12 Coding Anti‑Patterns That Sabotage Your Microservice Projects (And How to Avoid Them)
This article lists twelve common coding anti‑patterns—such as over‑splitting services, excessive method length, misleading comments, and ignoring logging—that dramatically reduce code readability and maintainability, illustrated with a fictional developer’s missteps and practical lessons for better software engineering.
1. One Table per Microservice
The developer embraces microservices to the extreme, creating a separate service for every database table, which leads to a sprawling architecture, excessive RPC calls, versioning headaches, and difficult deployments for new team members.
2. Refactoring Without Production Rollout
After refactoring, the new logic is only enabled in the test environment, leaving production unchanged; new developers mistakenly modify the “new logic” without realizing the feature flag is off, causing failed releases and overtime.
3. Methods Longer Than 1,000 Lines
Long, monolithic methods are believed to improve readability and showcase skill, but they make onboarding new developers painfully slow and increase bug risk.
4. Deeply Nested Control Structures
Excessive nesting of if/try/catch blocks creates unreadable code that overwhelms newcomers, despite the author’s confidence in its correctness.
5. Random Variable Names
Variables are named arbitrarily (e.g., str1, list2) to appear artistic, which later leads to confusion and forgotten meanings.
6. Misleading Comments
Comments are deliberately altered to convey incorrect information, causing new developers to waste time deciphering false guidance.
7. Ignoring Comment Updates
Code changes are made without updating existing comments, resulting in mismatched documentation and further confusion.
8. Copy‑Paste Code
Code is duplicated across the codebase instead of being refactored, leading to duplicated bugs and increased maintenance effort.
9. Ignoring Technical Specs
Complex technical designs are written but ignored during implementation, causing a gap between documentation and actual code.
10. No Logging
The developer never adds logs, making troubleshooting impossible when production issues arise.
11. Overkill Frameworks for Simple Problems
Heavyweight rule‑engine frameworks are introduced to solve trivial strategy selection, adding unnecessary complexity.
12. Reinventing Wheels
Instead of using proven libraries (e.g., Redisson for distributed locks), custom solutions are built, often introducing bugs while providing little benefit.
Conclusion
These practices severely degrade code readability and maintainability; developers should avoid them to build clean, maintainable systems.
Author: 五阳神功 Source: juejin.cn/post/7286155742850449471
macrozheng
Dedicated to Java tech sharing and dissecting top open-source projects. Topics include Spring Boot, Spring Cloud, Docker, Kubernetes and more. Author’s GitHub project “mall” has 50K+ stars.
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