Migration Factory

De la forteresse Mainframe a la liberte Cloud-Native | Le voyage de transformation IT

SCENE 6: TNR - TEST & NON-REGRESSION "Quality Assurance Laboratory" - Continuous Validation Loop SOURCE CAPTURE Flows - Data - Scenarios Recording from Legacy COMPARISON ENGINE AI-Powered Analysis Side-by-side - Diff detection - Pattern matching TARGET CAPTURE Flows - Data - Scenarios Recording from Target ZERO REGRESSION ✓ Feedback Loop to TNR to TNR SCENE 1: LEGACY "The Patient" Z/OS CICS/IMS DB2/VSAM BATCH RUN Steering Reports Partners Batch Constraints SCENE 2 Collection Src Doc Data PUMP SCENE 3: DOCTOR.FACTORY "The Diagnostic Center" DOCTOR.FACTORY INPUT - Languages L2G L3G L4G Editors DIAGNOSIS Analysis TRASH Rx REPO Clean SCENE 4: AI SURGICAL BLOCK "The Operating Theater" 🤖 Claude Code INPUT Languages Infra OUTPUT Code Docs Java - Python React - Go K8s - Docker Source Code API Specs Runbooks ⚡ ✨ Deploy SCENE 5: TARGET SI "The Modern Hospital" CLOUD NATIVE Microservices Real-time BI Observability Frontend Event-Driven GitOps ✅ 100% Open Source All "useful" scope migrated imagine-ops.com
Legacy / Problemes
AI Transformation
Target / Solutions
Process / Tools
Waste Elimination

Cliquez sur les bulles pour voir les details - Les connecteurs bleus relient le flux principal a la boucle TNR

The Transformation Process in Detail

🏰 SCENE 1: THE LEGACY WORLD - "The Patient"

Current IT Landscape

Mainframe towers drawn as a gothic fortress, tangled cables like invasive vines, direct dependencies between IMS/CICS code and external 4GL tools (NSDK, NatStar...) without versioned APIs, green screens.

RUN CICS, IMS, batch jobs, 24/7 operations
BATCH Scheduler Job calendars, spaghetti dependencies
Steering & KPIs Dashboards, SLA gauges, rising costs
Reports Printed report stacks, SPOOL queues
Partners API gateways, ESB, EDI connections
Constraints Vendor lock-in, end-of-support, skill shortage
🏭 SCENE 2: THE COLLECTION FUNNEL - "Data Extraction Pipeline"

Data Extraction Pipeline

Giant industrial funnel receiving data streams, suction pump labeled "PULL", multiple input connectors.

  • Source Control pipes - Source code extraction
  • Database extraction tubes - Schemas and data
  • Documentation feeds - Specifications, manuals
  • Runtime capture streams - Logs, traces, metrics
🏥 SCENE 3: DOCTOR.FACTORY - "The Diagnostic Center"

Diagnostic Center

Hospital/medical center style. The Legacy patient is examined and diagnosed.

INPUT - Source Languages:

L2G COBOL, PL/I, Assembler, Natural, RPG
L3G C, C++, Legacy Java
L4G SQL, Report generators, Screen painters
Proprietary PAC, ADABAS, TELON, Cool:Gen, Synon...

OUTPUT - Three Outputs:

TRASH (Morgue) Dead code, unused functions, obsolete processes
Rx (Prescription) Recommendations, treatment options, priorities
REPO (Repository) Central vault, source cartography, dictionaries
🤖 SCENE 4: AI SURGICAL BLOCK - "The Operating Theater"

AI Operating Room

Futuristic surgical suite with AI robots. Lead surgeon: Claude Code.

INPUT - Target Languages & Frameworks:

Java / Spring Boot Python / FastAPI TypeScript / Node.js Go Rust Kotlin React Angular Vue.js

Infrastructure:

PostgreSQL MongoDB Redis Kubernetes Docker Terraform GitLab CI ArgoCD

OUTPUT - Deliverables:

  • Generated source code packages
  • OpenSource runtime configurations
  • Complete documentation: Architecture, technical guides, deployment scripts, API specs, runbooks
🏗 SCENE 5: TARGET SI - "The Modern Hospital"

Modernized Infrastructure

Modern glass building, clean lines, cloud connections.

Modern RUN Microservices, containers, API-first, event-driven
Reporting Real-time dashboards, Self-service BI, Data lakes
Observability Metrics, logs, traces, automated alerting, SRE
Automations GitOps, Infrastructure as Code, Auto-scaling
Frontend Modern web apps, responsive, PWA
Batch/Outputs Event-driven, streaming pipelines, modernized jobs
🔬 SCENE 6: TNR - "Quality Assurance Laboratory"

Quality Assurance Laboratory

Scientific laboratory with comparison equipment. Continuous validation loop.

Source Capture Captured data flows, transaction scenarios, batch outputs
Comparison Engine Giant microscope, side-by-side screens, AI-powered diff analysis
Target Capture Equivalent modern captures, API responses, perf metrics

GOAL: ZERO REGRESSION

Green/red indicators, detailed comparison reports, exception management workflow

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