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Legacy migration & modernization.

Move off the codebase everyone is afraid of — incrementally, behind stable contracts, without stopping the business.

DjangoPostgreSQLOAuth2SAML2.0DockerAWSGCP
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Overview

Big-bang rewrites fail so reliably it's a cliché. The alternative is a strangler-pattern migration: freeze the external contract, put parity tests around it, and move the system one slice at a time while the old and new run side by side. Slower on paper, dramatically faster in practice — because it ships value the whole way through.

I led exactly this on a US insurtech platform: legacy C# APIs migrated to Django inside a HIPAA / OAuth2 / SAML 2.0 compliance environment, with insurers depending on the system throughout. The method below is the one that worked there.

What's included

Scope of the service

Migration audit & risk mapWhat moves, what stays, in what order — and the honest list of things nobody understands anymore, ranked by blast radius.
  • ▸Codebase and data audit: modules, dependencies, dead code, undocumented behavior
  • ▸Risk ranking by blast radius: what moves safely first, what needs scaffolding
  • ▸Recommended migration order with effort estimates per slice
DELIVERABLEWritten risk map and migration plan — sellable as a standalone first phase.
Strangler-pattern planAn incremental cutover route where each slice is small enough to roll back and valuable enough to justify itself.
  • ▸Routing layer design that lets old and new serve traffic side by side
  • ▸Slice definitions small enough to reverse, valuable enough to justify themselves
  • ▸A rollback plan per slice, tested before each cutover
DELIVERABLEA cutover plan in which no step is irreversible.
Contract parity testsAutomated tests that pin the legacy behavior — including its useful bugs — before anything is replaced.
  • ▸Tests pinning the legacy API's behavior, including the quirks integrators depend on
  • ▸Golden-file comparisons for complex responses
  • ▸CI gate: a slice ships only when parity passes
DELIVERABLEA parity suite that gives 'done' a definition.
Data migration & verificationSchema mapping, migration scripts, and reconciliation reports proving old and new agree before cutover.
  • ▸Schema mapping with transformation rules documented
  • ▸Migration scripts with dry-run mode
  • ▸Cutover rehearsals on production-sized data before the real one
DELIVERABLEReconciliation reports proving old and new agree, row by row.
Compliance-aware handlingRegulated data (HIPAA and similar) handled with audit trails intact through every phase of the move.
  • ▸Audit trails preserved through every phase — no gaps during transition
  • ▸PHI/PII handling mapped to your regime at each step
  • ▸Access-control parity: nobody gains or loses permissions by accident
DELIVERABLEA compliance continuity note you can hand to your auditor.
Team enablementYour engineers work inside the migration, not around it — so the new stack has owners on day one.
  • ▸Your engineers pair on migration slices from the start
  • ▸Decision records for every architectural choice made during the move
  • ▸Working sessions on the target stack's idioms and pitfalls
DELIVERABLEA team that operates the new system without me.
How it runs

Phases specific to this service

These slot into the standard engagement process — discovery, requirement analysis, and a written proposal always come first.

1

Audit & risk map

Weeks 1–2

Read the legacy code, trace the data, interview the people who operate it. Output: dependency map, risk ranking, and the migration order.

2

Pin the contract

Weeks 2–3

Parity tests around the external API surface. From here, 'done' has a definition: the new system passes the same tests.

3

Migrate in slices

Weekly cycles

Endpoints and modules move one at a time behind a routing layer. Every slice is deployed, verified against parity tests, and reversible.

4

Parallel run & reconcile

1–2 weeks per subsystem

Old and new run side by side on production traffic where the risk warrants it; reconciliation reports catch drift before users do.

5

Decommission

Final phase

The legacy system is retired deliberately — data archived, integrations rerouted, and the kill switch thrown only when nothing has called it in weeks.

Proof

Where I've done this before

Shipped work this service is based on — details on the projects page.

Backend Lead
Healthcare & Insurance SaaS PlatformMigrated legacy C# APIs to Django inside a HIPAA / OAuth2 / SAML 2.0 environment while the platform served insurers in all 50 states.
Technical Lead
Mechlin Software TechnologyDirected architecture and technical strategy for cloud-native replatforming; championed the DevOps adoption that made incremental cutovers safe.
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Fit

Is this the right service?

GOOD FIT IF
  • ▸Every new feature costs 3x what it should because of the legacy core
  • ▸The framework or language is end-of-life and the risk is now on a register
  • ▸One engineer holds the whole system in their head — and might leave
  • ▸An auditor or partner has flagged the current stack
NOT A FIT IF
  • ·The system works and the itch is aesthetic — a rewrite for its own sake destroys value
  • ·You want a big-bang rewrite with a hard switchover date — I'll argue against it

ENGAGEMENT · Fixed-scope per migration phase, with the audit (phase 1) often sold alone first — you can take the risk map and stop.

Other services
01Backend architecture & API development→02Full-stack SaaS product development→03Cloud infrastructure & DevOps→05AI-powered tooling & automation→06Fractional tech lead & team leadership→
Contact

Sound like your problem?

Send a short description of what you're building and where it hurts. Discovery call is free; written proposal within a week of requirement analysis.

Email meAll services
[email protected] · +91 79862 35112