Guidelines for Building Long‑Lived, Stable Systems: Goals, Practices, and Continuous Improvement

In previous posts we introduced coding standards and useful tools like Git; this article continues the discussion by presenting a comprehensive methodology for project development.

Part.1 Goal

We write code to deliver functionality for a system, and the author aims to build systems that can run stably for ten years.

Part.2 How to Do It

Achieving long‑term stability requires a holistic view, including:

Identifying required environments such as servers, databases, data centers, and networks.

Understanding potential runtime problems.

Designing clear, layered system architecture.

Writing clear, understandable code.

Part.3 Problems Encountered During System Operation

Operations‑related issues often determine whether a system can stay stable for a decade. Performance is less important than operability.

Carrier and Data Center Selection

In China, the main carriers are Telecom and Unicom; a reliable service should be deployed in data centers connected to both. Using at least two data centers, preferably in the same city (e.g., Beijing or Shanghai), improves reliability and reduces latency for MySQL master‑slave setups.

Cross‑Region Active‑Active Issues

If one data center fails, a read‑only replica cannot serve traffic, so active‑active designs must ensure failover without loss of functionality.

Server Selection

Different hardware vendors can affect performance; the author experienced quality issues with a particular vendor and now explicitly avoids that vendor’s machines.

New Service Platform Selection

The service evolved from physical machines to virtualization and now to container platforms; understanding the underlying platform is essential for making informed decisions.

Service Monitoring

After deployment, issues such as disk full, process crashes, memory leaks, or storage failures can arise; robust monitoring and alerting are critical to detect and resolve problems quickly.

Part.4 Continuous Improvement

Personal growth through continuous learning and reflection is vital; the author finds satisfaction in constantly improving coding skills.

Part.5 Conclusion

Key takeaways include reading good books, summarizing and reflecting on past projects, and refactoring undesirable code without using “no time” as an excuse, all aimed at building systems that remain stable for ten years.