30 Architectural Principles for Building Scalable Distributed Systems

Basic Principles

Principle 1: KISS (Keep it simple, stupid) – solve problems with the simplest possible solution.

Guide: Simplicity often requires more thought and time to achieve clear, understandable code.

Principle 2: YAGNI (You Aren’t Gonna Need It) – avoid building features that are not currently required.

Guide: Resist the temptation to implement speculative functionality that may never be used.

Principle 3: Crawl, walk, run – first get a working version, then iteratively improve and expand it.

Principle 4: Automate testing – treat all aspects of the product as automatable.

Guide: While the exact level of automation may vary, testing should be a core focus.

Principle 5: Consider ROI – only implement work that provides sufficient value.

Principle 6: Know your users – tailor effort to actual user needs rather than imagined ones.

Guide: Avoid building flashy UI when users prefer command‑line tools.

Principle 7: Design and test features in isolation to avoid bottlenecks caused by inter‑dependencies.

Principle 8: Avoid unnecessary fancy solutions that add complexity without real benefit.

Guide: Keep communication and code simple.

Feature Selection

Principle 9: Embrace MVP – deliver a minimal viable product, gather feedback, then iterate.

Principle 10: Implement as few features as possible; remove or defer unnecessary ones.

Principle 11: Defer work until it is truly needed, unless it impacts core processes.

Principle 12: Say no to unreasonable requests and propose better solutions; guide users rather than follow trends.

Server Design and Concurrency

Principle 13: Understand the full stack—from hardware to OS to language—to optimize I/O calls.

Principle 14: Apply Amdahl’s Law; use concurrent data structures and synchronization only when necessary, and keep lock hold times minimal.

Principle 15: In non‑blocking, event‑driven architectures, never block threads with I/O operations.

Distributed Systems

Principle 16: Stateless systems are inherently scalable; avoid stateful designs when possible.

Principle 17: Strive for exactly‑once delivery, but recognize its difficulty and aim for at‑least‑once with idempotent operations.

Principle 18: Make operations idempotent to simplify recovery.

Principle 19: Know the CAP theorem; use compensation mechanisms instead of distributed transactions when feasible.

Principle 20: Distributed consistency does not scale well; keep node counts modest (ideally ≤ 8).

Principle 21: Accept that latency and failures are inevitable in distributed environments.

User Experience

Principle 22: Understand user personas and goals; tailor interfaces accordingly.

Principle 23: The best product requires no manual.

Guide: Even in agile development, essential documentation (e.g., release notes) remains valuable.

Principle 24: When forced to choose, provide sensible defaults rather than exposing every option to users.

Principle 25: Always set reasonable default values for configurations.

Principle 26: Provide example values for configuration settings.

Principle 27: Configuration fields must be understandable and directly editable by users.

Principle 28: Reject unknown configuration values with clear errors; never silently ignore them.

Hard Problems

Principle 29: New programming languages rarely simplify problems; avoid switching languages without strong justification.

Principle 30: Complex drag‑and‑drop UIs are costly; only attempt them with substantial resources.

In an ideal world, a platform consists of orthogonal components (security, messaging, registry, validation, analytics) that can be combined independently. Reality, however, forces trade‑offs, early duplication, and added complexity, especially in distributed systems.

Conclusion

Architects should act like gardeners—pruning and guiding rather than dictating—using a well‑accepted principles list as an anchor for discussion and as a learning path for junior architects.