Multi-Cloud Portability: Moving Legacy UIs from Azure to AWS via React Components

Cloud lock-in is the silent killer of enterprise agility. For decades, organizations have tethered their core business logic to specific proprietary stacks—Silverlight on Azure, legacy ASP.NET on Windows Server, or mainframe-bound terminal emulators. When the mandate comes to shift to a multi-cloud strategy, usually to leverage AWS’s superior edge computing or AI services, teams realize their "portable" applications are actually concrete blocks.

The technical debt associated with these systems is staggering. Industry experts recommend a complete decoupling of the presentation layer from the underlying infrastructure to achieve true multicloud portability moving legacy assets. However, manual rewrites take years. According to Replay’s analysis, the average enterprise rewrite timeline stretches to 18 months, with a 70% failure rate.

We need a better way to extract the "soul" of an application—its user workflows and design intent—without getting bogged down in the spaghetti code of the past. This is where Visual Reverse Engineering and Replay transform the migration equation from a multi-year risk into a multi-week victory.

TL;DR: Moving legacy UIs from Azure to AWS requires decoupling the front-end from proprietary backends. Manual rewrites cost 40+ hours per screen and usually fail. Replay uses Visual Reverse Engineering to convert video recordings of legacy workflows into documented React components, reducing migration time by 70% and enabling true multicloud portability moving legacy systems to modern AWS stacks like S3, CloudFront, and Fargate.

---

The Architecture of Multicloud Portability Moving Legacy UIs#

True multicloud portability moving legacy applications isn't about containers alone; it’s about componentization. If your UI is tightly coupled to Azure-specific authentication libraries or proprietary .NET session states, moving to AWS is more than a "lift and shift"—it’s a ground-up reconstruction.

The $3.6 trillion global technical debt exists because we have historically prioritized speed of delivery over architectural purity. To move a legacy UI from Azure to AWS effectively, you must follow a three-tier decoupling strategy:

1. •Presentation Decoupling: Extract the UI logic into framework-agnostic or widely supported frameworks (React/TypeScript).
2. •State Management Abstraction: Move away from server-side session state to client-side or distributed state (Redux, Context API).
3. •Service Intermediation: Replace direct Azure service calls with an API Gateway or GraphQL layer that can resolve to AWS Lambda or Fargate.

Visual Reverse Engineering is the process of capturing the visual output and behavioral patterns of a legacy application to generate modern source code without accessing the original, often undocumented, backend logic.

Why Manual Migration Fails#

When architects attempt to manually port legacy UIs, they encounter the "Documentation Gap." Replay's research shows that 67% of legacy systems lack accurate documentation. Developers spend more time "archaeologizing" old code—trying to understand why a button behaves a certain way—than actually writing new code.

Learn more about reducing technical debt

---

From Azure App Service to AWS S3/CloudFront: The React Path#

The most common scenario for multicloud portability moving legacy involves moving an old ASP.NET or Silverlight application hosted on Azure App Service to a modern, serverless React architecture on AWS.

In the Azure world, the UI and the server are often one and the same. In the AWS world, we want a "Headless" approach. By using Replay, you record the user journey through the Azure-hosted application. Replay’s AI Automation Suite analyzes the DOM changes, CSS transitions, and state mutations, then outputs a clean React component library.

Step 1: Capturing the Workflow#

Instead of reading 10,000 lines of undocumented C#, a business analyst or developer simply records the "Create New Insurance Claim" workflow. Replay captures every hover state, validation message, and layout constraint.

Step 2: Generating the Component Library#

Replay converts these recordings into a standardized Design System. This ensures that the new AWS-hosted UI looks and behaves exactly like the Azure original, maintaining user productivity and reducing training costs.

Step 3: Deployment to AWS#

Once you have the React components, deployment becomes a standard CI/CD pipeline. You can host the static assets on AWS S3, distribute them via CloudFront, and point the API calls to a new microservices layer. This is the essence of achieving multicloud portability moving legacy—the UI no longer cares where it is hosted.

---

Code Comparison: Legacy Azure-Coupled Code vs. Portable React#

To understand the value of multicloud portability moving legacy, look at the code. Legacy applications often use proprietary tags or server-side controls that only function in a specific environment.

The Legacy Azure Snippet (ASP.NET WebForms)#

This code is tightly bound to the Windows/Azure ecosystem. Porting this to AWS requires a complete rethink of how the server interacts with the UI.

html
<!-- Legacy Azure-dependent UI -->
<asp:UpdatePanel ID="UpdatePanel1" runat="server">
    <ContentTemplate>
        <div class="container">
            <asp:Label ID="lblStatus" runat="server" Text="Status: Pending" />
            <asp:Button ID="btnSubmit" runat="server" Text="Submit Claim" 
                OnClick="btnSubmit_Click" 
                CssClass="azure-btn-primary" />
        </div>
    </ContentTemplate>
</asp:UpdatePanel>

The Modern Portable React Component (Generated by Replay)#

Replay takes the visual output of the above and generates a clean, TypeScript-ready React component. This code is 100% portable and can be deployed to any cloud provider or on-premise environment.

typescript
import React, { useState } from 'react';
import { Button, StatusLabel, Container } from './design-system';

interface ClaimSubmitProps {
  initialStatus?: string;
  onAction?: (data: any) => Promise<void>;
}

/**
 * Component generated via Replay Visual Reverse Engineering
 * Target: AWS S3/CloudFront deployment
 */
export const ClaimSubmit: React.FC<ClaimSubmitProps> = ({ 
  initialStatus = "Pending", 
  onAction 
}) => {
  const [status, setStatus] = useState(initialStatus);
  const [loading, setLoading] = useState(false);

  const handleSubmit = async () => {
    setLoading(true);
    try {
      if (onAction) await onAction({ timestamp: new Date() });
      setStatus("Submitted");
    } catch (error) {
      console.error("Submission failed", error);
    } finally {
      setLoading(false);
    }
  };

  return (
    <Container variant="fluid">
      <StatusLabel status={status} />
      <Button 
        label="Submit Claim" 
        onClick={handleSubmit} 
        isLoading={loading}
        variant="primary"
      />
    </Container>
  );
};

By converting the UI into the React component above, you’ve successfully achieved multicloud portability moving legacy. The logic is now encapsulated in a standard framework that AWS handles natively through its various front-end hosting services.

---

Strategic Advantages of Visual Reverse Engineering#

Industry experts recommend Visual Reverse Engineering because it bypasses the "Black Box" problem. Most legacy systems are black boxes—we know what goes in and what comes out, but the internal logic is a mystery.

Video-to-code is the process of using computer vision and metadata analysis to transform a screen recording of a software application into functional, editable source code.

According to Replay's analysis, companies utilizing visual extraction methods see a 70% average time saving compared to those using manual documentation and coding. This is critical for industries like Financial Services or Government, where the cost of downtime or a failed migration is measured in millions of dollars.

The Replay AI Automation Suite#

Replay doesn't just give you a "screenshot" of a component. Its AI Automation Suite identifies:

• •Design Tokens: Automatically extracts colors, typography, and spacing.
• •State Logic: Infers how the UI changes based on user input.
• •Data Flow: Maps out where information enters the system, facilitating the creation of new AWS-based APIs.

For a deeper dive into how this works in regulated sectors, see our article on Modernizing Healthcare Systems.

---

Overcoming the "18-Month Rewrite" Trap#

The 18-month average enterprise rewrite timeline is a death sentence in a competitive market. When an organization decides to pursue multicloud portability moving legacy apps, they often get stuck in "Analysis Paralysis." They spend six months just documenting the current state of the Azure environment.

Replay collapses this timeline. By focusing on the "Flows" (Architecture) and "Library" (Design System), teams can begin deploying to AWS in weeks, not years.

Comparison of Migration Workflows#

---

Security and Compliance in Multi-Cloud Migrations#

When moving legacy UIs, security cannot be an afterthought. Legacy Azure applications often rely on Active Directory (AD) integrations that are deeply embedded in the code. Moving to AWS means transitioning to AWS IAM or Cognito.

Replay is built for these regulated environments. Whether you are in Insurance, Healthcare, or Government, Replay offers:

• •SOC2 & HIPAA Readiness: Ensuring your migration data is handled securely.
• •On-Premise Availability: For organizations that cannot let their legacy UI recordings leave their network.
• •Clean Code Output: Replay doesn't include "hidden" libraries or telemetry in the generated React code. You own the code 100%.

Achieving multicloud portability moving legacy systems requires a clean break from old security paradigms. By generating fresh React code, you can implement modern OAuth2/OpenID Connect flows from day one on AWS, rather than trying to "bridge" old Azure AD protocols.

---

Implementation Guide: Moving to AWS with Replay#

To execute a successful multicloud portability moving legacy project, follow this roadmap:

1. •Inventory the Workflows: Identify the top 20% of screens that handle 80% of the business value.
2. •Record via Replay: Use the Replay recorder to capture these workflows in their current Azure environment.
3. •Audit the Library: Review the auto-generated React components in the Replay Library. Standardize the Design System.
4. •Map AWS Integrations: Use the Replay Flows tool to map out how the new React front-end will talk to AWS services (Lambda, DynamoDB, etc.).
5. •Pilot and Scale: Deploy the first workflow to AWS. Once validated, use Replay's AI to batch-process the remaining screens.

This method ensures that you aren't just moving technical debt from one cloud to another. You are actively liquidating that debt and replacing it with modern, portable assets.

---

Frequently Asked Questions#

How does Replay handle complex business logic during a multicloud portability moving legacy project?#

Replay focuses on the presentation layer and the user interaction logic. While it captures the "UI state," the deep backend business logic (like complex SQL stored procedures) should be modernized into microservices. Replay provides the "Flows" and documented components that make connecting to these new microservices on AWS seamless.

Can Replay convert Silverlight or VB6 UIs into React for AWS?#

Yes. Because Replay uses Visual Reverse Engineering, it is framework-agnostic. It doesn't matter if the legacy UI is Silverlight, Delphi, VB6, or an old version of Angular. If it can be rendered on a screen and recorded, Replay can convert it into modern React components.

Is the code generated by Replay maintainable?#

Absolutely. Unlike "low-code" platforms that trap you in proprietary runtimes, Replay generates standard TypeScript/React code. It follows modern best practices, uses your naming conventions, and is designed to be checked into your Git repository and maintained by your developers forever.

What are the main cost savings of using Replay for cloud migration?#

The primary savings come from the reduction in manual labor. By cutting the time per screen from 40 hours to 4 hours, enterprises save millions in developer salaries. Additionally, by shortening the timeline from 18 months to a few months, organizations realize the business value of AWS (lower OpEx, better scaling) much sooner.

---

Ready to modernize without rewriting? Book a pilot with Replay