Prasad Patil
ProjectMonolith → Mesh
Drawn byPrasad Patil
DisciplineCloud · AI · Microservices
ScaleEnterprise
SheetA-100  Rev. 4

existing to remainnew work

I move thirty-year-old systems to the cloud without breaking them.

Solution Architect at Tata Consultancy Services, fifteen years in one line of work: taking enterprise estates that cannot go down - mainframe, COBOL, legacy .NET - and rebuilding them as Java and .NET microservices on Azure. Lately with GenAI reading the code that no one left to explain it.

15+years shipping
2granted patents
AZ-305Azure Architect Expert
4enterprise units

← 2011 ‐ 2026  ·  overall →

Portrait of Prasad Patil
Set out from centre
A-101 Assess & decompose

One deployable, or six?

Every modernization starts the same way: a single artifact that does everything, that nobody can deploy on a Tuesday. Split it and you buy independence - and pay for it in network calls. Here's the trade, live.

existing ‐ to remain, drawn dashed
new work ‐ services, drawn solid
wire ‐ calls and event flow
single deployable

What changes

Deployable units
1
Blast radius
whole system
Scaling
all or nothing
Release cadence
coupled
Ownership
one team

The honest half: splitting adds network latency, eventual consistency, distributed tracing and per-service operations. Cut along business capabilities - bounded contexts - not technical layers, and only where the coupling is actually costing you. A well-run monolith beats a badly-drawn mesh every time.

A-102 Transform

COBOL in, Spring Boot out

The hard part of a mainframe migration was never syntax - it's that the business rules live in code no one has read in twenty years. An agentic pipeline reads it, maps it to a context, rewrites it, then argues with itself about the edge cases.

Analyze Map context Transform Review Test
CALC-INTEREST.cbllegacy
IDENTIFICATION DIVISION.
PROGRAM-ID. CALC-INTEREST.

DATA DIVISION.
WORKING-STORAGE SECTION.
01 WS-PRINCIPAL   PIC 9(9)V99.
01 WS-RATE        PIC 9(2)V9(4).
01 WS-TERM        PIC 9(3).
01 WS-INTEREST    PIC 9(9)V99.

PROCEDURE DIVISION.
    COMPUTE WS-INTEREST ROUNDED =
        WS-PRINCIPAL * WS-RATE
        * WS-TERM / 1200.
    DISPLAY 'INTEREST: ' WS-INTEREST.
    STOP RUN.
InterestCalculator.javatarget
// run the pipeline to generate

A-103 Track record

Fifteen years, as a trace

Four spans, one system under continuous migration. Open any span for what actually shipped.

20112015201920232026
  • Azure migration lifecycle tooling - Cloud Console, Migration Factory Hub, Well-Architected reviews.
  • GenAI-assisted COBOL → Java with contextual understanding of the legacy estate, not line-by-line translation.
  • Legacy .NET and mainframe rebuilt as Angular/React front ends over .NET and Java microservices.
  • Domain-Driven Design as the decomposition method - bounded contexts before services.
  • Intelligent Services Networks - core contributor, Spring Boot microservices with Azure integration.
  • Product architect for automating the software delivery lifecycle end to end.
  • Legacy → microservices via DDD, deployed as enterprise workloads on Azure.
  • Compliance as a Service - owned it end to end, from research through product delivery.
  • Compliance engines and integrations across heterogeneous enterprise infrastructure.
  • Produced the work behind a US patent (2017) and an Indian patent (2024).
  • Data-centre migration estimation - Java modules for transformation planning at estate scale.
  • Performance-sensitive work: multi-threading, design patterns, large-scale data structures.
  • Where the through-line started: understanding legacy infrastructure before moving it.
A-104 Case files

Four problems worth the trouble

Mainframe modernization with GenAI

TCS AI.Cloud · 2023 - now

Problem

COBOL estates carrying decades of business rules, with no surviving documentation and no author left to ask.

Approach

Architected a GenAI-driven migration that builds contextual understanding of the legacy system first, then generates Java - reviewed and test-gated rather than trusted.

Outcome

Recognized internally as Contextual Master - GenAI for Mainframe Modernization (2024).

Azure migration factory

TCS AI.Cloud · 2023 - now

Problem

Migration handled as a series of one-off projects, with quality depending on which team drew the short straw.

Approach

Led lifecycle tooling - Cloud Console, Migration Factory Hub, Well-Architected reviews - so assessment and landing zones became repeatable.

Outcome

A standard path from legacy estate to cloud-native, reusable across engagements.

Compliance as a Service

TRDDC · Ignio · 2014 - 2019

Problem

Compliance checking across networks and operating systems done manually, differently, by every team.

Approach

Took it from research to product: policy definition, a compliance engine, and integrations for mixed enterprise infrastructure.

Outcome

Two granted patents - US (2017) and India (2024) - plus a shipped service.

MindSpark - open source

2026 - now

Problem

Collaborative mind-mapping tools want your data on their servers and a dependency tree to match.

Approach

Zero-runtime-dependency vanilla JS, self-hostable in one command; real-time collaboration on Cloudflare Workers and Durable Objects with GitHub OAuth and JWT role-based access.

Outcome

MIT-licensed, maps stored in the user's own repo. Source →

A-106 Operate

What I bring to an architecture review

Architecture

  • Microservices & DDDbounded contexts, service boundaries, decomposition strategy
  • Cloud-native on Azurelanding zones, Well-Architected, migration lifecycle
  • Legacy modernizationmainframe, COBOL, legacy .NET estates

Build

  • Java & Spring Bootthe target stack for most migrations I run
  • Agentic AI & LLM fine-tuningapplied to code comprehension and translation
  • Full-stack deliveryAngular / React over .NET and Java services

Certified

  • Azure Solutions Architect ExpertAZ-305
  • Azure Administrator AssociateAZ-104
  • NPTELMachine Learning for Engineering & Science
JavaSpring BootAzure DDDKubernetes-era opsPython
A-107 Record

Patents & recognition

Patents

  • Compliance Automation PlatformUS patent · 2017
  • Compliance as a ServiceIndian patent · 2024
  • Compliance as a Servicetechnical paper · 2017

Awards

  • Contextual MasterGenAI for mainframe modernization · 2024
  • Best Performer of the YearTCS · 2021
  • 2nd Rank, Ignio Hackathon2019

Education

  • PhD Scholar - ML & Quantum ComputingIIIT Nagpur · ongoing
  • B.E. Computer ScienceRKNEC, Nagpur · 2010
  • Diploma, Computer Technology3× gold medalist · 2007

Got an estate nobody wants to touch?

Architecture reviews, modernization strategy, and the awkward question of whether you should split that service at all.