Micro-Frontend Decomposition via Visual Heatmapping of Legacy Feature Usage

The "Strangler Fig" pattern is the industry standard for legacy migration, yet 70% of enterprise rewrites still fail or exceed their timelines. The primary reason isn't a lack of engineering talent; it’s a lack of visibility. When you are staring at a 15-year-old monolithic JSP or ASP.NET application, the architectural boundaries aren't in the code—they are in the way users actually interact with the interface. Traditional static analysis tools can tell you which functions call each other, but they can't tell you which UI clusters represent a discrete business capability ready for a micro-frontend (MFE) transition.

To solve the $3.6 trillion global technical debt crisis, we have to stop guessing where to cut the monolith. We need a data-driven approach: microfrontend decomposition visual heatmapping. By recording real user workflows and mapping interaction density to component boundaries, architects can identify "seams" in the legacy UI that are ripe for extraction.

TL;DR: Legacy modernization fails because 67% of systems lack documentation. Microfrontend decomposition visual heatmapping allows architects to use actual user behavior to define MFE boundaries. By using Replay to record legacy workflows, teams can convert visual recordings into documented React components, reducing manual screen conversion from 40 hours to just 4 hours.

The Blind Spot in Traditional Decomposition#

Most architects approach micro-frontend decomposition through Domain-Driven Design (DDD). While DDD is theoretically sound, it falls apart when applied to "Big Balls of Mud" where the business logic is inextricably tangled with the presentation layer. In these environments, the frontend is often the only source of truth for how the system actually functions.

According to Replay's analysis, the average enterprise rewrite timeline stretches to 18 months because teams spend the first six months simply trying to understand what the legacy system does. Manual documentation is a pipe dream when the original developers have long since departed.

Video-to-code is the process of converting screen recordings into functional, documented React components, allowing teams to skip the "discovery" phase and move straight to implementation. By leveraging microfrontend decomposition visual heatmapping, we can see exactly which features are used together, providing a factual basis for our MFE boundaries.

Implementing Microfrontend Decomposition Visual Heatmapping#

How do we move from a blurry recording of a legacy system to a cleanly decoupled micro-frontend architecture? The process involves three distinct phases: Observation, Mapping, and Extraction.

1. The Observation Phase: Recording Workflows#

Instead of reading through thousands of lines of legacy code, we record the "Golden Paths"—the critical workflows that keep the business running. Whether it's a claims adjustment in insurance or a trade execution in financial services, these recordings capture the state changes, edge cases, and UI quirks that documentation misses.

2. The Mapping Phase: Generating the Heatmap#

Once we have the recordings, we apply visual heatmapping. This isn't just about "where the mouse clicks." It's about "feature density." We look for clusters of UI elements that always appear together in a specific user journey.

If the "Customer Search" and "Account Details" screens are always accessed in tandem, they likely belong in the same micro-frontend. If the "Reporting" module is only accessed once a month by a specific user group, it is a prime candidate for a lazy-loaded MFE.

3. The Extraction Phase: Leveraging Replay#

This is where Replay transforms the process. Rather than having a developer manually recreate the legacy UI in React—a process that takes an average of 40 hours per screen—Replay’s AI Automation Suite performs visual reverse engineering. It takes the recording and generates a documented React component library and design system.

Comparison: Manual Decomposition vs. Visual Heatmapping#

Technical Implementation: From Heatmap to Module Federation#

Once microfrontend decomposition visual heatmapping has identified your boundaries, the next step is technical orchestration. In a modern React environment, this usually involves Webpack Module Federation or Vite's federation plugins.

Below is an example of how a shell application might consume a micro-frontend that was identified and generated via Replay's Flows.

Example: Micro-Frontend Container Setup#

typescript
// shell/src/App.tsx
import React, { Suspense } from 'react';

// The 'AccountModule' was identified as a discrete boundary 
// through microfrontend decomposition visual heatmapping.
const AccountDetails = React.lazy(() => import('AccountMFE/AccountDetails'));
const TransactionHistory = React.lazy(() => import('TransactionMFE/History'));

const App: React.FC = () => {
  return (
    <div className="container">
      <header>
        <h1>Enterprise Banking Portal (Modernized)</h1>
      </header>
      <main>
        <Suspense fallback={<div>Loading Account Details...</div>}>
          <AccountDetails />
        </Suspense>
        
        <Suspense fallback={<div>Loading Transactions...</div>}>
          <TransactionHistory />
        </Suspense>
      </main>
    </div>
  );
};

export default App;

In this scenario, the

component isn't just a rewrite; it is a component generated from the legacy UI's visual state. Industry experts recommend this approach because it ensures visual parity with the legacy system, reducing the "shock" to the end-user during the transition.

Example: The Replay-Generated Component#

When Replay processes a legacy screen, it doesn't just produce "spaghetti code." It produces a clean, themed component that adheres to a centralized Design System.

tsx
// components/AccountDetails.tsx
import React from 'react';
import { Card, Badge, Grid } from '@enterprise-ds/core';

interface AccountProps {
  id: string;
  balance: number;
  status: 'active' | 'suspended';
}

/**
 * Component generated via Replay Visual Reverse Engineering.
 * Source: Legacy "ACCT_INFO_77" screen.
 */
export const AccountDetails: React.FC<AccountProps> = ({ id, balance, status }) => {
  return (
    <Card padding="lg" shadow="md">
      <Grid columns={2}>
        <div>
          <h3>Account ID: {id}</h3>
          <p className="text-xl font-bold">${balance.toLocaleString()}</p>
        </div>
        <div className="text-right">
          <Badge color={status === 'active' ? 'green' : 'red'}>
            {status.toUpperCase()}
          </Badge>
        </div>
      </Grid>
    </Card>
  );
};

By automating the generation of these components, Replay enables a 70% average time savings. Instead of spending months on "pixel-pushing," your senior architects can focus on the complex data orchestration and API integration required for a successful Legacy Modernization Strategy.

Why Visual Heatmapping Beats Static Analysis#

Static analysis tools often fail in legacy environments because of "dead code" and "zombie features." Industry experts recommend looking at runtime behavior rather than source files. In many 10-year-old monoliths, up to 40% of the codebase is never actually executed by a real user.

If you decompose based on code, you waste time migrating features that no one uses. Microfrontend decomposition visual heatmapping ensures you only modernize what matters. By focusing on the visual interaction layers, you are essentially performing a "usage-based audit" of your technical debt.

This is particularly critical in regulated industries like Healthcare and Financial Services. In these sectors, ensuring that a modernized component behaves exactly like its predecessor is a compliance requirement. Replay is built for these environments, offering SOC2 and HIPAA-ready configurations, and even on-premise deployments for highly sensitive government or manufacturing data.

Scaling the Migration with Replay's Library and Blueprints#

Once the initial decomposition is complete, the challenge shifts to governance. How do you ensure that 15 different micro-frontend teams aren't reinventing the wheel?

1. •The Library (Design System): Replay automatically extracts common UI patterns from your legacy recordings into a unified Design System. This becomes the "Single Source of Truth" for all MFEs.
2. •Flows (Architecture): This feature allows you to visualize the entire user journey and map it to your new micro-services, providing a high-level view of the decomposition progress.
3. •Blueprints (Editor): Architects can use the Blueprint editor to tweak the AI-generated code, ensuring it meets specific enterprise coding standards before it is committed to the repository.

By using microfrontend decomposition visual heatmapping, you aren't just moving code; you are evolving your architecture based on the reality of user behavior. This reduces the risk of the "Big Bang" rewrite failure and allows for a phased, incremental rollout that keeps stakeholders happy.

Overcoming the "Document Gap"#

The most significant hurdle in any enterprise migration is the "Document Gap"—the 67% of legacy systems that have no surviving documentation. When you use Replay, the recording is the documentation. The visual reverse engineering process creates a living map of the system.

According to Replay's analysis, teams that use visual recordings as their primary discovery tool are 3x more likely to finish their migration on schedule. They avoid the "analysis paralysis" that comes with trying to decode legacy SQL stored procedures or obfuscated JavaScript.

Frequently Asked Questions#

What is microfrontend decomposition visual heatmapping?#

It is a methodology used in legacy modernization where architects record real user interactions with a monolithic application. These recordings are then analyzed to identify clusters of feature usage, which serve as the data-driven boundaries for creating micro-frontends. This ensures that the new architecture reflects actual business processes rather than tangled legacy code structures.

How does Replay help with micro-frontend migration?#

Replay uses visual reverse engineering to convert video recordings of legacy UIs into clean, documented React code. It identifies UI patterns, creates a centralized design system, and maps user flows to architectural boundaries. This allows teams to modernize up to 10x faster, reducing the time spent on manual screen conversion from 40 hours to 4 hours.

Is visual heatmapping secure for regulated industries?#

Yes, when implemented with enterprise-grade tools like Replay. Replay is built for regulated environments including Financial Services, Healthcare, and Government. It is SOC2 and HIPAA-ready and offers on-premise deployment options to ensure that sensitive user data and proprietary workflows never leave your secure perimeter.

Can I use this for non-web legacy systems?#

While micro-frontend decomposition is primarily a web architecture, the principles of visual reverse engineering can be applied to any UI-based system. Replay's AI Automation Suite is designed to handle complex, data-heavy interfaces common in manufacturing, telecom, and insurance, converting the visual output of these legacy systems into modern, web-standard React components.

How does this approach handle complex business logic?#

Microfrontend decomposition visual heatmapping focuses on the "presentation seams." While the UI is extracted and modernized via Replay, the underlying business logic is typically migrated through API refactoring. However, because Replay documents the "Flows" and state changes of the UI, it provides backend developers with a clear roadmap of what the APIs need to support, bridging the gap between frontend and backend teams.

Ready to modernize without rewriting? Book a pilot with Replay