• Services
  • Use Cases
    • About UsCustomersCareersInsightsGet In Touch
    Go Back

    Modernizing .NET Applications for AWS: Best Practices Beyond Rehosting

    June 24, 2025

    5 minutes

    Modernizing legacy .NET applications for the cloud is more than rehosting (lift-and-shift). While rehosting can provide quick gains, long-term agility and scalability come from broader transformations, AWS provides a mature ecosystem for .NET modernization. Moreover, if you combine AWS with new paradigms such as Agentic AI, organizations can unlock entirely new business capabilities.

    A report from Growth Acceleration Partners reveals that 92% of organizations continue to rely on legacy technologies such as Visual Basic 6.0, VB.NET, and Classic ASP, highlighting the urgent need for modernization. Additionally, 41% of organizations indicate plans to modernize their legacy applications within the next year. This growing momentum toward modernization is fueling a widespread shift among large organizations to adopt modern architectures and cloud-native technologies.

    Through this blog post let us explore advanced modernization strategies for .NET on AWS.

    Why Go Beyond Rehosting?

    Rehosting, or ‘lift-and-shift’ can move workloads to the cloud from on-prem or another cloud service without much code modification. While it can allow for a quick move, it does not help you realize the full value of cloud-native and it does not provide the optimal solutions for other things like: scalability, cost optimization, automating DevOps and integrating with cloud services that have emerged like serverless computing, Container orchestration, Managed databases usually called as a service (DBaaS).

    Re-hosted applications can still have legacy constraints such as monolithic architecture, tight coupling, and outdated frameworks. These constraints can limit performance, make maintenance a nightmare, and prevent modern practices such as continuous delivery and monitoring in real-time.

    In contrast, cloud-native modernization allows for scaling, flexibility, and automation. By leveraging microservices, containers, and serverless technologies, as well as AWS services such as RDS, Lambda, and EventBridge, organizations can improve performance, speed up development, and generate innovation in a cloud-first organization.

    AWS-Native Strategies for .NET Modernization

    1. Replatform to Managed Services

    Replatforming replaces infrastructure-heavy components with AWS managed services. For .NET applications, this often includes:

    • Amazon RDS or Aurora for SQL Server
    • Amazon ElastiCache for in-memory caching
    • Amazon MQ or SQS for message brokering

    Managed services reduce operational overhead and improve reliability. They also simplify scaling and compliance.

    2. Containerization

    Break down monoliths into containerized workloads. Use:

    • AWS Fargate or Amazon ECS for running .NET Core/.NET 6+ containers
    • Docker for container packaging
    • AWS App Mesh or Service Connect for service-to-service communication

    Containerization promotes portability and CI/CD automation. It also facilitates blue/green and canary deployments.

    3. Refactor to Microservices

    Refactoring involves breaking a monolith into microservices. Use .NET 6/7 minimal APIs or ASP.NET Core for lightweight service development. Back these with:

    • AWS Lambda for event-driven logic
    • API Gateway for routing and throttling
    • DynamoDB or Aurora Serverless for scalable, low-latency storage

    This approach supports modular deployments and independent scaling.

    4. Automate with Infrastructure as Code (IaC)

    Use AWS CloudFormation, CDK, or Terraform to define infrastructure. IaC enables repeatable, testable, and version-controlled deployments.

    For .NET developers, AWS CDK for .NET provides native C# bindings to define cloud infrastructure directly in familiar language constructs.

    5. Modernize CI/CD Pipelines

    Use AWS CodePipeline, CodeBuild, and CodeDeploy for robust CI/CD workflows. Integrate GitHub Actions or Azure DevOps for source control and pipeline orchestration.

    Add SonarQube, Checkmarx, or OWASP ZAP for security and quality checks in the build stage.

    Observability and Governance

    Modernized applications need full-stack observability:

    • Use Amazon CloudWatch for logs, metrics, and traces.
    • Integrate X-Ray for request tracing across services.
    • Use AWS Config and Control Tower for governance and policy enforcement.

    Security best practices include:

    • IAM fine-graining
    • Secrets Manager for credentials
    • AWS Shield and WAF for DDoS protection

    Integrating Agentic AI into Modern .NET Architectures

    Agentic AI refers to autonomous or semi-autonomous systems that can perceive, reason, and act on behalf of users or systems. These agents use LLMs and decision-making frameworks to execute complex tasks across systems.

    Unlike traditional AI, agentic models don’t just predict—they plan and act. They can invoke APIs, generate code, and even orchestrate workflows.

    Use Cases in Modern .NET on AWS

    1. Intelligent Workflows

    Agentic AI agents can coordinate workflows within modern .NET microservices. For instance:

    • Parsing complex input and determining service routing
    • Using Amazon Bedrock or SageMaker to run agents trained on domain-specific data
    • Triggering downstream AWS Lambda functions based on interpreted user intent

    2. DevOps Automation

    Use agentic agents to:

    • Monitor CI/CD pipelines
    • Trigger rollbacks or re-deployments
    • Suggest infrastructure improvements based on system telemetry

    Note: Tools such as LangChain, Semantic Kernel, or custom OpenAI agents can integrate directly with .NET Core apps via REST or SDKs.

    3. Autonomous Observability

    Agents can analyze logs and metrics to identify anomalies. They can then:

    • Open tickets in systems like ServiceNow
    • Trigger scaling policies via AWS SDK
    • Modify CloudWatch alarms or dashboards dynamically

    Note: This reduces MTTR and enhances resilience.

    4. AI-Augmented Customer Support

    Embed agentic copilots within customer-facing .NET apps. Let them:

    • Handle complex interactions
    • Interpret customer issues
    • Escalate to the right backend service

    Note: Integrate with Amazon Lex, Bedrock, or external LLM APIs (OpenAI, Anthropic) for real-time decision-making.

    Implementation Considerations

    1. Architecture Design:

    Agentic AI integration requires asynchronous, event-driven architectures. Use:

    • Amazon EventBridge for event routing
    • SQS and SNS for queuing and pub-sub
    • Step Functions for multi-step orchestration

    2. Security and Compliance:

    • Amazon EventBridge for event routing
    • SQS and SNS for queuing and pub-sub
    • Step Functions for multi-step orchestration

    Ensure AI agents operate under scoped IAM roles. Log every action. Validate outputs—especially when agents write code or interact with sensitive data.

    3. Model Management:

    Use SageMaker or Bedrock for secure model hosting. Or, invoke third-party APIs with guardrails like:

    • Prompt templates
    • Output validation
    • Rate limits

    Conclusion

    Modernizing .NET applications on AWS means rethinking how applications are built, deployed, and operated. Moving beyond rehosting opens the door to elastic scaling, cloud-native resilience, and rapid innovation.

    With Agentic AI, this modernization goes further. Applications become not just services—but collaborators. The combination of .NET modernization and agentic intelligence can transform enterprise agility, automation, and customer experience.

    As both AWS and AI capabilities evolve, staying at the intersection of cloud-native and intelligent design will define the next era of software engineering.