Designing Scalable and Reliable Cloud-Native Solutions with .NET Core and AWS

Introduction

Modern cloud-native applications must be secure, scalable, observable, and cost-efficient. In this post, we explore how to design such systems using .NET Core and AWS, applying battle-tested architectural principles like separation of concerns, loose coupling, pay-per-use services, and automation.

✅ Secure API Endpoints and Data Protection

Security is foundational. A strong security posture in AWS starts with protecting APIs and securing data both in-transit and at-rest.

• API Gateway for managed, throttled, and secured endpoints
• ACM for TLS/mTLS certificates
• Cognito or Keycloak to issue JWT tokens and manage users, roles, sessions
• mTLS for service-to-service authentication
• KMS to encrypt sensitive data and secrets at rest
• Secrets Manager to store keys, rotate credentials, and reduce hardcoded secrets

🎯 Delivering SPAs with S3, CloudFront and WAF

Single Page Applications (React, Angular, Vue) can be delivered efficiently using:

• S3 static website hosting with proper MIME types and versioning
• CloudFront for caching, Brotli/GZip compression, and global delivery
• Invalidation rules for cache busting during CI/CD
• AWS WAF for:
  • IP reputation filters
  • SQL Injection and XSS protections
  • Rate limiting and geo-blocking

🧩 Loose Coupling via Event-Driven Architecture

Loose coupling allows teams to work independently and systems to scale modularly.

• EventBridge to decouple services using events
• SNS/SQS for pub-sub and queue-based messaging
• CQRS pattern to separate commands from queries, reducing coupling between reads and writes
• Services communicate asynchronously and remain autonomous

🔍 Observability and Diagnostics

Build observability for cloud-native microservices in AWS using both infrastructure and application-level metrics:

• CloudWatch Logs and CloudWatch Metrics for application insights
• Alarms to monitor thresholds and notify via SNS
• X-Ray for distributed tracing
• ServiceLens to map bottlenecks and visualize dependencies
• Instrument applications with structured logs and correlation IDs

You can use the Serilog package and configure it to write logs to CloudWatch directly:

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using Amazon;
using Serilog;
using Serilog.Sinks.AwsCloudWatch;
using Amazon.CloudWatchLogs;

var logGroupName = "MyAppLogs";

var options = new CloudWatchSinkOptions
{
    LogGroupName = logGroupName,
    Region = RegionEndpoint.USEast1.SystemName,
    TextFormatter = new Serilog.Formatting.Compact.RenderedCompactJsonFormatter(),
    MinimumLogEventLevel = Serilog.Events.LogEventLevel.Information
};

Log.Logger = new LoggerConfiguration()
    .WriteTo.Console()
    .WriteTo.AmazonCloudWatch(options)
    .CreateLogger();

var builder = WebApplication.CreateBuilder(args);
builder.Host.UseSerilog();

⚙️ Scalable from Day One

Architect systems to scale seamlessly based on load:

• ECS Fargate for containerized workloads, scaling via CPU/RAM thresholds
• AWS Lambda with .NET AOT for minimal cold-start and high concurrency
• Aurora Serverless v2 or DynamoDB for elastic databases
• Step Functions to coordinate complex workflows without servers

🛡️ Reliability and Fault Tolerance

Build for failure by embracing resilient design patterns:

• Multi-AZ deployment using Application Load Balancer (ALB)
• RDS, Aurora, EFS backups, snapshots and failovers
• SQS with DLQs, Lambda retries, exponential backoff
• Use Polly in .NET for retry/circuit breaker logic
• Health checks and auto-recovery mechanisms in ECS and Lambda

You can add Microsoft.AspNetCore.Diagnostics.HealthChecks to your project as well as checks for each required service like AspNetCore.HealthChecks.Aws.S3 or AspNetCore.HealthChecks.SqlServer. Then you can configure it like this:

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builder.Services.AddHealthChecks()
    .AddCheck("self", () => HealthCheckResult.Healthy())
    .AddSqlServer(builder.Configuration.GetConnectionString("DefaultConnection"), name: "sql")
    .AddUrlGroup(new Uri("https://example.com"), name: "external-api");
var app = builder.Build();
app.MapHealthChecks("/health/live");     // Liveness
app.MapHealthChecks("/health/ready");    // Readiness
app.Run();

In case you are not familiar with health checks, here is a summary of the main types, their purposes, and how they are used in cloud-native systems:

ALB: Application Load Balancer
DLQ: Dead Letter Queue
DI: Dependency Injection
K8s: Kubernetes
ECS: Elastic Container Service
LB: Load Balancer
ETL: Extract, Transform, Load (data processing pipelines)
DBA: Database Administrator

💸 Pay-Per-Use and Cost Optimization

Only pay for what you use:

• Lambda, API Gateway, S3, Dynamo On-Demand, Aurora Serverless
• Tune logging and metrics using sampling, filtering and retention policies
• Apply FinOps practices:
  • Resource tagging for cost attribution
  • Budget alerts and forecasting
  • Automate unused resource cleanup

🔁 Reduced Operations and Automation

Reduce toil and deploy faster:

• Infrastructure as Code using Terraform or AWS CDK
• CI/CD with GitHub Actions, CodeBuild, or CodePipeline
• Embrace serverless first mindset to minimize ops and patching
• Version control infrastructure, review PRs, and track deployments

🔄 Application Portability and Clean Architecture

Make applications resilient to infrastructure changes:

• Design with Interfaces, Dependency Injection, and Abstraction
• Use clean layering to isolate infrastructure dependencies (e.g. DBs, caches, storage)
• Package with Docker and run in:
  • Fargate
  • EKS / Kubernetes
  • OpenShift or any CNCF-compliant platform
• Enables future replatforming or hybrid cloud adoption

🧠 Conclusion

Building scalable and reliable systems with .NET Core and AWS is not about choosing the trendiest services, but about combining the right building blocks, applying solid design principles, and enforcing automation, observability, and security.

This architecture supports rapid delivery, safe deployments, cost control, and resilience to failure — everything we need to thrive in the cloud-native era.

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