From Monolith to Modular: Using Video to Map Component Boundaries

Most enterprise modernization projects are doomed before the first line of code is written. The failure isn't a lack of engineering talent; it’s a lack of visibility. When you attempt to move from monolith to a modular architecture, you aren't just refactoring code—you are performing digital archaeology on systems where the original authors left a decade ago and the documentation is a collection of outdated Confluence pages and broken links.

The industry standard for legacy rewrites is a disaster. 70% of these projects fail or significantly exceed their timelines. We continue to treat software like a static text file when we should be treating it like a living process. To successfully transition from monolith to a modern React-based micro-frontend or modular core, you need to stop reading dead code and start recording live behavior.

TL;DR: Visual Reverse Engineering uses video as the primary source of truth to map component boundaries and business logic, reducing modernization timelines from 18 months to mere weeks.

The $3.6 Trillion Visibility Gap#

Global technical debt has ballooned to $3.6 trillion. For the average CTO in financial services or healthcare, this debt isn't an abstract concept—it’s the reason why a "simple" UI update takes six months and three regression cycles.

The core problem is that 67% of legacy systems lack any meaningful documentation. When you decide to move from monolith to a modular architecture, your team spends 80% of their time "discovery-mapping"—manually clicking through screens, tracing obfuscated network calls, and trying to guess which COBOL or Java backend service powers which pixel.

This manual archaeology takes an average of 40 hours per screen. In a 500-screen enterprise application, that’s 20,000 man-hours just to understand what you have before you even write a single React component.

The Modernization Matrix: Comparing Approaches#

Why "Video as Source of Truth" Beats Code Analysis#

Traditional static analysis tools fail because they can't capture intent. They see the "how" (the code) but not the "why" (the user workflow). By using Replay, we shift the focus to the visual layer.

If a user performs a "Claims Submission" workflow in a legacy insurance portal, that workflow defines the boundaries of the components you need. You don't need to analyze 50,000 lines of spaghetti jQuery; you need to record the user interaction and let AI map those visual state changes to modular React components.

Mapping Component Boundaries#

In a monolith, boundaries are blurred. A single script might handle validation, API calls, and DOM manipulation for five different logical sections of a page. When moving from monolith to modularity, the hardest task is "de-tangling."

Replay uses visual recording to identify:

1. •Visual Atomic Units: Identifying recurring UI patterns (buttons, inputs, modals) to populate a modern Design System.
2. •State Transitions: Monitoring how data flows from one "screen" to the next to define props and context.
3. •Side Effects: Mapping network requests triggered by specific UI actions to generate precise API contracts.

💡 Pro Tip: Don't try to refactor the backend and frontend simultaneously. Use Replay to extract the UI and business logic first, then point your new modular components at the legacy APIs using the generated contracts.

The Technical Execution: From Recording to React#

The transition from monolith to a modular system using Replay follows a structured, automated pipeline. This isn't a "low-code" shortcut; it’s an engineering-grade extraction process.

Step 1: Workflow Recording#

An SME (Subject Matter Expert) or QA engineer records a standard business process—for example, "Onboarding a New Patient" in a healthcare CRM. Replay captures the DOM mutations, network traffic, and state changes.

Step 2: Visual Boundary Analysis#

The AI Automation Suite analyzes the recording. It identifies that the "Patient Header" is a persistent element across five screens, while the "Medical History Form" is a distinct functional module.

Step 3: Component Extraction#

Replay generates documented React components based on the recording. It doesn't just "scrape" the HTML; it reconstructs the logic.

typescript
// Example: Extracted "PolicySearch" component from a 15-year-old Insurance Monolith
// Replay preserved the validation logic and mapped the legacy API endpoint.

import React, { useState } from 'react';
import { useLegacyBridge } from '@replay/core';

interface PolicyProps {
  onSelect: (id: string) => void;
  initialFilter?: string;
}

export const PolicySearch: React.FC<PolicyProps> = ({ onSelect, initialFilter }) => {
  const [query, setQuery] = useState(initialFilter || '');
  const { data, loading, error } = useLegacyBridge('/api/v1/legacy/policy-lookup', { query });

  // Business Logic preserved from manual workflow recording
  const handleSearch = (val: string) => {
    if (val.length < 3) return; 
    setQuery(val);
  };

  return (
    <div className="modern-container">
      <input 
        type="text" 
        onChange={(e) => handleSearch(e.target.value)}
        placeholder="Search by Policy ID..."
      />
      {loading && <Spinner />}
      <ul className="results-list">
        {data?.map(item => (
          <li key={item.id} onClick={() => onSelect(item.id)}>
            {item.policyHolderName} - {item.status}
          </li>
        ))}
      </ul>
    </div>
  );
};

Step 4: API Contract Generation#

While the UI is being extracted, Replay simultaneously documents the "black box" backend. It generates OpenAPI/Swagger specifications based on the actual traffic observed during the recording.

yaml
# Generated API Contract for Legacy Monolith
paths:
  /api/v1/legacy/policy-lookup:
    get:
      summary: Extracted from PolicySearch Workflow
      parameters:
        - name: query
          in: query
          required: true
          schema:
            type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PolicyList'

💰 ROI Insight: Manual documentation and API mapping for a single enterprise module typically cost $15,000–$25,000 in engineering hours. Replay reduces this to the cost of a 10-minute recording session.

Challenging the "Rewrite from Scratch" Myth#

The "Big Bang" rewrite is the most expensive way to fail. When you rewrite from scratch, you aren't just building new features; you are trying to replicate decades of edge-case fixes that no one remembers.

The future of enterprise architecture isn't rewriting—it's understanding.

By moving from monolith to modular through visual extraction, you preserve the "tribal knowledge" embedded in the system. If the legacy system has a specific, weird validation rule for zip codes in Nebraska, Replay captures that behavior because it's part of the recorded workflow.

Breaking Down the Silos#

1. •The Library (Design System): As you record more workflows, Replay identifies patterns. It tells you, "You have 14 different versions of a DatePicker across this monolith. Here is one unified React component to replace them all."
2. •The Flows (Architecture): Visualizing the application map. Instead of a 200-page PDF architecture document, you have a living, interactive map of how users actually move through the system.
3. •The Blueprints (Editor): Fine-tune the extracted code before it ever hits your Git repository.

⚠️ Warning: The biggest risk in modernization is "Feature Creep." Teams often try to add new features while migrating. Replay enforces a "Logic-First" migration, ensuring the new system works exactly like the old one before you start innovating.

Built for the Regulated Enterprise#

We recognize that the most critical monoliths live in highly regulated environments. You cannot simply upload your healthcare portal's source code to a public LLM.

Replay is designed for:

• •Financial Services: High-security environments where data privacy is paramount.
• •Healthcare: HIPAA-ready workflows that protect PII/PHI during the extraction process.
• •Government/Defense: On-premise deployment options for air-gapped modernization.
• •Telecom: Handling high-complexity state management in massive OSS/BSS systems.

Frequently Asked Questions#

How does Replay handle complex business logic hidden in the backend?#

Replay captures the inputs and outputs of that logic via network interception and DOM state changes. While it doesn't "see" the COBOL code on the mainframe, it documents the exact behavior and data requirements of that logic, allowing you to wrap it in a modern API or replicate it in a new microservice with 100% accuracy.

Can we move from monolith to a specific framework like Vue or Angular instead of React?#

While our primary output is optimized for React (the enterprise standard), the underlying visual blueprints and API contracts are framework-agnostic. The "Blueprints" can be adapted to generate components for any modern frontend stack.

How much manual cleanup is required after extraction?#

We reduce the manual workload by 70-90%. In our "4 hours vs 40 hours" metric, that 4 hours includes the time an engineer spends reviewing the generated React component, refining the styling to match the new design system, and hooking up the final state management.

What happens to our existing E2E tests?#

Replay actually improves your testing posture. It automatically generates E2E test scripts (Cypress/Playwright) based on the recorded workflows. This ensures that your new modular component behaves exactly like the legacy monolith component it replaced.

The Path Forward#

The era of the 24-month "transformation project" is over. Boards of Directors no longer have the patience for multi-million dollar failures. The move from monolith to modularity must be surgical, data-driven, and fast.

Stop guessing what your code does. Start recording what your users do.

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Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.