Lack of Incidents Is Not Evidence of Stability

Many organizations use incident frequency as a proxy for system health.

If nothing has broken recently, the system is assumed to be stable. If uptime is high and pages are rare, reliability is treated as solved.

This assumption is convenient, but it is often wrong.

In practice, the absence of incidents usually says very little about whether a system is well understood, resilient, or safe to change.

Quiet Systems Can Still Be Risky

Low incident counts tend to mean one of three things:

• The system has not been stressed in a meaningful way

• The same small group of people is still holding it together

• Failure modes exist, but have not been triggered yet

None of these indicate stability. They indicate luck or containment.

Many fragile systems operate for long periods without visible failure. When they do fail, the impact is usually larger than expected, and recovery takes longer than planned.

Where the Cost Actually Shows Up

The real cost of uncertainty appears before the first outage.

Teams working on systems they do not fully understand behave differently, even if uptime is perfect. Changes take longer. Reviews become heavier. Manual checks are added “just to be safe.” Deployment windows shrink.

Over time, delivery slows down. Not because the work is harder, but because the system is unpredictable.

Velocity drops before reliability does.

Caution Becomes Policy

This slowdown is rarely explicit.

No one announces that the system is risky. Instead, teams compensate quietly. They add approval layers, freeze periods, and informal rules about when it is safe to change things.

What started as caution hardens into process.

At that point, the system still works, but it no longer supports momentum. Engineering effort shifts from building to avoiding mistakes.

Low Incidents Can Hide High Risk

One of the most misleading signals in software systems is “we haven’t had a major incident.”

That statement often depends on specific people still being available, historical assumptions still holding, and traffic patterns not changing in unexpected ways.

The most damaging failures tend to happen when one of those conditions changes. Staff turnover, growth, integration work, or external dependencies expose gaps that were always there.

The lack of previous incidents does not reduce the risk of future ones. It often increases surprise.

Stability Is About Predictability, Not Silence

A stable system is not one that never fails. It is one whose failure modes are understood.

Teams can reason about what will break, how they will detect it, and what recovery looks like. Because of that clarity, they can change the system with confidence.

Predictability enables speed. Silence does not.

A Useful Question

Instead of asking how long it has been since the last incident, a more useful question is:

What would happen if this system failed in a way we did not expect?

If the answer is unclear, if recovery depends on specific people, or if teams would need to improvise under pressure, the system is already constraining the organization. Just quietly.