A product manager asks for what appears to be a small change: add one field to an existing customer workflow.
Engineering estimates two weeks.
The field itself might take an afternoon. The rest of the estimate comes from everything surrounding it. The same data model is used in several unrelated places, tests around the workflow are unreliable, one integration expects the old payload and nobody is completely sure whether a production configuration was ever captured in version control.
Nothing is obviously broken. Customers are still using the application every day.
Yet a small change has exposed something important about its health.
That is often how technical debt becomes visible. Not through a dramatic outage, but through friction: ordinary work takes longer, updates become riskier and engineers spend increasing amounts of time working around decisions made months or years earlier.
The Software Engineering Institute defines technical debt as design or implementation choices that may be expedient in the short term but create a technical context in which future changes become more costly—or potentially impossible. SEI: Managing the Consequences of Technical Debt
That definition explains why technical debt matters to App Health.
Technical debt affects application health when yesterday's shortcuts begin reducing today's ability to operate, understand, secure or change the application safely.
The debt may live inside the codebase, architecture, tests, documentation or technology stack. Its consequences can appear almost anywhere.
The term is often used so broadly that almost anything imperfect gets called technical debt.
Old code becomes debt. Missing documentation becomes debt. A bug becomes debt. A technology somebody dislikes becomes debt.
That makes the concept much less useful.
Martin Fowler's discussion of the Technical Debt Quadrant makes an important distinction: some debt is deliberately accepted to achieve a short-term objective, while other debt accumulates through poor understanding or careless decisions. The metaphor is useful because it helps teams think about the future cost created by today's technical choices, not because every flaw should automatically be labelled debt.
A team might deliberately release a feature using a simpler architecture because getting to market quickly is more valuable than building for hypothetical future scale. That decision is not necessarily unhealthy.
It becomes a health problem when the circumstances change but the compromise remains.
Perhaps usage has grown tenfold, yet the original architecture is still expected to carry it. Maybe the “temporary” manual deployment step has been in production for three years, or a dependency upgrade repeatedly gets postponed because the surrounding code has become difficult to change.
The health question is therefore not:
Does this application contain technical debt?
Almost every mature application does.
The better question is:
Is the debt now restricting the application's ability to remain healthy?
The most characteristic effect of technical debt is that normal changes become harder than they should be.
The Software Engineering Institute explicitly describes technical debt as affecting maintainability and evolvability and notes that unmanaged accumulated debt increases development and sustainment costs. SEI: Managing Technical Debt in Complex Software Systems
This is the software equivalent of paying interest.
A feature that once required changing one component now touches five because responsibilities were never separated properly. A library update needs weeks of regression work because test coverage is weak, while an engineer spends two days understanding a module before making a ten-line change because its behaviour is poorly documented.
The business experiences this as increasingly slow delivery.
The engineering team experiences it as friction.
Within Levelworks' App Health model, that friction often appears across Explainable & Debuggable, Tested, Current & Updated, Well Documented and Seamlessly Updatable rather than living inside one neat “technical debt” category.
This is why technical debt can damage health without causing any immediate production failure.
[Internal Link: “10 Warning Signs Your App Needs Maintenance”]
Debt also changes what happens when something goes wrong.
Consider two modules containing the same defect.
The first is well structured, has reliable tests and produces useful diagnostic information. An engineer can locate the cause, make a targeted correction and verify that the fix did not affect neighbouring functionality.
The second contains tightly coupled logic, limited tests and years of incremental workarounds. Fixing the same defect requires understanding several indirect dependencies, manually checking unrelated workflows and hoping an unexpected side effect does not reach production.
The bug is identical.
The health of the surrounding software changes the cost of correcting it.
This relationship has been observed empirically. A study of ten open-source PHP applications found that modules with greater measured technical debt were more defect-prone and required more corrective-maintenance effort. The Relation Between Technical Debt and Corrective Maintenance in PHP Web Applications
That does not mean technical debt mechanically causes every defect. It does show why debt and application-health problems often reinforce one another.
Weak internal structure makes defects harder to avoid and harder to correct; frequent corrective work then consumes the time that might otherwise have been used to reduce the underlying debt.
Technical debt becomes particularly damaging when teams lose confidence in their ability to change the application safely.
Suppose an important component has little reliable test coverage.
The first consequence is obvious: engineers have less automated evidence that a modification behaves correctly.
The second is more significant. Because changing the component feels dangerous, teams begin avoiding it.
A dependency upgrade is postponed. Refactoring is deferred. Compatibility changes are kept to the minimum possible. Developers add another special case because changing the underlying design carries too much uncertainty.
Now technical debt is generating more technical debt.
This affects several App Health dimensions at once. Tested is weak because behaviour is difficult to verify, while Seamlessly Updatable deteriorates because releases involving that component require disproportionate effort. Eventually Current & Updated may weaken too because necessary modernization becomes difficult.
Google's engineering practices describe code health as something that can decline through many small compromises over time, particularly when teams are under delivery pressure. Google's code-review standard explicitly favours changes that improve maintainability, readability and understandability rather than allowing a codebase to deteriorate gradually. Google Engineering Practices: The Standard of Code Review
Technical debt rarely arrives as one enormous decision.
Often it is the accumulated effect of hundreds of individually understandable ones.
Not all technical debt is architectural.
Deferred upgrades can become debt too.
The SEI specifically notes that delayed technology refreshes, upgrades and sustainment work can fall within the technical-debt problem when they make future change more expensive. SEI: Recommendations for Managing Technical Debt
Imagine an application that remains on an old framework because upgrading does not deliver any visible customer feature.
The first postponed release may not matter much. After several years, however, the application may need a newer runtime before the framework can be upgraded, while another dependency is no longer compatible with either version.
What would once have been a routine upgrade becomes a migration project.
This is where technical debt begins affecting Current & Updated directly, but the impact can spread further.
An ageing technology stack may become harder to patch securely, harder to run on newer platforms and harder to connect with modern integrations. The original debt therefore begins weakening Secure, Compatible and Integrable as well.
[Internal Link: “How the Different Dimensions of App Health Work Together”]
One reason technical debt is easy to postpone is that users may not experience it immediately.
An application with tangled code can still respond quickly. An undocumented deployment process can run successfully for years because the same engineer manages every release, while an unsupported dependency may continue functioning perfectly.
The application may look healthy from the outside.
Technical debt frequently affects the cost and risk of future action before it affects current user experience.
That distinction matters.
App Health is not only about whether the software performs its job today. It also considers whether the organisation can keep that software secure, supported and changeable as the environment moves around it.
A system that performs beautifully but requires three weeks of preparation for a small security patch carries a real health weakness, even if customers have never experienced an outage.
Architecture debt becomes particularly damaging when boundaries inside the application no longer match the way the product needs to evolve.
Imagine customer billing, notifications and account management all depending directly on the same internal customer model. A seemingly simple change to that model now creates consequences across three unrelated areas.
The problem is not merely that the code is complicated.
The application has lost locality of change: teams cannot modify one concern confidently without reasoning about many others.
This influences Explainable & Debuggable because behaviour is harder to trace, Tested because the regression surface becomes larger, and Seamlessly Updatable because every change carries a wider deployment risk.
Technical debt of this kind also makes product development progressively slower. New functionality has to accommodate old coupling instead of being built around the needs of the current product.
Eventually, teams begin designing the roadmap around what the application can tolerate.
That is a significant health signal.
Some technical debt exists outside the code itself.
A system may be reasonably designed but difficult to operate because important knowledge was never recorded.
Perhaps only one engineer knows why a particular configuration exists, how a critical integration authenticates, or what manual step has to happen after a deployment.
Nothing is wrong while that person is available.
The debt becomes visible when somebody else needs to change or recover the system.
This is why Well Documented and Supported are part of Levelworks' App Health framework. Missing knowledge increases the cost of maintenance and can also make Explainable & Debuggable weaker because engineers must reconstruct historical decisions before investigating current behaviour.
Documentation debt is particularly deceptive because it often has almost no immediate runtime effect.
The application can remain technically stable while becoming progressively more dependent on institutional memory.
Instrumentation itself accumulates debt.
An application may contain logs added over many years without a coherent structure, dashboards that reflect architecture no longer in use, or alerts that have become so noisy that engineers ignore them.
This creates an interesting relationship between technical debt and Observable.
The application is generating enormous amounts of operational data, yet the team's ability to understand its health is declining.
The result can be longer detection times, slower diagnosis and greater reliance on users to report problems.
Technical debt is therefore not confined to business logic. Monitoring, build systems, deployment tooling, test environments and operational processes can all accumulate decisions that were once expedient but now make maintenance harder.
One of the clearest ways technical debt becomes visible is in the delivery process.
DORA's software-delivery metrics examine both throughput and instability, including change lead time, deployment frequency, failed deployment recovery time, change fail rate and deployment rework rate. DORA's research treats speed and stability as related capabilities rather than assuming teams have to choose one or the other. DORA Software Delivery Performance Metrics
Technical debt can place pressure on both sides.
Changes take longer because engineers have to understand or work around fragile code, while deployments become less predictable because the effects of a modification are harder to anticipate.
When a release fails, recovery may also take longer because the system is difficult to debug or the deployment process itself contains debt.
The application may therefore remain available most of the time while becoming progressively less Seamlessly Updatable.
That is why rising change lead time or increasing release rework can be useful indirect signals of application health.
Not all technical debt grows equally.
Consider two examples.
The first is a poorly structured internal report that changes once every three years. Cleaning it up might be worthwhile, but leaving it alone creates relatively little ongoing cost.
The second is the authentication layer of a SaaS application. It changes regularly, depends on external libraries and sits inside nearly every user journey.
The same amount of technical imperfection creates very different health consequences.
The SEI describes technical debt as a contingent liability because its impact depends partly on how the system needs to evolve.
This leads to an important principle:
Technical debt becomes most damaging where future change is frequent, important or unavoidable.
Debt around security-sensitive components, core business workflows, rapidly changing integrations or foundational architecture deserves more attention than debt in a stable, low-impact area that rarely needs modification.
Because technical debt can damage App Health, it is tempting to conclude that teams should remove as much of it as possible.
That would be a mistake.
Technical perfection has a cost too.
Rewriting stable code with no meaningful maintenance burden may provide less value than improving monitoring, fixing a user-facing reliability problem or building something customers actually need.
The important distinction is between debt that exists and debt that is creating harmful interest.
A useful review asks:
Question
What it reveals
How often do we need to change this area?
Frequently changed debt generates more friction.
Does it cause defects or incidents?
Operational consequences increase its importance.
Does it block security or dependency updates?
Debt may be affecting Current & Updated and Secure.
Does it make releases unusually risky?
It may be weakening Tested or Seamlessly Updatable.
Does only one person understand it?
Documentation and supportability are involved.
Will delaying it materially increase future effort?
The debt may be compounding.
This is a much more useful basis for prioritisation than “old code should be rewritten.”
Martin Fowler's technical-debt framing is helpful here because debt can sometimes be a deliberate and economically sensible trade-off. The important part is understanding when the interest has started outweighing the value gained from taking it on.
The strongest sign that technical debt has become unhealthy is not ugly code.
It is lost freedom.
The team cannot upgrade a vulnerable dependency because too much else would break. A product change is postponed because one component is considered too dangerous to touch. A new integration cannot use the preferred SDK because the application runs on an obsolete runtime, while an incident takes hours longer to diagnose because nobody understands why the system was designed the way it was.
At that point, yesterday's compromises are controlling today's decisions.
That is where technical debt connects most directly to Levelworks' view of App Health.
Healthy applications do not need to be debt-free. They need their debt to remain understood and contained enough that the software can still be Secure, Current & Updated, Tested, Explainable & Debuggable, Well Documented and Seamlessly Updatable when the business needs it to change.
[Internal Link: “What Happens When You Stop Maintaining an App?”]
Technical debt becomes dangerous when those options begin disappearing.
The important question is therefore not:
“How much technical debt do we have?”
It is:
“What is our technical debt preventing this application from doing safely, efficiently or confidently?”
That is the point where technical debt stops being an internal engineering concern and becomes a measurable problem with the health of the application itself.
