Audit and risk map
We map the codebase, its dependencies, its data and its actual usage, which features are used, and by whom. Plenty of modernization budget gets spent rebuilding functionality nobody has opened in two years.
Services
Legacy application modernization services
The system is fifteen years old, undocumented, and runs the business. Every quarter it gets more expensive to change and harder to hire for. A rewrite has been proposed twice and shelved twice, because stopping feature work for eighteen months is not survivable.
That instinct is right: big-bang rewrites fail at a famously high rate. We modernize in slices, each one shippable, each one reversible, with the old and new systems running side by side until the new one has earned the traffic.
When to call us
You probably need this if…
- The framework or runtime is past end-of-life and security patches have stopped
- Onboarding a developer onto the codebase takes months
- Small changes require regression testing the whole application
- One person is the only one who understands a critical component
How we work
Our approach to legacy application modernization
Incremental decomposition
Strangler-fig pattern: new capability is built outside the monolith and traffic is routed to it a slice at a time. The monolith shrinks as its responsibilities move out, and every step is independently valuable.
Platform and database upgrades
Runtime, framework and database version upgrades with a test harness built first, so you can tell the difference between a behaviour change and a bug. Data migrations are rehearsed against production-shaped data before they are run.
Phased cutover
Feature flags, dual-write where it is warranted, and a documented rollback for every step. Users move in cohorts and the previous system stays available until the new path is proven under real load.
Deliverables
What you actually receive
Artefacts, not activity. Everything here is something you keep, and something you could hand to another supplier.
- Codebase audit with a prioritised risk register
- Target architecture and slice-by-slice migration sequence
- Regression test harness around existing behaviour
- Rehearsed data migration scripts with rollback
- Decommissioning plan for the retired system
Technologies we use for this
- .NET
- Java
- Node.js
- Python
- PostgreSQL
- SQL Server
- Oracle
- Kafka
- Docker
- Kubernetes
More on how we choose between them on our technology stack page.
FAQ
Legacy Application Modernization: common questions
Should we rewrite or refactor?
Refactor unless the platform itself is the constraint: an unsupported runtime, a language you cannot hire for, or a data model that blocks every roadmap item. Even then we replace it in slices rather than all at once. The audit gives you the evidence to make that call rather than an opinion.
Can you work on a system with no documentation and no tests?
That is the normal starting point. We characterise existing behaviour with tests first, so there is a safety net before anything moves. Those tests are also the documentation you were missing.
How do you avoid breaking things during modernization?
Small reversible steps, a test harness around current behaviour, traffic shifted gradually behind flags, and the old path kept warm until the new one is proven. Nothing goes out that cannot be rolled back within minutes.
Talk to us about legacy application modernization
Book a free [30] minutes consultation. You will talk to an engineer, not an account manager, and you will leave with a concrete opinion on your options | whether or not you hire us.