Service · Legacy System Upgrades
Legacy SystemUpgrades
Your system works. Throwing it out costs money. Not upgrading it — is a gamble.
You have a system. It works. It handles customers, money, the core processes of the business. Even if it's built in AngularJS (not Angular), PHP 5, .NET Framework, or Java EE — it gets the job done.
Until today.
Developers who know the tech are retiring or moving on. Adding a new feature takes two months instead of two weeks. Libraries with known vulnerabilities that no longer get updates. A system burning 10x the resources it should. And a customer complaining that the UI looks like 2010.
One day, something will break. The question is: are you driving the upgrade on your terms — or is it driving you when the system collapses?
We do smart upgrades. Without breaking what already works. Without a two-year "big bang."
01 / Why not just rebuild
Why not just "rebuild from scratch"?
It's the tempting option. It's also why most full-rewrite projects fail.
There's a third way: gradual modernization. One system, upgraded component by component, with the business running through most of the stages.
02 / What we do
What we do
From audit to CI/CD — through frontend, backend, database, cloud and UI. Everything needed to bring a system into 2026.
03 / Our approaches
Our approaches
We recommend the right approach for each case — after we've seen the system and understood the business.
04 / How an upgrade is planned
Diagnosis, alternatives, and a transition plan you can roll back from.
'The system is old' is not a diagnosis. Before deciding what to upgrade, you need to know exactly what is blocking the business, what depends on what, and which parts can be replaced without touching the others. This is our order of work.
What is actually blocking the business?
The diagnosis starts from the symptoms the business feels — not from the technology version. Each symptom has a likely technical cause, and each cause has a fix of a different size.
| What the business feels | Common technical cause | What the diagnosis checks |
|---|---|---|
| Every small change takes weeks | No automated tests; code where everything depends on everything; manual deployment | How long from fix to production, how much of that is waiting, and where things break after a change |
| Hard to find developers willing to touch it | A technology no longer taught; versions without support; knowledge held by one person | Which components are end-of-life, who in the organization knows each part, what happens if that person is unavailable |
| The system is slow or falls over under load | Inefficient queries, a single server, no monitoring that shows where the time goes | Measurement before assumption: which screens and actions are slow, when, and in which component |
| New tools cannot be connected | No API; data is reachable only through the screens or straight from the database | Which integrations the business needs in the coming year, and the shortest way to expose data without rewriting |
| Worry about security or compliance | Libraries with known vulnerabilities, old encryption, blanket permissions, no audit log | A dependency scan, a map of who can access what, and which regulatory requirement actually applies |
Map before you change
Staged upgrade versus full rewrite
Both routes are legitimate. The difference is what you risk, when you see a result, and what happens if something goes wrong halfway.
| Comparison | Staged upgrade | Full rewrite |
|---|---|---|
| What happens to the existing system | Keeps running; parts of it are replaced one by one | Keeps running unchanged until cutover day, then is retired |
| When the first result is visible | After the first component — usually early | Only when the new system is complete enough to replace the old one |
| The main risk | A long period of two technologies side by side; the temptation to stop halfway | Forgotten business logic surfaces only after cutover; a single cutover day on which everything hangs |
| What happens if it goes wrong | Roll back the one component; the rest of the system is unaffected | Roll back to the whole old system — if the data created in the meantime can be restored |
| When it is the right call | When there are parts worth preserving, when the business cannot stop, and when the existing team needs to keep working | When the diagnosis shows nothing worth preserving, or the platform itself is ending |
The transition plan — what is in it
Every stage of the upgrade gets the same one-pager: what moves, when, who is responsible, how it is verified, and how to roll back. Without that page there is no stage.
| Item | What is defined | Example (illustrative) |
|---|---|---|
| Stage scope | The component or process that moves, and what is explicitly not touched | The orders screen moves to the new frontend; the API and database stay |
| Data migration | Which data moves, how fields are mapped, and how arrival is verified | A trial run on a copy; record counts compared; an exceptions report |
| Testing | What is tested automatically, what is tested by users, and what counts as 'pass' | Regression tests on the existing calculations; two users from the team run a full process |
| Owners | Who signs off on your side, who is responsible on ours, and who decides whether to stop | The operations manager signs off; our team lead is responsible; either can stop |
| Transition window | When the cutover happens, how long it should take, and what users will notice | Outside working hours; users notified in advance; the form changes — the data does not |
| Rollback | What triggers a rollback, how it is done, and what happens to data created in the meantime | If the order flow fails for more than one user — the old screen is restored the same day; the data is shared, so nothing is lost |
What happens after the upgrade
05 / Technology
Our stack
Known migration paths — from old frontend to modern cloud. With the tools that make the transition smooth.
Frontend migration
- AngularJS → React
- jQuery → Modern JS
- Backbone → Next.js
- SSR → SPA
Backend migration
- PHP 5/7 → Laravel
- .NET Framework → .NET 8+
- Java EE → Spring Boot
- Old Ruby/Python → modern
Database migration
- Old MySQL → PostgreSQL
- Oracle → PostgreSQL
- MongoDB upgrades
Cloud migration
- On-Prem → AWS
- On-Prem → GCP
- On-Prem → Azure
- Heroku → Vercel/Railway
Tools
- AWS DMS
- Azure Migrate
- Strangler Frameworks
- Feature Flags
- Blue/Green Deploy
Architecture
- Monolith → Microservices
- Event-driven
- API Gateway
06 / How we work
How we work
- 01
Comprehensive audit
Not just the code — processes, documentation, team habits too. The whole system.
- 02
Risk report
What's the biggest risk? Security? Operations? Maintenance? You decide what's most urgent.
- 03
Modernization plan
A clear roadmap: what to upgrade, in what order, on what timeline, in what budget. With checkpoints along the way.
- 04
Gradual upgrade
Sprints of 2 to 4 weeks. Each sprint — one component upgraded, tested, and shipped to production.
- 05
Tests at every step
Not just that the new works — that the old doesn't break. Automated regression testing.
- 06
Knowledge transfer
Your developers learn along the way. By the time the project ends — the internal team knows how to maintain it.
07 / Who it's for
Who this is for
08 / Why us
Why us
FAQ
Frequently asked questions
Yes. Those are two of the most common cases we see. There are ways to migrate gradually to React/Next.js without breaking the existing system.
There is no honest flat price for a legacy upgrade: the budget follows scope. The drivers are how much of the system is actually blocking the business, whether a staged upgrade or a rewrite is the right call, how much undocumented behavior must be reverse-engineered, and how the transition is staged so the business keeps running. We scope the work first, then give a fixed, itemized quote — what is included, what is excluded and what would change the number. The mapping stage produces the plan, and the plan is what we quote against.
The upgrade timeline depends on the system's condition, the scope of the changes and its dependencies. After the assessment, we define a work plan and milestones based on the findings.
In most cases, no. We use feature flags, blue/green deployment, and the Strangler Pattern — changes roll in gradually without disruption.
Not required. We can run in parallel — new features on the new stack, fixes on the old. Both slow down a little, but neither stops.
React/Next.js for frontend, Node.js/Python/Go for backend, PostgreSQL for DB, cloud (AWS/GCP). But we adapt — sometimes staying on Java/Spring is the right call.
It's part of the challenge and we handle it. Training, mentoring, explaining the value. Your team is brought into the project — not pushed aside.
From an audit of what you have: services, dependencies, data, sensitivity. From there — pick a strategy (Lift & Shift, Replatform, or Refactor).
Depends. SAP, Oracle, Salesforce and the like — we work on integration and upgrades, not always full replacement (that's a specialized domain). Happy to assess.
Checkpoints every sprint (2 to 4 weeks). Each sprint — a component upgraded, shipped to production, visible. No "surprises at the end."
Built before 2018? Dependencies that don't update? Hard to hire developers for it? Fixes that take months instead of weeks? Probably legacy. Book a meeting — we'll look together.
As part of the project — we create documentation. Sometimes it's the first real documentation the system has ever had. An asset in itself.
Absolutely — and it's one of the strongest justifications for modernization. Adding AI into old workflows can save thousands of hours. We do this work.
A staged upgrade replaces the system piece by piece while it keeps running; a full rewrite builds a new system beside the old one and swaps it in at once. The decision follows from the diagnosis: how much of the problem sits in parts that can be isolated, how much undocumented business logic there is, and how long the business can live with two systems. A rewrite is not our default — it is chosen when the diagnosis shows there is nothing worth preserving.
For every stage: what moves, when, who is responsible on your side and on ours, how it is verified, and how to roll back if it is not. Without the rollback clause there is no plan — only hope.
Keep reading
- ComparisonVibe Coding vs production engineering — when each one fitsMVPs from Cursor/Lovable/Bolt vs production-engineered code. What AI tools handle, where they break, and how to migrate between the two.
- ServiceTechnology & product consulting — the decision before the buildA one-off consultation, a professional audit with a recommendations document, or ongoing CTO advisory. Architecture, code review, development and AI strategy — with no commitment to build with us.
Let's talk
From legacyto 2026.
A 30-minute intro call. No strings attached. We'll look at the system together, tell you what we see — and how to upgrade without taking the business down.
Straight. To the point. On time.