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服务器中需要测量什么

跟踪延迟、错误和工具使用情况。

服务器中需要测量什么 是 CoddyKit 上的免费 MCP Academy 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 MCP Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MCP Academy 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。

Why Measure at All?

Once your MCP server runs in the wild, you cannot fix what you cannot see. Observability turns guesswork into clear signals about how it behaves. 🔍

The Three Pillars

Observability rests on three signals: logs, metrics, and traces. Today you focus on metrics, the numbers that summarize health at a glance.

Latency: How Slow?

The first thing to track is latency: how long each tool call takes from request to response. Slow tools frustrate the model and the user alike.

Don't Trust the Average

One slow call can hide behind a happy average. Watch percentiles like p95 and p99 so you catch the worst experiences your callers actually feel.

Error Rate: How Often Broken?

Track your error rate: the share of tool calls that fail. A rising rate is your earliest warning that something upstream just broke. ⚠️

Throughput: How Busy?

Count calls over time to see throughput. Knowing requests per minute tells you when load spikes and whether your server can keep up.

Per-Tool Usage

Break metrics down by tool name. Knowing which tool is hot, slow, or failing lets you fix the exact part that matters instead of guessing.

Counters vs Gauges

A counter only goes up, like total calls. A gauge moves both ways, like active sessions right now. Pick the type that fits the thing you measure.

A Simple Timer in Python

You can capture latency with nothing more than a timer around your tool body, then record the elapsed seconds.

import time

start = time.perf_counter()
result = do_work()
elapsed = time.perf_counter() - start
print("latency_seconds", elapsed)

Label Your Metrics

Attach labels like tool name and status to every metric. Labels let you slice one number into the views that answer real questions.

Golden Signals

A handy checklist is the golden signals: latency, traffic, errors, and saturation. Cover these four and you see most problems before users do.

Quick Check

Let us make sure the latency idea stuck.

Recap

You now know what to measure: latency, errors, throughput, and per-tool usage. These numbers turn a silent server into one you can actually trust. 🎯

常见问题解答

「服务器中需要测量什么」课时是免费的吗？

是的 — 「服务器中需要测量什么」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 MCP Academy 课程的其余内容，请升级到 CoddyKit PRO。 MCP Academy 课程共包含 4 节课。

「服务器中需要测量什么」这节课中我会学到什么？

跟踪延迟、错误和工具使用情况。你通过在浏览器中直接运行的动手代码来练习 MCP Academy，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 MCP Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 MCP Academy 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。

「服务器中需要测量什么」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 MCP Academy 课中编写并运行代码吗？

能。每节 MCP Academy 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。

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