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源码与架构

如何组织代码，让它在增长、团队扩张和需求变化中依然稳固。

深入浅出地讲解软件架构与代码组织方式——从 Ports & Adapters、Clean Architecture，到依赖管理、模块边界，以及每种方案背后的权衡取舍。内容基于图解、真实示例和可落地的经验，适用于从个人项目到企业级系统的各种规模。

源码与架构

Scaling the Database: Indexes, Read Replicas, Caching, and Sharding — In That Order

The database is almost always the first thing to buckle under growth — and the first thing engineers over-engineer in a panic. A no-hype ladder for scaling the data layer: why you measure and add an index before touching hardware, how read replicas exploit the read/write asymmetry (and the replication-lag trap they bring), where caching helps and why invalidation is the hard part, and when you finally reach for partitioning and sharding — the one decision that is genuinely hard to undo.

2026年6月4日14 分钟阅读

源码与架构

You Can't Fix What You Can't See: Logs, Metrics, Traces, and SLOs at Scale

In a monolith, debugging was almost cosy — one log file, one process, one place the truth lived. Distributed systems quietly took that away: one request now fans out across a dozen services, and when it breaks there is no single log to read. A no-hype guide to seeing your system at scale: the three pillars (metrics, logs, traces) and the question each one answers, why a single propagated trace ID is the highest-leverage habit you can adopt, how SLOs turn reliability into an error budget you can spend, and how to alert on symptoms so on-call doesn't burn out.

2026年6月4日14 分钟阅读

源码与架构

Events, Queues, and the Art of Not Calling Each Other: Event-Driven Architecture, Explained

When services hold hands through synchronous calls, latency adds up and one slow dependency takes down checkout. A no-hype guide to event-driven architecture: sync vs async, commands vs events, what brokers really promise (at-least-once, not exactly-once), choreography vs orchestration, and exactly when NOT to reach for events.

2026年6月3日13 分钟阅读

源码与架构

Who Owns the Data? Database-per-Service, Sagas, and Eventual Consistency Without Tears

Splitting code is the easy half — splitting data is where distributed systems humble you. A practical guide to owning data across services: why a shared database is a distributed monolith, the trade from ACID to eventual consistency, the dual-write bug and the outbox that fixes it, sagas with compensating actions, and when CQRS and event sourcing are worth their lifetime cost.

2026年6月3日13 分钟阅读

源码与架构

The Distributed-Systems Tax, Paid: Timeouts, Retries, Circuit Breakers, and Idempotency

The moment a call leaves your process it can be slow, fail, or happen twice — and that is the normal case, not the exception. The resilience toolkit, explained plainly: why timeouts come first, how retries become a self-inflicted DDoS without backoff and jitter, why idempotency is the price of retrying, and how circuit breakers, bulkheads, graceful degradation, and observability keep one bad dependency from taking down everything.

2026年6月3日13 分钟阅读

源码与架构