The Hidden Costs of Overdesign and Bad Practices in API Systems

In software development, simplicity and clarity are often sacrificed in favor of overly complex solutions. While it can be tempting to add more features and intricate designs to ensure robustness, overdesign and poor practices can have significant consequences. They frustrate developers, lead to inefficiencies, increase costs, and put unnecessary strain on system resources. A recent example involving a team that has faced challenges with complexity highlights the pitfalls of such an approach.

Overdesign: The Problem of Too Much Complexity

Overdesign occurs when systems are built with more complexity than necessary. This might manifest in bloated APIs, convoluted data flows, or excessive checks and processes that don’t add substantial value. The goal is often to anticipate future problems, but this approach typically results in cumbersome systems that are difficult to maintain and scale.

In one case, a company found itself paying a hefty price just to host two API services and a portal for viewing transactions. The system had become bloated, requiring an excessive amount of resources to perform relatively simple tasks. Not only was the design inefficient, but it was also costing the company far more than it should have.

Overdesign as a Reaction to Concurrency Problems

I once spoke with the CIO responsible for this system. He explained that the overly complex architecture was an attempt to resolve an earlier issue: the system couldn’t handle more than 20 concurrent API transactions without crashing. To solve this, they decided to completely overhaul the system’s architecture. However, instead of addressing the root cause of their concurrency problems in a focused and effective way, they rebuilt the system with more features and complexity, thinking this would solve their scaling issues.

The result? A system far more expensive and resource-hungry than necessary. It felt like they didn’t fully understand the problem they were trying to solve, and instead of refining their approach, they opted for an overkill solution that didn’t even fully address the initial issues.

Bad Practices Compound the Issue

Not only was the system overdesigned, but bad practices also compounded the problem. After the new architecture was in place, the team still encountered critical issues, such as the inability to retrieve audit logs during a transaction dispute. This was a glaring oversight in such a crucial system, where basic traceability should be a given.

In another instance, a transaction dispute arose, and this time the team was able to provide audit logs — but here’s the shocking part: a developer revealed that these logs came from his personal files. Wait, what? Audit logs for production transactions coming from a developer’s personal logs? This raises serious concerns. Is a portion of the production data or logs being stored on a developer’s local machine? Regardless, this is clearly another example of poor practice that further erodes the credibility of the system’s design.

A History of Iterations with Little Improvement

Over the years, the team implemented several versions of the system, akin to upgrade cycles, but these revisions didn’t seem to yield any significant improvements. In fact, the latest iteration, where the API returns no response body for a 200 status code, raises questions about whether the design is now even worse than before or just as problematic. From an outsider’s perspective, the core issues seem unresolved, with complexity continuing to burden the system.

The Consequences of Overdesign and Poor Practices

1. Increased Resource Consumption:
   Overdesign often leads to systems consuming far more resources than necessary, resulting in excessive costs for what should have been a relatively lightweight service.
2. Developer Frustration:
   Complex systems are difficult to maintain and understand, leading to confusion, longer development cycles, and increased potential for bugs. This frustration can negatively impact job satisfaction and team morale.
3. Diminished Performance:
   Overdesigned systems can introduce performance bottlenecks, resulting in slower response times and degraded user experiences, which can lead to decreased user engagement.
4. Hard-to-Integrate Systems:
   APIs that are overly complicated become challenging to integrate with other systems, hindering collaboration and reducing overall effectiveness.
5. Wasted Money:
   Companies end up paying significantly more than necessary for cloud infrastructure, third-party services, and additional developer time spent managing complexity.
6. Increased Time to Market:
   Complex designs often lead to longer development cycles, delaying product launches and allowing competitors to gain an advantage.
7. Knowledge Silos:
   Overdesign can create knowledge silos within teams, making it difficult for new members to onboard and for organizations to remain agile.
8. Higher Testing and Maintenance Costs:
   The complexity of overdesigned systems leads to increased costs associated with quality assurance and ongoing maintenance, straining resources further.

Best Practices to Avoid Overdesign and Bad Practices

1. Keep It Simple:
   Focus on delivering essential features that meet core user needs without unnecessary complexity. This promotes easier maintenance and quicker onboarding.
2. Start Small and Scale:
   Begin with a minimum viable product (MVP) that addresses fundamental needs. Iterate based on real-world feedback rather than speculative requirements.
3. Follow Established Standards:
   Adhere to well-known design patterns and API standards to ensure ease of use, maintenance, and scalability.
4. Engage Stakeholders Early:
   Collaborate with developers, analysts, and end-users throughout the design process to align the system with actual problems and needs.
5. Monitor Resource Usage:
   Continuously assess system performance and resource consumption to identify inefficiencies and optimize before complexity spirals out of control.
6. Document Thoroughly:
   Maintain comprehensive documentation that clearly outlines the system’s architecture and features, aiding team understanding and onboarding.
7. Implement Incremental Improvements:
   Focus on making small, manageable enhancements based on feedback and metrics rather than attempting large-scale overhauls.
8. Prioritize User Experience:
   Keep the end-user in mind throughout the design process to ensure that features genuinely address user needs without adding unnecessary complexity.
9. Encourage Cross-Functional Collaboration:
   Foster collaboration among various teams to incorporate different perspectives and ensure holistic solutions.
10. Regularly Review and Refactor:
    Schedule periodic reviews of the system’s architecture to identify areas for improvement and streamline the codebase as needed.

Conclusion

Overdesign and poor practices are common traps that many development teams fall into when faced with problems like scalability or performance bottlenecks. While it’s natural to want to build robust systems, adding unnecessary layers of complexity can cause more harm than good. In the case of the team that over-engineered its API to solve concurrency problems, the result was a system that consumed far more resources than necessary, riddled with bad practices that further eroded its efficiency and traceability.

The lesson here is simple: when designing systems, focus on the real problems at hand and avoid the temptation to overcomplicate. By adhering to simplicity, established best practices, and a well-defined purpose, teams can create more efficient, scalable, and cost-effective systems that serve their intended purpose without wasting resources.