Why "It Works in Tests" Is Not the Same as "It Works in Production"?

Have you ever had something that worked perfectly in tests but failed in production?

At some point in your career, you start realizing that passing all tests doesn't automatically mean your system is ready for what will actually happen in production, and this realization usually comes after you have already seen things break in ways no test ever predicted.

In tests, everything is controlled and polite

The data looks reasonable, traffic is limited, dependencies respond on time, and failures happen in isolation instead of all at once.

Production behaves very differently

Users don't follow the happy path, traffic doesn't grow linearly, small delays accumulate, retries amplify pressure, and suddenly a piece of code that always "worked fine" starts showing its weaknesses.

This is where many systems struggle, not because the logic is wrong, but because they were built to be correct, not to be resilient.

Correctness answers the question of whether something works under ideal conditions.

Engineering maturity shows up when you start asking whether it will still work when latency increases, when services slow down, when the database is under pressure, and when multiple small problems happen at the same time.

That's why concerns like caching, timeouts, backpressure, graceful degradation, and observability stop being optional details and start becoming essential design decisions.

Over time, you also realize that the most dangerous problems are rarely obvious bugs. They are hidden assumptions that only reveal themselves under real load and real stress.

Production doesn't reward code that only looks clean or elegant.

It rewards systems that behave predictably when things get messy.

And learning to design for that reality is one of the biggest shifts that separates writing code from engineering systems.