient) {}
  createOrder(order: CreateOrderDto) {
    return this.http.post<ApiResponse<OrderView>>('/api/orders', order);
  }
}

Add an HTTP interceptor to send x-correlation-id header and Authorization bearer token.

8. Idempotency & Message deduplication

• Keep ProcessedMessage table with MessageId to ignore duplicate message deliveries.

• Use Service Bus message-id + dedupe logic.

9. Testing

• Unit test command handlers and domain logic.

• Integration tests for message flows (use in-memory or test instance of Service Bus or use the Azure Service Bus emulator).

• Contract tests for message contracts.

10. Observability, Monitoring & Health

• Use Application Insights (or OpenTelemetry) for distributed tracing and metrics.

• Add Health Checks endpoints and Kubernetes liveness/readiness probes.

• Structured logging with Serilog, sink to central store.

---

Deployment & CI/CD (short)

• Dockerize each service.

• Build pipeline: build -> test -> image -> push to ACR.

• Deploy pipeline: pull image -> AKS (Kubernetes manifests) or Azure App Service.

• Use Helm charts for Kubernetes; include config via ConfigMaps and secrets via Azure Key Vault.

• Use canary / blue-green with ingress controller and feature flags (LaunchDarkly or open-source).

---

Practical tips & pitfalls

• Do not share a single database across services — this creates high coupling.

• Prefer eventual consistency; design UIs to show pending states (e.g., "Payment Processing").

• Compensation is not rollback — design compensating actions carefully.

• Keep messages small and versionable — maintain backward compatibility.

• Start with choreography for simple flows; move to orchestrator for complex flows requiring centralized control.

• Use feature toggles while deploying new message flows.

---

Minimal code sample: publish event to Service Bus (adapter)

public interface IMessageBus
{
    Task PublishAsync<T>(T @event, string topicName);
}

public class AzureServiceBusAdapter : IMessageBus
{
    private readonly ServiceBusClient _client;
    public AzureServiceBusAdapter(ServiceBusClient client) => _client = client;

    public async Task PublishAsync<T>(T @event, string topicName)
    {
        var sender = _client.CreateSender(topicName);
        var body = JsonSerializer.Serialize(@event);
        var msg = new ServiceBusMessage(body) { MessageId = Guid.NewGuid().ToString() };
        msg.ApplicationProperties["MessageType"] = typeof(T).FullName;
        await sender.SendMessageAsync(msg);
    }
}

---

Folder structure suggestion (service-level)

/Orders.Api
  /Controllers
  /Commands
  /CommandHandlers
  /Domain
  /Events
  /Projections
  /Infrastructure
     /Persistence
     /Messaging (ServiceBus adapter)
     /HttpClients (adapters)
  /Services (business services)
  /Tests

---

Checklist before go-live

• Message contracts versioned & documented.

• Idempotency & DLQ handled.

• Circuit breakers instrumented.

• Health checks + readiness gates.

• Logging and distributed tracing configured.

• Saga persistence & compensations tested.

• Secure secrets (Key Vault) and communication (TLS, JWT).

---

Suggested next steps (practical small milestones)

1. Create a Shared.Messaging project with event/command contracts.

2. Scaffold Orders service with basic create order command and publisher (no Saga yet).

3. Create Inventory service subscriber to update read model.

4. Add Azure Service Bus adapter and test end-to-end message flow locally (or in dev subscription).

5. Implement a simple saga orchestrator for a 3-step flow (inventory → payment → shipping).

6. Add Polly policies and instrument logging/tracing.

7. Dockerize and deploy to a dev cluster.

🚀 Step-by-Step Guide: Deploying Applications to Azure Kubernetes Service (AKS) with Docker

 When you’re building modern applications, you need scalability, reliability, and automation. That’s where Docker and Kubernetes come in. Docker helps you containerize applications, while Azure Kubernetes Service (AKS) helps you manage, scale, and deploy those containers in the Azure cloud.

In this article, we’ll cover how to go from local code (Git repository) to a running application in AKS, with a detailed step-by-step tutorial. This guide will help you deploy your app seamlessly in Azure Cloud using Docker and Kubernetes.

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🔹 Why Use Azure Kubernetes Service (AKS)?

• Scalability – Easily scale applications up or down.

• High availability – AKS ensures your application is always running.

• Integration – Works with Azure services like Azure Monitor, Azure DevOps, Azure Container Registry (ACR).

• Cost-effective – Pay only for worker nodes, not for the control plane.

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🔹 Prerequisites

Before starting, ensure you have:

• An Azure Subscription (with permissions to create resources).

• Azure CLI installed (az --version).

• Docker Desktop or Docker CLI installed locally.

• Kubectl CLI installed for Kubernetes commands.

• A working Git repository or local code with a Dockerfile.

👉 SEO Keywords: Docker on Azure, Azure CLI setup, Deploy Kubernetes cluster in Azure

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🔹 Step 1: Containerize Your Application with Docker

1. In your project root, create a Dockerfile. Example for ASP.NET Core:

FROM mcr.microsoft.com/dotnet/sdk:7.0 AS build
WORKDIR /src
COPY ["MyApp/MyApp.csproj", "MyApp/"]
RUN dotnet restore "MyApp/MyApp.csproj"
COPY . .
WORKDIR "/src/MyApp"
RUN dotnet publish "MyApp.csproj" -c Release -o /app/publish

FROM mcr.microsoft.com/dotnet/aspnet:7.0 AS final
WORKDIR /app
COPY --from=build /app/publish .
EXPOSE 80
ENTRYPOINT ["dotnet", "MyApp.dll"]

2. Build and test locally:

docker build -t myapp:v1 .
docker run -p 8080:80 myapp:v1

---

🔹 Step 2: Push Docker Image to Azure Container Registry (ACR)

AKS needs images from a container registry. Using Azure Container Registry (ACR) is secure and simple.

# Login to Azure
az login

# Create resource group
az group create --name myResourceGroup --location eastus

# Create ACR (name must be unique)
az acr create --resource-group myResourceGroup --name myACRname --sku Standard

# Login to ACR
az acr login --name myACRname

# Tag and push image
ACR_LOGIN=$(az acr show -n myACRname -g myResourceGroup --query loginServer -o tsv)
docker tag myapp:v1 $ACR_LOGIN/myapp:v1
docker push $ACR_LOGIN/myapp:v1

---

🔹 Step 3: Create Azure Kubernetes Service (AKS) Cluster

az aks create \
  --resource-group myResourceGroup \
  --name myAKSCluster \
  --node-count 2 \
  --enable-addons monitoring \
  --generate-ssh-keys \
  --enable-managed-identity

---

🔹 Step 4: Connect AKS with ACR

Attach your ACR to AKS so the cluster can pull images securely:

ACR_ID=$(az acr show -n myACRname -g myResourceGroup --query id -o tsv)
az aks update -g myResourceGroup -n myAKSCluster --attach-acr $ACR_ID

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🔹 Step 5: Deploy Your Application to AKS

Create a Kubernetes manifest file (deployment.yaml):

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: myacrname.azurecr.io/myapp:v1
        ports:
        - containerPort: 80
---
apiVersion: v1
kind: Service
metadata:
  name: myapp-service
spec:
  type: LoadBalancer
  selector:
    app: myapp
  ports:
  - port: 80
    targetPort: 80

Deploy using kubectl:

az aks get-credentials -g myResourceGroup -n myAKSCluster
kubectl apply -f deployment.yaml
kubectl get pods
kubectl get svc myapp-service

Copy the EXTERNAL-IP and open it in a browser. 🎉 Your app is live in Azure Cloud!

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🔹 Step 6: Production Enhancements

• Use Ingress + NGINX Controller for domain-based routing.

• Enable Azure Monitor for logs and performance tracking.

• Configure readiness and liveness probes for high availability.

• Automate builds using Azure DevOps or GitHub Actions CI/CD pipelines.

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✅ Conclusion

Deploying applications with Docker and Azure Kubernetes Service (AKS) might sound complex, but once you understand the flow, it becomes straightforward:

1. Code → Dockerize

2. Push → Azure Container Registry

3. Cluster → Create AKS

4. Deploy → With Kubernetes manifests

This step-by-step guide helps you move from local development to enterprise-grade deployments in the cloud. With AKS, your applications become scalable, secure, and production-ready.