分布式追踪为何重要
跨多个服务跟踪一个请求
分布式追踪为何重要 是 CoddyKit 上的免费 Spring Boot 4 Microservices & REST APIs 课时。 这是第 1 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Spring Boot 4 Microservices & REST APIs 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Spring Boot 4 Microservices & REST APIs 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
The microservices visibility gap
When one user request flows through many services, a failure or slowdown is hard to locate. Distributed tracing stitches the whole journey into a single, viewable timeline.
Trace and span
Two core concepts:
- A trace represents one end-to-end request
- A span represents one unit of work within it (e.g. a single service call)
Trace and span IDs
Every trace gets a traceId; every span gets a spanId and a reference to its parent span. These IDs propagate from service to service so the pieces can be reassembled.
Context propagation
The trace context is carried between services, usually in HTTP headers (e.g. W3C traceparent). Downstream services read it and continue the same trace instead of starting a new one.
// example incoming header (W3C Trace Context)
// traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01What a trace reveals
A trace view shows each span's duration as a waterfall, so you instantly see which service is the bottleneck, where an error originated, and how calls fan out.
Three pillars of observability
Tracing complements the other two pillars:
- Metrics - aggregated numbers (latency, throughput)
- Logs - discrete events
- Traces - causal request flow across services
Where Micrometer fits
Micrometer Tracing is Spring's tracing abstraction. It creates and propagates spans for you, with pluggable backends (Brave/OpenTelemetry) and exporters (Zipkin).
Where Zipkin fits
Zipkin is a tracing backend: services send their finished spans to it, and it stores and visualizes the assembled traces in a web UI.
Automatic instrumentation
Much instrumentation is automatic: incoming HTTP requests, RestTemplate/WebClient calls, and messaging get spans without code changes once tracing is on.
Sampling
Tracing every request can be expensive. Sampling records only a fraction of traces. A probability like 0.1 records 10%, balancing insight against overhead.
management:
tracing:
sampling:
probability: 0.1 # sample 10% of requestsThe payoff
With tracing, debugging a slow or failing distributed request changes from guesswork across many logs to opening one trace and reading the waterfall. It is essential at scale.
Quick Check
Confirm the core tracing concepts.
Recap
You learned why tracing matters:
- A trace = whole request; a span = one unit of work
- traceId/spanId propagate via headers across services
- Micrometer creates spans; Zipkin stores and visualizes them
- Sampling controls overhead
常见问题解答
「分布式追踪为何重要」课时是免费的吗？
是的 — 「分布式追踪为何重要」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Spring Boot 4 Microservices & REST APIs 课程的其余内容，请升级到 CoddyKit PRO。 Spring Boot 4 Microservices & REST APIs 课程共包含 4 节课。
「分布式追踪为何重要」这节课中我会学到什么？
跨多个服务跟踪一个请求 你通过在浏览器中直接运行的动手代码来练习 Spring Boot 4 Microservices & REST APIs，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 Spring Boot 4 Microservices & REST APIs 需要有经验吗？
无需任何先前经验。CoddyKit 上的 Spring Boot 4 Microservices & REST APIs 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 1 节课，共 4 节。
「分布式追踪为何重要」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 Spring Boot 4 Microservices & REST APIs 课中编写并运行代码吗？
能。每节 Spring Boot 4 Microservices & REST APIs 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。