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Technical Debt: When to Pay It Off and When to Live With It

· 8 min read
Ayoub Abidi
Ayoub Abidi
full-stack developer

Technical debt is a concept known by almost every software development team. Just like financial debt, technical debt increase over time, making the codebase more and more difficult and expensive to maintain.

technical-debt

This article will present the nuances of technical debt management, focusing specifically on when you should prioritize paying it down and when it might be reasonable to live with it. We'll examine concrete indicators, practical strategies, and real-world scenarios that could help development teams make relevant decisions about their technical debt.

TL;DR​

Technical debt is similar to any other debt: it's not necessarily bad, but is becoming dangerous if ignored. You should accept it wisely, track it clearly, and pay it off when the cost of keeping exceed the benefit.

In other words: write fast but refactor smart.

Understanding Technical Debt​

Before deep diving into the various management strategies, it's important to understand that technical debt can take multiple forms. Here's some of them.

Code-level debt​

Suboptimal code patterns, duplicate code, violations of best practices...

Example: code duplication

function checkUserEmail(email) {
  return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email);
}

function validateAdminEmail(email) {
  const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;  // Duplicated logic
  return emailRegex.test(email);
}

⬇️

// Better approach would be:
function validateEmail(email) {
  return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email);
}

Architectural debt​

Structural issues that affect the entire system, such as tight coupling between components or monolithic architectures that should be modular.

Documentation debt​

Missing, outdated, or inadequate documentation.

Test debt​

Non-sufficient test coverage, or overly complex test suites.

Infrastructure debt​

Outdated dependencies, deployment processes, or development environments.

Technical debt is inevitable in most software projects. The key ain't to eliminate it entirely (that obviously not possible in the real world) but to manage it strategically.

When to Pay Off Technical Debt​

When It Directly Impacts User Experience​

If technical debt is causing visible issues for end users, such as slow performances, frequent crashes, or security vulnerabilities it should be addressed immediately. Those issues directly affect your product's reputation and user experience.

Example: Performance debt affecting user experience

// Before: Inefficient API calls causing lag
async function loadDashboard() {
  const userData = await fetchUserData();   // 500ms
  const statsData = await fetchStatsData(); // 700ms
  const notifData = await fetchNotifData(); // 600ms
  // Total: ~1800ms (sequential calls)
  
  renderDashboard(userData, statsData, notifData);
}

⬇️

// After: Optimized parallel API calls
async function loadDashboard() {
  const [userData, statsData, notifData] = await Promise.all([
    fetchUserData(),
    fetchStatsData(),
    fetchNotifData()
  ]);
  // Total: ~700ms (parallel calls)
  
  renderDashboard(userData, statsData, notifData);
}

When Development Velocity Is Decreasing​

If your team is spending way more time working around technical issues in the codebase than bringing new features, it's a strong signal that technical debt is eating your velocity. Track those metrics over time:

  • Time spent on bug fixes vs. new feature development
  • Average time to implement new features
  • Frequency of unexpected issues during deployment

When these metrics show a negative trend, it's the time to allocate resources to paying down debt.

When Adding New Features Suddenly Becomes Excessively Complex​

If seemingly simple features require disproportionate effort due to the complexity of the codebase, technical debt is likely the culprit. This is particularly evident when:

  • Simple changes require modifications in multiple places
  • Adding new functionality requires extensive understanding of unrelated parts of the system
  • Developers consistently underestimate the time required for new features (Trust me, whether you’ve been coding since floppy disks or the cloud was just literal water vapor, your estimates will still be hilariously wrong)

When Onboarding New Team Members/Interns Takes Too Long​

If new developers struggle to understand the codebase and are able to contribute and fix issues in a reasonable time, it could indicate excessive technical debt. Don't understimate the power of a clean, well-structured codebase with appropriate documentation. It will accelerate onboarding and reduce the learning curve exponentially.

You Are Scaling​

What worked for 100 users may fall apart at 1000. Scalability is one of the top reasons to pay off infrastructure or architectural debt.

When to Live With Technical Debt​

When Time-to-Market Is Critical​

In highly competitive markets or when working against tight deadlines, accepting some technical debt might be necessary to ship products on time. This is especially true for startups or new products where market validation is far more important than perfect code.

Example: Expedient MVP implementation with acknowledged debt

/*
 TODO: Technical Debt - Current Implementation
 This is a simplified implementation to meet the MVP launch deadline.
 Known limitations:
    - No caching mechanism (could cause performance issues at scale)
    - In-memory storage (will need DB implementation for production)
    - No error handling for network failures
 */

async function fetchProducts() {
  // Simplified implementation for MVP
  let products = {};
  const response = await fetch('/api/products');
  const data = await response.json();

  data.forEach(item => {
    products[item.id] = item;
  });

  return Object.values(products);
}

When the Code Is in a Rarely Changed Area​

Not all parts of a codebase are created equal. Some modules or components rarely change after initial development. Technical debt in these stable areas might not be worth addressing if they work correctly and don't affect the rest of the system.

When the Cost of Fixing Exceeds the Benefits​

Sometimes, the effort required to fix technical debt outweighs the benefits. This is particularly true for:

  • Legacy systems approaching retirement
  • Code that will soon be replaced by a new implementation
  • Non-critical features with limited usage

When Technical Debt Is Isolated​

If the technical debt is well-contained and ain't affect other parts of the system, it becomes acceptable to live with it and ain't become the end of the world and hands of destruction 😜.

When Your Team Is Undergoing Significant Changes​

During periods like team transitions, onboarding multiple new members, or dealing with organizational restructuration, maintaining stability might be more important than paying down technical debt. You should wait for a period of team stability before tackling significant refactoring efforts.

Practical Strategies for Technical Debt Management​

Allocate Regular Time for Debt Reduction​

Many successful development teams allocate a fixed percentage of their time (e.g., 20%) to addressing technical debt. This creates a sustainable approach to debt management without sacrificing feature development.

Practice Continuous Refactoring​

Instead of large, risky refactoring, incorporate continuous refactoring into your development workflow. This reduces the risk and makes debt reduction more manageable.

Documentation​

Use TODOs, comments, or issue trackers to record what was done and why. Don’t let debt hide.

Measuring the Impact of The Technical Debt​

In order to make relevant decisions about technical debt, you need to measure its impact. Here are concrete metrics to track.

Development Velocity​

Track how long it takes to implement similar features over time.

Code Churn​

Measure how frequently code changes in specific areas.

Build and Deployment Metrics​

Track build failures, deployment issues, and rollbacks.

Static Analysis Results​

Use tools in your pipelines workflow like Ruff, Bandit, or ESLint to identify code quality issues.

Real-World Case Studies​

Case Study 1: Etsy's Continuous Deployment Revolution​

Etsy faced significant technical debt in their deployment process, with infrequent, painful deployments that slowed innovation. Instead of a massive overhaul, they gradually transformed their process:

  1. They introduced automated testing and continuous integration
  2. They focused on small, incremental improvements to their deployment pipeline
  3. They built tools to increase visibility into the deployment process

This gradual approach allowed them to move from deployments every few weeks to multiple deployments per day, without disrupting their business operations.

Case Study 2: Twitter's Rewrite of Their Timeline Service​

Twitter's timeline (a.k.a X now) service accumulated significant technical debt as the platform grew. They decided to rewrite it completely, but did so incrementally:

  1. They built the new system alongside the old one
  2. They gradually moved traffic to the new system
  3. They maintained backward compatibility throughout the transition

This approach allowed them to replace a critical service without any disruption of the user experience.

Conclusion​

Most of the time, the successful approach to manage technical debt is a balanced one: allocate regular time for debt reduction, establish clear metrics for tracking debt, and build a culture that values code quality alongside feature delivery.

Remember that the goal ain't getting the perfect code, but a codebase that enables your team to deliver value to users efficiently and sustainably. By making informed decisions about when to pay off technical debt and when to live with it, you can strike the right balance between speed and sustainability in your development process.

References and Further Reading​