Building Scalable .NET Microservices

Microservices architecture has become the go-to approach for building large, complex systems that need to scale independently. In this post, I'll share insights from building production microservice systems with .NET Core.

The Challenge

Traditional monolithic applications become increasingly difficult to maintain and scale as they grow. Teams step on each other's toes, deployments become risky, and scaling specific features becomes impossible. Microservices solve these problems by breaking applications into small, independent services.

Service Boundaries

The first challenge is identifying proper service boundaries. A service should:

- Have a single responsibility - Own its data (no shared databases between services) - Communicate through well-defined APIs - Be deployable independently

I typically start by analyzing domain boundaries and identifying natural seams in the application. Don't over-engineer earlyâ€”start with 2-3 services and refactor as needs become clear.

Communication Patterns

For synchronous communication, REST APIs or gRPC work well. gRPC is particularly powerful for service-to-service communication due to its performance characteristics.

For asynchronous communication, message queues like RabbitMQ or Azure Service Bus decouple services and improve resilience. A service failure won't cascade through your system if you're using async messaging.

Containerization

Docker is essential for microservices. Each service should have a simple Dockerfile that captures all dependencies. Multi-stage builds keep images lean:

```dockerfile FROM mcr.microsoft.com/dotnet/sdk:8.0 AS build WORKDIR /src COPY ["MyService.csproj", "."] RUN dotnet restore COPY . . RUN dotnet publish -c Release -o /app

FROM mcr.microsoft.com/dotnet/runtime:8.0 WORKDIR /app COPY --from=build /app . ENTRYPOINT ["dotnet", "MyService.dll"] ```

Deployment & Orchestration

Azure DevOps combined with Docker makes deployment straightforward. Build a service in a pipeline, push to container registry, and deploy to Kubernetes or ACI.

Key lessons learned: - Implement health checks from day one - Use proper logging and distributed tracing (Application Insights) - Plan for resilienceâ€”timeouts, retries, circuit breakers - Monitor resource usage and auto-scale based on demand

Microservices add operational complexity, but when done right, the benefits in scalability and team velocity are substantial.