Technical Debt Is Killing Your Business

The 2024 Stack Overflow survey revealed that technical debt is the top source of frustration for developers at work.

Technical debt affects 62.4% of developers, making it twice as problematic as the next two most frustrating issues: complex tech stacks and deployment.

There probably isn’t a programmer out there who intentionally writes unclean code to the detriment of the project. But at what point does clean code become unclean?

The concept of “technical debt” was first introduced by Ward Cunningham, and it’s a useful metaphor to understand the long-term consequences of shortcut decisions in software development.

Just like taking out a loan, technical debt allows you to expedite a process and achieve immediate results.

A development team might push out a new feature quickly to meet a tight deadline or capitalize on a market opportunity. This rapid delivery can provide immediate benefits, such as satisfying customer demands or beating competitors to market.

However, just like a financial loan, technical debt comes with its own costs, which can be thought of as “interest.”

In the context of coding, this interest doesn’t involve money but rather future challenges and reduced efficiency.

Needless to say, you can even rack up so much interest that the amount of interest exceeds your total income, making full repayment impossible.

Skipping important steps like writing tests, having strong coding standards, properly refactoring code, or documenting processes might save time initially, but these omissions can lead to significant issues down the line.

Poorly written or undocumented code becomes a nightmare to maintain, as developers spend extra time deciphering and understanding it.

Over time, these issues accumulate, resulting in slower development cycles and increasing frustration among the team. The codebase becomes fragile, where even small changes can cause unexpected problems elsewhere, leading to a fear of making any modifications.

Eventually, the technical debt must be “paid off” by addressing these shortcomings.

This often involves going back and fixing the shortcuts taken earlier, such as writing tests, refactoring messy code, and improving documentation.

This process can be time-consuming and expensive, especially if the debt has been allowed to accumulate over a long period.

In some cases, the debt can become so overwhelming that it hinders further development, requiring a complete overhaul of the system to continue making progress.

In its early years, Twitter (now called x) faced significant technical debt due to its rapid growth, which the platform wasn’t initially designed to handle.

This resulted in frequent outages, famously known as the “Fail Whale” incidents, where the site would crash and display an image of a whale being lifted by birds.

The technical debt accumulated from these initial design choices made it challenging to scale and manage the increasing load.

To address these issues, Twitter underwent a significant overhaul, transitioning to a more scalable architecture that could better accommodate its growing user base.

In 2011, Target launched its e-commerce website independently, moving away from Amazon’s platform. The website crashed on launch day due to an overwhelming amount of traffic, which it couldn’t handle.

The site was down for nearly 20 hours, leading to significant financial loss and damage to the company’s reputation.

The technical debt was attributed to insufficient load testing and infrastructure not being adequately scaled to handle peak traffic. Target had to invest heavily in infrastructure and backend improvements to ensure such failures didn’t recur.

In February 2017, AWS experienced a significant outage in its S3 (Simple Storage Service) in the US-East-1 region. The outage was caused by a human error during a routine maintenance task, which inadvertently took down a large number of servers.

The outage affected numerous websites and services that relied on S3 for storage, including major companies like Netflix, Reddit, and Adobe.

The incident revealed technical debt in the form of operational dependencies and single points of failure within AWS’s infrastructure. It led to widespread disruptions and highlighted the need for improved failover mechanisms and incident response protocols.

Thus, managing technical debt is crucial for maintaining the long-term health and agility of a software project.

What causes technical debt?

1. Too Much Business Pressure

The need to release features quickly due to business demands forces teams to deliver before the features are fully polished.

This often results in temporary fixes and workarounds that obscure unfinished parts of the project, leading to technical debt.

It’s a delicate balance to get both the business and engineering aspects right.

2. Lack of Tests

When there aren’t enough tests in place, it becomes easy to implement quick fixes and risky solutions. This can lead to significant issues, especially if changes are pushed to production without proper testing.

The consequences can be severe, like accidentally sending incorrect emails to thousands of users or causing data loss.

3. Lack of Documentation

Without proper documentation, onboarding new team members becomes difficult, and the project can come to a standstill if key personnel leave.

This lack of information can lead to a buildup of technical debt as new developers struggle to understand the existing code.

4. Postponed Refactoring

As a project evolves, some parts of the code can become outdated and cumbersome.

If refactoring is postponed, these parts become even more entangled with new code, making future changes more difficult and increasing the technical debt.

5. Incompetence

Technical debt can also result from a lack of experience or skill. The informal term for this is often referred as a skill issue.

Developers who aren’t familiar with best practices may write poor-quality code, contributing to the accumulation of debt.

6. Lack of Interaction Among Team Members

When team members don’t communicate effectively, knowledge isn’t shared, leading to outdated understandings of the project’s processes.

This issue can worsen if junior developers are not properly trained, causing inconsistencies and misunderstandings in the codebase. See reason number 3

7. Lack of Decoupling of Components

Changes in one area can impact the entire system, making it challenging to develop and maintain.

This often happens when a project resembles a monolithic structure rather than being composed of independent modules, making it difficult to isolate and address specific issues.

Fortunately, the industry has adopted the microservices approach for decoupling components. A microservice is a single, lightweight process focused on doing one thing precisely.

8. Lack of Coding Standards

When there isn’t a consistent coding standard in place, developers code according to their own preferences and styles. This leads to a fragmented and inconsistent codebase where different parts of the project follow various conventions.

Without uniformity, the codebase becomes difficult to navigate and understand, especially for new team members or developers who weren’t involved in the original implementation.

It also complicates code reviews, as reviewers may need to address stylistic inconsistencies rather than focusing on the actual logic and functionality of the code.

Moreover, an inconsistent codebase increases the likelihood of bugs and errors, contributing to technical debt. When different coding styles and practices are mixed, maintaining and updating the code becomes more challenging.

Changes in one part of the codebase might not integrate smoothly with others, leading to unexpected issues and additional work.

As a result, the development process slows down, with more time spent on debugging and refactoring instead of building new features.

In the long run, the absence of a consistent coding standard can hinder scalability and complicate implementing large-scale changes or improvements.

It can also negatively impact the team’s morale, as developers may feel frustrated by the lack of clear guidelines and the resulting disorganization.

Therefore, establishing and enforcing coding standards is crucial for maintaining a clean, efficient, and sustainable codebase.

This lack of oversight contributes to technical debt, as varying coding styles and practices can complicate maintenance and future development.

Technical debt may seem harmless now, but it’s a ticking time bomb that can devastate your business if left unchecked.