Let’s face it – many established companies are live software museums. Marketing often advertises it as cutting-edge, state-of-the-art, and crème de la crème. But under the hood, in the age of AI, our world still relies on vintage technology.
Chemical terminals use 25-year-old tools that work in Internet Explorer 5 only, trains run on Windows XP, and who knows what Perls you may find in a traditional banking sector?
Why on Earth?
I have a theory: when businesses buy products or services, their expectations are proportional to the commitment. One does not simply take away a tool folks used for decades. This phenomenon is called technological inertia.
Then, one day, customers riot, demanding high-speed wi-fi on the Win XP train. You order golden routers and do a lab test. During the rollout, two million people join the network. The electric system fails. Trying to fix lights, you break doors. The release reverted via USB drive downgrade on 250 trains, 13 bricked in the process. Passengers are happy the doors work again.
Meet sunk cost fallacy: individuals or organizations may have invested heavily in the existing technology. And they are unwilling to abandon that investment, even if a new solution would be more cost-effective in the long run.
The point of no return is called don’t touch if it works. The longer it remains without a change, the more untouchable it gets. Crossing this Rubicon means an expensive and lengthy upgrade ahead.
Vehicle management at car2go
At car2go (carsharing company), I worked in the vehicle lifecycle management team. We took ownership of a relatively fresh Angular 1 single-page app developed by an external agency.
Our motivated team started making changes. I remember applying a fix that caused seven new bugs. This pattern repeated again and again. Skilled and experienced engineers could not maintain the stability bar set by the company. Only manual QA saved us because automated tests did not catch issues.
The situation was spiraling out of control. We proceeded with caution, and that slowed our progress. During retrospectives, we began questioning our course of action. Some code was relatively fresh, though the main pain point was data binding side-effects in convoluted controllers.
On the API side, challenges were more significant – multiple databases were out of sync, critical bugs in queue processing, inconsistent data, and limited observability.
Big bang is not an option
Our team concluded it was pragmatic to rethink the architecture. We needed modularity to achieve a better user experience. And a trunk-compatible system design that makes daily releases possible.
The head of engineering recognized the added value of the transition to innovation-friendlier architecture. Five engineers and a PO with QA and PM support performed zero downtime incremental upgrades that took 1.5 years to complete. For vehicle management, it was an investment that paid off.
When you operate a fleet of expensive cars, the difference between email damage tracking and an automated system could be millions of euros per year. According to my calculations, the return on investment was around 5-7x.
How to keep up with the progress?
Recently, micro-service architecture has been a subject of wide criticism. Watch this brilliant video.
Michael Paulson, aka The Primeagen, a prominent yelling tech figure, likes to mock startups for having more services than users.
The core issue is not a particular architecture. Humans associate failures with things they dislike. Be it a monolith, micro-services, or a framework. But the true killer is the complexity.
I see a repeating pattern occurring in established companies. Software is left unattended for some time. People join and leave, and priorities shift. Suddenly, a vintage marvel becomes a development blocker because multiple critical parts depend on it. Organizations invest astronomical amounts into legacy system integration.
Take action before it’s too late, and keep making changes as the product evolves. Motivated people recognize when something doesn’t work. When it happens, the lead must make a calculated decision.
How to address it?
There is a better alternative – invest in reasonable modularity. I build high-performance, innovation-friendly software that helps companies avoid expensive upgrades and legacy service pain. Estimated ROI within five years +600%.
Does it resonate with your experience? I'm curious to hear how you integrate vintage software. And how do you keep up with the WILD pace of change in the web tooling?
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