An old system can run for years and still handle the most important processes in a company, and yet it increasingly becomes a brake. Every new feature costs more than it should. And a simple change in the price list or an integration with some external tool turns into a project that takes weeks. At some point the question comes up that returns with almost every major business decision: should modernizing a legacy IT system mean continuing to develop the existing application or rewriting it from scratch? The answer is rarely obvious, because on one side there is proven business logic and on the other a growing technical debt.
At Web Systems we look at this from the contractor’s perspective. Since 2006 we have been designing and maintaining web applications, B2B systems, API integrations and automations, and over those years we have taken over the maintenance of quite a few systems written by someone else entirely. And we know one thing: the decision to rewrite or to develop is not a matter of technological fashion, but of a cool calculation of risk, cost and company goals. In this article we show how to recognize the moment of decision, when to develop, when to rewrite, which intermediate approaches make sense and what to really look at when estimating costs and risks.
Spis treści
How to tell that a system needs a modernization decision
The first signal is usually the cost of changes. When adding a seemingly trivial feature takes weeks of work and careful navigation around fragments of code nobody understands any more, that is a clear sign that technical debt has started to dictate the pace. The second common symptom? A lack of documentation combined with the departure of the people who originally wrote the application. The knowledge of why something works the way it does leaves with them. And every modification turns into a game of guessing the consequences.
At the same time the security risk grows. Outdated libraries, an obsolete version of the language or framework, no regular updates – these are open doors for vulnerabilities that have had public exploits for a long time. In systems processing personal data or payments, such a state is no longer just a technical problem but also a matter of legal compliance. On top of that come performance problems that surface as the number of users or the volume of data grows, because an architecture designed years ago simply did not anticipate today’s scale.
Integrations are a category of their own. New tools, payment gateways, accounting systems and marketing platforms expect modern APIs and data exchange formats. An older system often cannot connect to them without costly workarounds, and sometimes cannot connect at all. Below we have gathered the typical symptoms of technical debt that we observe during audits:
- every change requires manual testing, because there are no automated tests
- deploying a new version is stressful and gets postponed to weekends
- nobody on the team feels confident in the critical modules
- the libraries and the environment are no longer supported by the vendor
- data is scattered and there is no single source of truth
If you recognize several of these points at once, the decision about the direction of modernization stops being optional. It becomes merely a matter of time and money.
When it pays to develop the existing application
Developing an existing application makes sense more often than the enthusiasm for writing everything anew suggests. The strongest argument? Proven business logic. If for years the system has correctly handled orders, settlements or document workflow, then it contains hundreds of decisions and exceptions that cost real time and real money. That knowledge is valuable and there is no reason to throw it away carelessly. The second condition is the state of the code: if it can be read, and the structure, imperfect as it is, allows changes to be made safely, the foundation is fit for further work.
In that case the optimal approach is gradual modernization. It consists of refactoring the critical fragments, updating dependencies to supported versions and systematically adding tests that guard against regressions. This mode of work has a huge business advantage: the system keeps running for the entire duration of the work. The company does not stop selling or serving customers, and the risk is spread over small, controlled steps instead of one big leap into the unknown.
In practice the order matters. Before we start bigger changes we begin by getting the lay of the land, because blind refactoring without a safety net quickly ends in errors that are hard to catch later.
Tip: Start with a code audit and test coverage of the most important business paths before you touch the architecture at all. Tests act as a safety net and give you the confidence that further improvements do not break anything.
Developing the existing application also works well when the budget is limited and time pressure is high. Incremental modernization lets you finance the work in stages and observe the results after each phase. It is also easier to manage the expectations of the team and the board, because progress is visible to the naked eye, and the risk that the project stalls is much lower than with a full rewrite. In many projects it is exactly this consistent, well planned development that brings a better return than an expensive restart.
When it is better to rewrite the application from scratch
There are, however, situations in which further patching delivers less and less and a rewrite becomes the more sensible investment. The first: an architecture that fundamentally blocks development. If every change requires modifications in a dozen places, and the modules are so tangled that they cannot be separated, the cost of maintenance grows faster than the value the system delivers. The second signal is technology that is no longer supported: no security updates, a disappearing market of specialists and the impossibility of running the environment on modern infrastructure.
Another argument is the limits of scale. When the system cannot be scaled sensibly as traffic grows, when the data structure no longer keeps up with the needs, and API integrations require ever more precarious workarounds, incremental modernization can end up costing more than building a new foundation. In such cases a rewrite is not a whim but a way to regain control over the cost of further development.
The risks have to be named honestly, though, because a rewrite can be a trap. The biggest threat? Losing the knowledge embedded in the old code – all those exceptions and business rules that were never documented anywhere. The second is the notorious underestimation of scope: the new system has to reproduce the entire functionality of the old one before it adds anything new. And that is usually far more work than the first estimates assume.
A typical mistake: rewriting everything at once, in big-bang switchover mode, where the old system is turned off only after the whole new one is finished. Such a project can drag on for months without a working result, and the pressure grows with every week. That is why, even when we decide on a rewrite, we split it into stages and keep the old system alive for as long as necessary – so that the risk stays under control and the company does not lose continuity of operations.
Intermediate approaches – strangler fig, staged migration, extracting modules
Between full development and a complete rewrite lies an area of intermediate solutions, which in practice work best most often. The best known is the strangler fig approach, that is, gradually wrapping the old system with new services. New features are built in modern technology and traffic is redirected to them piece by piece. The old code lives as long as it is needed and fades away naturally once all of its responsibilities have been taken over by the new components. As a result the system runs without interruption and the risk is spread into small portions.
The second tool is breaking the monolith into smaller modules or services – where that is justified. We stress that condition, because microservices are not a goal in themselves and can add a lot of operational complexity. We extract the fragments that change most often, have a clearly separate responsibility or require independent scaling. The rest can stay in a coherent module until there is a real reason to split it.
A separate and often underestimated stage is data migration. It is one of the riskiest elements of the whole undertaking, because data can be inconsistent, contains historical exceptions and does not fit the new model without transformation. Migration requires its own plan, a test environment and verification of correctness on real data sets, not just on nice examples. A good practice? Run both systems in parallel and compare the results before the old one is switched off.
These approaches share one architectural principle: separation of responsibilities and a single source of truth for each type of data. When it is clear which component owns a given piece of information and only that component can change it, the system becomes predictable, easier to test and more resistant to errors. And it is exactly this discipline, not the choice of a particular technology, that determines whether further development will be cheap and safe or will once again turn into mounting technical debt.
Costs, risks and maintenance – what to look at when deciding
A modernization decision should be based on comparing costs over a horizon of several years, not just on the price of the nearest rollout. On one side there is the cost of maintaining the old system: the growing number of hours needed for minor changes, the risk of outages, the cost of keeping obsolete infrastructure running and the increasingly expensive access to specialists who know the technology. On the other side is the cost of modernization, which is often higher at the start but pays for itself through the lower cost of every subsequent change. Only putting both curves side by side over a three to five year horizon shows the real picture.
When making the assessment it is worth sticking to a few clear criteria. They help separate the engineering decision from emotions and technological fashion:
- Security – can the system be updated and does it protect data in line with the requirements
- Compliance – does it meet industry and legal regulations today and in the foreseeable future
- Scalability – will it carry the growth of traffic and data without rewriting the foundations
- Cost of further development – how much does adding a typical new feature really cost
A less visible but, in my view, decisive factor is the testability and readability of the architecture. A system covered by tests and divided into components with clear boundaries generates far less technical debt, because every change can be introduced safely and verified quickly. It is exactly this quality that has the strongest influence on the cost of maintenance in the long run. And at the same time it is the hardest to appreciate until it starts to be missing.
Finally, it is worth looking at the future of the system. A modern version of an application is not just a refreshed interface, but also readiness for integrations, the automation of repetitive processes and AI-based solutions such as document analysis or support for customer service. The modernization decision is therefore at the same time a decision about how capable the system will be of taking on further improvements without another costly revolution.
FAQ – the most common questions about modernizing IT systems
Does modernization mean downtime for the company?
In most cases no. A well planned modernization, especially in an incremental model or in the strangler fig approach, lets you keep the system running throughout the work. Changes are introduced in stages and new components are launched alongside the old ones, with traffic redirected only after testing. The risky moment tends to be the data migration and the final switchover – which is why we plan them separately, with the option to roll back. With proper preparation, end users often do not even feel that a deep rebuild is going on underneath.
How long does rewriting an application take and what does the time depend on?
There is no single number, because the time depends on the complexity of the business logic, the number of integrations, the quality of the data and how well the old system is documented. What usually takes the most time is not writing the new code, but reproducing all the rules and exceptions hidden in the existing application. That is why a thorough audit at the beginning shortens the whole project, because it allows a realistic estimate of the scope. A staged approach means the first working fragments appear quickly and the whole thing matures gradually.
Can a system be modernized in stages on a limited budget?
Yes, and that is often exactly what we recommend. We split the modernization into phases, starting with the areas of highest risk or highest maintenance cost, where improvement brings the fastest return. Each stage is priced separately and delivers a measurable effect, so the budget can be spread over time and the work financed from the ongoing benefits. This approach limits the risk and lets you pause or re-plan the project if the company’s priorities change.
Summary
There is no single universal answer to the question of whether modernizing a legacy IT system should mean further development or a rewrite from scratch. It all depends on the state of the code, the quality of the architecture, the business goals and the real cost of maintenance over a horizon of several years. When the logic is proven and the code can be read and tested, it usually pays more to develop the existing application step by step. When the architecture blocks development and the technology is no longer supported, a controlled, staged restart tends to make more sense. And most often the best results come from intermediate solutions that combine the advantages of both paths.
What matters most is that this decision follows from an audit and hard criteria – security, scalability, testability and the cost of further development – and not from a fashion for a particular technology. A well conducted analysis lets you avoid two extremes: pointlessly rewriting a working system and keeping alive a solution that generates nothing but costs and risk.
If you are facing such a decision, at Web Systems we will help you make it based on facts. We start with an audit, show you the real options and carry out modernization, integrations, automations and AI implementations in a way that does not bring your company to a halt. Get in touch with us if you are planning an MVP, a new application, a systems integration or the modernization of an existing solution – we will gladly advise you on where it is best to start.
