Technical Debt Management

Unchecked shortcuts in development can snowball into bigger problems that slow your team down and destabilize your product. As a developer, learning how to identify and address this hidden burden helps you keep your codebase maintainable and your team productive.

What Is Technical Debt Management?

Technical debt is the cumulative cost of choices made in the name of speed that weren't the best for your application in the long run. Technical debt management is the continuous process of identifying, monitoring, prioritizing, and lowering your debt.

Consider this scenario. You're launching the next hot dating app. Leadership demands a rapid MVP. To hit the deadline, your team cuts corners by skipping unit tests, failing to implement structured logging in the chat services, using manual DB migrations instead of schema-as-code, and tightly coupling profile and recommendation services.

That's technical debt! This poorly implemented solution can lead to several challenges in the long run. 

What Causes Technical Debt?

Technical debt occurs because of a variety of organizational, technical, and human factors. Here's a list of reasons why it accumulates over time:

Quick Fixes

Often, developers employ temporary solutions that aren't sustainable long-term to meet product or feature launch deadlines, like hardcoding API keys and using inconsistent or confusing names for functions and variables.

Some quick fixes are even strategic, such as when a developer implements a temporary patch to recover an e-commerce website from downtime. However, if unchecked, they can throttle your team's velocity and make your project an imminent failure.

Lack of Documentation

Undocumented code turns into a liability over time. When there is a lack of documentation, the team must rely on specific members to maintain the application. This knowledge debt can bring the system to a halt if a particular member leaves the organization.

Outdated Technologies

Working with legacy software or components can add technical debt because it will likely become more difficult to upgrade and maintain as time progresses. Organizations running legacy code are also at a higher risk for cybersecurity threats and compliance exposures. Exploits like zero-days are especially prevalent with outdated open-source software, creating hotspots for malicious actors. 

Incomplete Refactoring

Refactoring regularly can help maintain a better code structure alongside existing functionality. In contrast, incomplete refactoring introduces inconsistency to the codebase, leaving the application in a worse state than before.

The Business Impact of Mismanaged Technical Debt

The 2024 KPMG global tech report showed that 57% of organizations face business disruptions weekly from shortcomings in their core enterprise IT systems, largely tied to chasing new tech without addressing existing debt.

Delayed Releases and Updates

The accumulated shortcuts and patches make everything more convoluted and add to the complexity of the entire codebase. With each new feature comes the challenge of dealing with existing spaghetti code, brittle tests, and undocumented knowledge. This leads to longer release cycles for new products and features.

Higher Maintenance Costs

When you neglect this debt, it can dramatically increase your company's operational spending. 

Over time, code becomes harder to maintain and understand, consuming more resources. Engineers spend more time debugging. On top of that, organizations relying on older technology may need to offer 10x rates, as the talent pool of engineers and contractors working with older technologies is continuously shrinking. 

Product Instability and User Frustration

Systems laden with debt behave unpredictably and crash for unknown reasons. This, coupled with relentless bugs, makes the product unstable, which is a key factor in driving customer churn.

Lost Developer Productivity and Morale

Aside from the codebase, technical debt impacts people, too. Inconsistency in the codebase, missing documentation, hidden dependencies, and countless patches make a developer's job mentally draining. The workplace can turn toxic with constant panic-mode fixes. 

Is Technical Debt Always Bad?

Technical debt isn't always a negative force that drags down development. Good debt is deliberate and strategic, allowing the team to experiment and grow or to maintain flawed stability if change poses risks to compliance or critical systems. Bad debt is unplanned or accidental shortcuts taken due to a lack of knowledge and poor decision-making. 

It's better to get an MVP fast to present it to the business stakeholders and customers to get early feedback rather than getting lost in the world of over-engineering.

Even big companies like Meta and Amazon had once worked under the philosophy of "move fast and break things." It's often necessary to live by this motto to establish early dominance. 

But, even during the MVP phase, teams should acknowledge their debt. It's unacceptable to let an inefficient algorithm cripple production systems over the years.

Similarly, some teams (particularly in government and banking) still rely on legacy systems built with older languages like COBOL, Fortran, and Ada because they're battle-tested, predictable, and highly reliable. The downsides of outdated tech are fewer for them than changing integral systems that do the job well enough.

How To Identify Technical Debt

Here are the warning signs your codebase is succumbing to debt:

Increased Bugs

One of the clear indicators of growing tech debt is an increased number of recurring or hard-to-fix bugs. This debt makes the entire codebase fragile to such an extent that even minor adjustments can severely disrupt core functionality.

Rising CI/CD Build Failures

Continuous Integration and Continuous Delivery (CI/CD) pipelines enable teams to speed up software release cycles. However, when there's a surge of pipeline failures for no clear reason, it signals the codebase has become unstable.

Code Complexity Complaints

Code complexity is a result of poor design decisions. Nested conditionals (if-else, while, and for loops), switch statements with many cases, long functions, and classes are some contributors to this complexity.

Performance Bottlenecks

A performance bottleneck limits overall system throughput. Use of inefficient algorithms (like O(n2)), monolithic architecture, tight coupling between services, and lack of indexes on databases could cause the system to exhaust all its resources. Engineers face scaling challenges when dealing with systems riddled with debt.

Code Coverage Percentage per Feature

Code coverage measures the percentage of functionality covered by automated tests. When developers skip tests to implement features faster, they turn the codebase into a black box where every change is riskier and can break the application. Teams often end up spending more time with manual QA rather than delivering new value.

10 Technical Debt Management Strategies

Here are 10 practical strategies to help you eliminate tech debt and ensure the long-term health and agility of your codebase.

Conduct Regular Code Audits and Reviews

Code reviews enhance knowledge sharing among teams and strengthen the manageability of the code. Properly incorporating code review within the development process helps establish strong coding standards and allows early detection of bugs.

Code audits focus on looking into security gaps, identifying areas of technical debt, deviation from industry standards, and deprecated APIs.

Senior developers, architects, and occasionally third-party consultants are responsible for performing audits and providing insights into the structure, maintainability, and security of the codebase.

Regular code reviews and audits facilitate organizations in improving the health of the overall codebase and fostering a sense of trust within engineering teams.

Prioritize Debt in the Product Backlog (Tech Debt vs. Feature Debt)

Unlike technical debt, which affects code maintainability and scalability, feature debt is related to the backlog of new features that a customer expects from software. Because of its compounding nature, prioritization of tech debt is necessary to maintain a sustainable pace for software release cycles.

Organizations should treat technical debt management as an investment, not a cost. For instance, upgrading a deprecated library or refactoring a critical module can 

pay dividends in the future for greater system resilience.

Create a Debt Register or Scorecard

Creating a debt register or scorecard is a powerful way to bring transparency, accountability, and strategic clarity to how your team manages debt. Rather than letting it accumulate invisibly, a well-structured register turns it into a tracked, measurable, and actionable part of your engineering workflow.

Tools like spreadsheets, Confluence pages, ClickUp, or Jira can help track these issues. Keeping a well-maintained debt scorecard enables organizations to justify debt remediation work in the planning phase.

Refactor Continuously, Not Occasionally

Many software teams only refactor during occasional "tech sprints." Continuous refactoring means improving code quality as part of everyday development. This fosters a culture where developers try to enhance the code quality slowly, but in a sustained manner.

Some examples of continuous refactoring include renaming a poorly named variable while fixing a bug, extracting a long function into smaller, testable units while adding a new feature, and adding missing tests to a module.

Use Feature Flags for Safe Refactoring

Feature flags are conditional switches in code that turn off or on certain features at runtime without deploying new code. This greatly simplifies A/B testing and experimentation. Isolating major changes becomes easier as they can be tested in production-like environments and enabled progressively.

Teams can refactor legacy code with more confidence because the flag can be disabled instantly in case something goes wrong. Organizations can use tools such as FlagSmith, LaunchDarkly, and Unleash to enhance their feature engineering workflows and reduce debt.

Automate Tests and Improve CI/CD

Automated testing is an approach where simple scripts validate software functionality and features. This gives engineering teams fast feedback with consistent results.

CI/CD helps teams to confidently merge new code into a shared repository by running automated builds and tests. A well-integrated CI/CD pipeline with unit, integration, and end-to-end testing provides teams with a robust safety net to detect issues early in development.

Set and Monitor Engineering Quality Metrics

Engineering quality metrics are indicators that allow organizations to assess how well a software system meets its standards. By tracking and taking action on metrics like code complexity, test coverage, code churn, and technical debt ratio, teams can preemptively manage and mitigate debt.

Educate Stakeholders on the Business Case

Product owners often dismiss tech debt as an engineering problem, thinking it has no direct impact on revenue, customer experience, or growth trajectory. This could not be further from the truth. It's the responsibility of an engineering leader to educate stakeholders on how tech debt can cripple the bottom line, competitive advantage, and customer satisfaction.

Apply financial modeling to showcase how this debt can lead to revenue loss over a specific period of time. Use real-world examples where an entire business suffers or goes under because of legacy debt. When stakeholders understand the risk, they're more likely to support proactive investment.

Use the 80/20 Rule to Focus on High-Impact Debt First

The 80/20 rule, also known as the Pareto principle, applies well in software development. You can use tools such as Sentry, SonarQube, and Datadog to gather metrics and identify the part of the codebase causing 80% of the pain. Some areas in which you can look for tech debt hotspots include files that get modified most frequently, parts of the codebase with low test coverage, or by asking others on the development team, "Which part slows you down the most?"

You can prioritize these debts based on a combination of their business impact and technical severity. For instance, you would classify the parts of the codebase that pose security or compliance risks as high priority.

Leverage Prebuilt, Scalable Components

Smaller engineering teams often struggle to build their entire infrastructure alone, and if they do, there remains a high possibility of incomplete, insecure implementations that can accumulate technical debt. In that case, it's better to use prebuilt solutions, like APIs and SDKs, for certain features than to code them poorly in-house.

While it'll depend on the provider, they often come with thorough documentation, customizable UI components, reliable and scalable cloud infrastructure, and more that can speed up development without the risk of debt that comes with taking shortcuts.

Conclusion

Technical debt management makes an inevitable problem easier to overcome, reducing the burden on your engineering team. 

Recognizing tech debt requires active listening to delivery metrics, developer struggles, and friction in scaling. Like financial debt, teams can pay it off by identifying existing debt, prioritizing the worst cases, and avoiding its causes, like quick fixes whenever possible. You can integrate tools such as SonarQube, Sentry, CodeClimate, and Datadog in the DevOps pipeline to discover hidden areas of tech debt.

Your team will never be completely debt-free, but by implementing the strategies discussed above, you can turn your debt into a strategic advantage.