监控专家技能：全面可观测性、性能监控与告警系统实施指南

monitoring-expert by jeffallan/claude-skills

1,100 周安装量

7,200 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/jeffallan/claude-skills --skill monitoring-expert

开发运维监控

🇨🇳中文介绍

监控专家

可观测性与性能专家，负责实施全面的监控、告警、追踪和性能测试系统。

核心工作流

评估 — 识别需要监控的内容（SLI、关键路径、业务指标）
埋点 — 向应用程序添加日志记录、指标和追踪（参见下方示例）
收集 — 配置聚合与存储（Prometheus 抓取、日志传输器、OTLP 端点）；在继续之前验证数据是否到达
可视化 — 使用 RED（请求率/错误/延迟）或 USE（利用率/饱和度/错误）方法构建仪表板
告警 — 在关键路径上定义阈值和异常告警；在部署前验证不会产生误报洪流

快速入门示例

结构化日志记录（Node.js / Pino）

import pino from 'pino';

const logger = pino({ level: 'info' });

// 良好做法 — 结构化字段，包含关联 ID
logger.info({ requestId: req.id, userId: req.user.id, durationMs: elapsed }, 'order.created');

// 不良做法 — 字符串插值，无关联 ID
console.log(`Order created for user ${userId}`);

Prometheus 指标（Node.js）

import { Counter, Histogram, register } from 'prom-client';

const httpRequests = new Counter({
  name: 'http_requests_total',
  help: 'Total HTTP requests',
  labelNames: ['method', 'route', 'status'],
});

const httpDuration = new Histogram({
  name: 'http_request_duration_seconds',
  help: 'HTTP request latency',
  labelNames: ['method', 'route'],
  buckets: [0.05, 0.1, 0.3, 0.5, 1, 2, 5],
});

// 为路由添加埋点
app.use((req, res, next) => {
  const end = httpDuration.startTimer({ method: req.method, route: req.path });
  res.on('finish', () => {
    httpRequests.inc({ method: req.method, route: req.path, status: res.statusCode });
    end();
  });
  next();
});

// 暴露抓取端点
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', register.contentType);
  res.end(await register.metrics());
});

广告位招租

在这里展示您的产品或服务

触达数万 AI 开发者，精准高效

联系我们

OpenTelemetry 追踪（Node.js）

import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { trace } from '@opentelemetry/api';

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),
});
sdk.start();

// 围绕关键操作的手动 Span
const tracer = trace.getTracer('order-service');
async function processOrder(orderId) {
  const span = tracer.startSpan('order.process');
  span.setAttribute('order.id', orderId);
  try {
    const result = await db.saveOrder(orderId);
    span.setStatus({ code: SpanStatusCode.OK });
    return result;
  } catch (err) {
    span.recordException(err);
    span.setStatus({ code: SpanStatusCode.ERROR });
    throw err;
  } finally {
    span.end();
  }
}

Prometheus 告警规则

groups:
  - name: api.rules
    rules:
      - alert: HighErrorRate
        expr: |
          rate(http_requests_total{status=~"5.."}[5m])
          / rate(http_requests_total[5m]) > 0.05
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Error rate above 5% on {{ $labels.route }}"

import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  stages: [
    { duration: '1m', target: 50 },   // 爬升阶段
    { duration: '5m', target: 50 },   // 持续负载
    { duration: '1m', target: 0 },    // 下降阶段
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],  // 95% 分位数 < 500 毫秒
    http_req_failed:   ['rate<0.01'],  // 错误率 < 1%
  },
};

export default function () {
  const res = http.get('https://api.example.com/orders');
  check(res, { 'status is 200': (r) => r.status === 200 });
  sleep(1);
}

根据上下文加载详细指导：

主题	参考	加载时机
日志记录	`references/structured-logging.md`	Pino, JSON 日志记录
指标	`references/prometheus-metrics.md`	Counter, Histogram, Gauge
追踪	`references/opentelemetry.md`	OpenTelemetry, spans
告警	`references/alerting-rules.md`	Prometheus 告警
仪表板	`references/dashboards.md`	RED/USE 方法, Grafana
性能测试	`references/performance-testing.md`	负载测试, k6, Artillery, 基准测试
性能剖析	`references/application-profiling.md`	CPU/内存剖析, 瓶颈
容量规划	`references/capacity-planning.md`	扩缩容, 预测, 预算

使用结构化日志记录（JSON）
包含用于关联的请求 ID
为关键路径设置告警
监控业务指标，而不仅仅是技术指标
使用适当的指标类型（counter/gauge/histogram）
实现健康检查端点

记录敏感数据（密码、令牌、PII）
为每个错误都设置告警（告警疲劳）
在日志中使用字符串插值（应使用结构化字段）
在分布式系统中忽略关联 ID

🇺🇸English

Monitoring Expert

Observability and performance specialist implementing comprehensive monitoring, alerting, tracing, and performance testing systems.

Core Workflow

Assess — Identify what needs monitoring (SLIs, critical paths, business metrics)
Instrument — Add logging, metrics, and traces to the application (see examples below)
Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
Visualize — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
Alert — Define threshold and anomaly alerts on critical paths; validate no false-positive flood before shipping

Quick-Start Examples

Structured Logging (Node.js / Pino)

import pino from 'pino';

const logger = pino({ level: 'info' });

// Good — structured fields, includes correlation ID
logger.info({ requestId: req.id, userId: req.user.id, durationMs: elapsed }, 'order.created');

// Bad — string interpolation, no correlation
console.log(`Order created for user ${userId}`);

Prometheus Metrics (Node.js)

import { Counter, Histogram, register } from 'prom-client';

const httpRequests = new Counter({
  name: 'http_requests_total',
  help: 'Total HTTP requests',
  labelNames: ['method', 'route', 'status'],
});

const httpDuration = new Histogram({
  name: 'http_request_duration_seconds',
  help: 'HTTP request latency',
  labelNames: ['method', 'route'],
  buckets: [0.05, 0.1, 0.3, 0.5, 1, 2, 5],
});

// Instrument a route
app.use((req, res, next) => {
  const end = httpDuration.startTimer({ method: req.method, route: req.path });
  res.on('finish', () => {
    httpRequests.inc({ method: req.method, route: req.path, status: res.statusCode });
    end();
  });
  next();
});

// Expose scrape endpoint
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', register.contentType);
  res.end(await register.metrics());
});

OpenTelemetry Tracing (Node.js)

import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { trace } from '@opentelemetry/api';

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),
});
sdk.start();

// Manual span around a critical operation
const tracer = trace.getTracer('order-service');
async function processOrder(orderId) {
  const span = tracer.startSpan('order.process');
  span.setAttribute('order.id', orderId);
  try {
    const result = await db.saveOrder(orderId);
    span.setStatus({ code: SpanStatusCode.OK });
    return result;
  } catch (err) {
    span.recordException(err);
    span.setStatus({ code: SpanStatusCode.ERROR });
    throw err;
  } finally {
    span.end();
  }
}

Prometheus Alerting Rule

groups:
  - name: api.rules
    rules:
      - alert: HighErrorRate
        expr: |
          rate(http_requests_total{status=~"5.."}[5m])
          / rate(http_requests_total[5m]) > 0.05
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Error rate above 5% on {{ $labels.route }}"

k6 Load Test

import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  stages: [
    { duration: '1m', target: 50 },   // ramp up
    { duration: '5m', target: 50 },   // sustained load
    { duration: '1m', target: 0 },    // ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],  // 95th percentile < 500 ms
    http_req_failed:   ['rate<0.01'],  // error rate < 1%
  },
};

export default function () {
  const res = http.get('https://api.example.com/orders');
  check(res, { 'status is 200': (r) => r.status === 200 });
  sleep(1);
}

Reference Guide

Load detailed guidance based on context:

Topic	Reference	Load When
Logging	`references/structured-logging.md`	Pino, JSON logging
Metrics	`references/prometheus-metrics.md`	Counter, Histogram, Gauge
Tracing	`references/opentelemetry.md`	OpenTelemetry, spans
Alerting	`references/alerting-rules.md`	Prometheus alerts
Dashboards	`references/dashboards.md`

Constraints

MUST DO

Use structured logging (JSON)
Include request IDs for correlation
Set up alerts for critical paths
Monitor business metrics, not just technical
Use appropriate metric types (counter/gauge/histogram)
Implement health check endpoints

MUST NOT DO

Log sensitive data (passwords, tokens, PII)
Alert on every error (alert fatigue)
Use string interpolation in logs (use structured fields)
Skip correlation IDs in distributed systems

Weekly Installs

1.1K

Repository

jeffallan/claude-skills

GitHub Stars

7.2K

First Seen

Jan 20, 2026

Security Audits

Gen Agent Trust HubPass SocketPass SnykPass

Installed on

opencode940

gemini-cli905

codex888

github-copilot847

claude-code830

cursor802